Regional Outlook
 

FEDERAL DEPOSIT INSURANCE CORPORATION FIRST QUARTER 2001 

FDIC
 

Kansas City
 

Region
 

Division of
 

Insurance
 

John M. Anderlik,
 

Regional Manager
 

Jeff W. Walser,
 

Regional Economist
 

Richard D. Cofer, Jr.,
 

Senior Financial
 

Analyst
 

Regional Perspectives 

◆ LTA Ratios Do Not Always Correlate with NIMs—A surprisingly large 

number of community banks in the Kansas City Region show an unexpected relationship between loan-to-asset ratio and net interest margin. Portfolio composition, 

asset and loan growth, leverage, and funding appear largely responsible for the 

divergence between loan-to-asset ratio and net interest margin. See page 4. 

◆ In the 1980s, Higher LTA Ratios Tended to Boost Net Interest Margins 

but Were Associated with Increased Risk of Failure—A review of community banks prior to the 1980s agricultural crisis shows that loan-to-asset ratio and net 

interest margin frequently were indicators of increased potential for failure. See 

page 9. 

By the Kansas City Region Staff 

In Focus This Quarter 

◆ Credit Problems for U.S. Businesses Continue to Rise—Commercial 

loan quality indicators of insured banks have steadily worsened since 1998. Factors 

contributing to this deterioration include rising financial leverage in the corporate 

sector as well as weaknesses within certain domestic industries. Many market 

observers also have attributed the increase in problem commercial loans to a 

heightened appetite for risk and relaxed underwriting standards from 1996 to 1999. 

The apparent softening in economic conditions in recent months reduces prospects 

that business loan quality will improve any time soon. In the meantime, lenders, 

analysts, and supervisors continue to pay close attention to U.S. business lending 

conditions. See page 12. 

◆ Outlook for Three Industries Facing Uncertainty—Industries as 

diverse as telecommunications, health care, and textiles have been experiencing 

problems, despite the economic expansion that began nine years ago. Although the 

sources of their difficulties are quite different, these industries share some common 

concerns and challenges. Fierce competition characterizes their operating environment. Armed with a better grasp of the origins of stress in these industries, we will 

have a better basis for understanding the lending risks associated with a changing 

policy and economic environment in the years to come. See page 20. 

By the Division of Insurance Staff 

A Publication of the Division of Insurance
 
The Regional Outlook is published quarterly by the Division of Insurance of the Federal Deposit 

Insurance Corporation as an information source on banking and economic issues for insured 

financial institutions and financial institution regulators. It is produced for the following eight 

geographic regions: 

Atlanta Region (AL, FL, GA, NC, SC, VA, WV)
 

Boston Region (CT, MA, ME, NH, RI, VT)
 

Chicago Region (IL, IN, MI, OH, WI)
 

Dallas Region (CO, NM, OK, TX)
 

Kansas City Region (IA, KS, MN, MO, ND, NE, SD)
 

Memphis Region (AR, KY, LA, MS, TN)
 

New York Region (DC, DE, MD, NJ, NY, PA, PR, VI)
 

San Francisco Region (AK, AS, AZ, CA, FM, GU, HI, ID, MT, NV, OR, UT, WA, WY)
 

Single copy subscriptions of the Regional Outlook can be obtained by sending the subscription 

form found on the back cover to the FDIC Public Information Center. Contact the Public Information Center for current pricing on bulk orders. 

The Regional Outlook is available on-line by visiting the FDIC’s website at www.fdic.gov. For 

more information or to provide comments or suggestions about the Kansas City Region’s Regional Outlook, please call John Anderlik at (816) 234-8198 or send an e-mail to janderlik@fdic.gov. 

The views expressed in the Regional Outlook are those of the authors and do not necessarily reflect 

official positions of the Federal Deposit Insurance Corporation. Some of the information used in 

the preparation of this publication was obtained from publicly available sources that are considered 

reliable. However, the use of this information does not constitute an endorsement of its accuracy by 

the Federal Deposit Insurance Corporation. 

Chairman Donna Tanoue 

Director, Division of Insurance Arthur J. Murton 

Executive Editor George E. French 

Writer/Editor Kim E. Lowry 

Editors Lynn A. Nejezchleb 

Maureen E. Sweeney 

Richard A. Brown 

Ronald L. Spieker 

Publications Manager Teresa J. Franks 
 

 

 

Letter from the Executive Editor
 

To the Reader: 

The goal of the Regional Outlook is to provide useful risk-related information to bankers, banking agency staff, and 

other interested readers. To do this more effectively, the second quarter 2001 edition will have a new look. We will 

publish a single national edition that will provide an overview of economic and banking risks and discussions of these 

risks as they relate to insured institutions in each FDIC Region. We will tell the national story and, at the same time, 

alert the reader to specific trends and developments at the regional level. 

After considering our experience with this new format, we may adopt it permanently for the second and fourth quarters of each year. The first and third quarter editions will continue to feature in-depth coverage of the economy and 

banking industry in each Region. Trying new formats will help us find the right balance between regional coverage 

of specific topics and analysis of economic and banking issues that cut across regional lines. 

After you have read the next edition of the Regional Outlook, we would like to hear from you. Does this new 

approach provide a more effective vehicle for reporting on banking and economic trends? What other suggestions do 

you have for improving our presentation of risk-related information? Call us with your comments at (877) 275-3342 

or (800) 925-4618 (TDD) or e-mail them to lnejezchleb@fdic.gov. 

Sincerely, 

George E. French
 

Executive Editor 


Kansas City Regional Outlook 3 First Quarter 2001
 
 

 

 

Regional Perspectives
 

Regional Perspectives
 

•	 A surprisingly large number of community banks in the Kansas City Region show an unexpected relationship between loan-to-asset ratio and net interest margin. Portfolio composition, asset and loan growth, leverage, and funding appear largely responsible for the divergence between loan-to-asset ratio and net interest 

margin. 

•	 A review of community banks prior to the 1980s agricultural crisis shows that loan-to-asset ratio and net 

interest margin frequently were indicators of increased potential for failure. 

Region’s Economic and Banking Conditions 

Community Banks’ Responses to Margin 

Pressures Have Affected Risk Profiles 

This article is the second in a two-part series that examines the ongoing decline of community banks’1 net 

interest margins (NIMs) in the Kansas City Region. In 

Regional Outlook, fourth quarter 2000, we showed how 

declining NIMs are widespread among community 

banks, with 73 percent reporting a decline in NIMs 

between 1992 and 1999.2 We discussed the strong competitive forces responsible for the NIM compression 

and how community banks offset the downward pressure on NIMs by dramatically increasing loan-to-asset 

(LTA) ratios, from 49.9 percent in 1992 to 62.4 percent 

in 1999, the highest level ever reported. 

Although declining NIMs and rising LTA ratios define 

the aggregate, there is considerable variance among 

individual community banks. We previously discussed 

how, in general, rising LTA ratios contribute to higher 

NIMs, and falling LTA ratios contribute to falling 

NIMs. This article goes beyond this generalization to 

show that a small subset of community banks reports 

contrary results. Specifically, some banks report low 

loan volumes but strong NIMs, and some banks report 

high loan volumes but relatively low NIMs. This article 

explains how differences in loan growth rates, portfolio 

composition, capital levels, and funding sources have 

1 A community bank refers to an FDIC-insured commercial bank in 

the Kansas City Region with total assets of less than $250 million. As 

of December 31, 1999, 2,059 community banks represented 93 percent of all commercial banks in the Region. Our discussion of community banks is limited to 1,754 community banks that, as of 

year-end 1999, met the following criteria: have been in operation 

throughout the 1990s and were in operation for at least three years as 

of January 1, 1990; are not considered credit card banks (banks with 

at least 50 percent of total loans in credit card receivables); and have 

not used pushdown accounting because of mergers during the 1990s. 

2 Unless otherwise noted, all year dates refer to year-end. 

influenced the LTA-NIM relationship and assesses 

how these differences contribute to significantly different risk profiles for particular groups of banks. Finally, 

we review the condition of community banks prior to 

the 1980s agricultural crisis and note the usefulness of 

the LTA-NIM relationship as an indicator of potential 

failure. 

LTA Ratios Do Not Always Correlate with NIMs 

In last quarter’s article, we discussed the strong positive 

link between a bank’s LTA ratio and NIM performance. 

The LTA ratio and NIM generally move together, either 

positively or negatively. Banks that hold low loan volumes report lower margins and banks that hold high 

loan volumes report higher margins. We showed that, in 

the aggregate, community banks in the Kansas City 

Region that reported incrementally higher LTA ratios 

also posted incrementally increased NIMs and less NIM 

compression over time.3 However, when we look 

beyond aggregates, we find that some banks do not follow this trend. In fact, they reported exactly the opposite results in 1999: relatively low LTA ratios and high 

NIMs, or high LTA ratios and low NIMs. 

Chart 1, a scatterplot, shows the generally positive relationship between LTA ratios and NIMs; however, this 

chart also shows that some banks differ from the norm. 

The chart plots the Region’s 1,754 community banks by 

reported 1999 LTA ratios and NIMs and segments the 

middle quintile (20 percent) of LTAs and NIMs. In general, the scatterplot shows that higher LTA ratios correspond with higher NIMs, and vice versa. These 

quadrants contain the most dots and represent the 

3 See Table 1 in “Declining Net Interest Margins and Rising Loan-toAsset Ratios—a Disturbing Paradox,” Regional Outlook, fourth quarter 2000. 

Kansas City Regional Outlook 4	 First Quarter 2001
 
Regional Perspectives 

CHART 1 

A Scatterplot Shows the Positive Relationship 

between LTA Ratios and Net Interest Margins 

Each Dot Represents One Community Bank 

6.0 

quintile (20 percent) by rank, accurately represents the 

reported results of the aggregate, making it a proxy for 

all 1,754 community banks. Each quadrant represents 

banks that are in the top or bottom 40 percent as ranked 

by the LTA ratio and NIM. For example, the lower left 

quadrant, the Low LTA–Low NIM group, represents 

Percent Net Interest

Margin (NIM) 

5.5 banks that rank in the bottom 40 percent of reported LTA 

5.0 ratios and in the bottom 40 percent of reported NIMs. 

4.5 

4.0 

3.5 

3.0 

2.5 

2.0 

Middle LTA 

Quintile 

Middle NIM 

Quintile 

The factors that appear most important in explaining 

the differences among the banks in the four quadrants 

are loan growth, portfolio composition, and degree of 

leverage. 

30% 40% 50% 60% 70% 80% 90% 

Loan-to-Asset (LTA) Ratio 

Source: Bank Call Reports, Community Banks, 1999 

expected relationships. However, the chart also shows 

unexpected relationships: some banks report low LTA 

ratios but high NIMs, or high LTA ratios but low NIMs. 

These quadrants contain fewer dots. 

To better understand the unexpected relationships found 

in the upper left and lower right quadrants, we compared the four quadrants in Chart 1 by showing the data 

in a matrix format (see Table 1). Table 1 replaces individual dots with data on the number of banks, median 

NIMs, and median LTA ratios. 

The shaded middle cross, which represents banks 

reporting either an LTA ratio or an NIM in the middle 

TABLE 1 

Loan Growth, Portfolio Composition, and 

Leverage among Groups of Banks Differ 

Significantly 

As expected, banks with low LTAs and low NIMs, represented in the lower left quadrant, report relatively low 

loan volume that results in lower overall asset yields. 

These banks report a lower loan growth rate (see Table 

2, next page) and a relatively lower overall credit risk 

profile than the other groups (see Table 3, next page). 

They also report relatively higher capital and loan loss 

reserve levels (see Table 4, page 7). 

Also as expected, banks with high LTAs and high NIMs, 

represented in the upper right quadrant, report relatively high loan volume, resulting in high asset yields. 

Community Banks Are Segmented by Loan Levels and Net Interest Margins 

LOW LTA–HIGH NIM HIGH LTA–HIGH NIM

>4.38% BANKS: 169 BANKS: 389 

NET INTEREST 

MARGIN 

PERCENT 

RANGE, 1999 

NIM: 

LTA: 

4.70% 

50.64% 

NIM: 

LTA: 

4.97% 

73.06% 

4.10%– 

4.38% 

MIDDLE CROSS

BANKS: 622 

NIM: 4.23% 

LTA: 62.47% 

<4.10% 

LOW LTA–LOW NIM

BANKS: 406 

NIM: 3.56% 

LTA: 47.82% 

HIGH LTA–LOW NIM

BANKS: 168 

NIM: 3.78% 

LTA: 71.06% 

<58.2% 58.2%–64.3% >64.3% 

LOAN-TO-ASSET RATIO PERCENT RANGE, 1999 

Source: Bank Call Reports, Community Banks 

Kansas City Regional Outlook 5 First Quarter 2001 
 

 

 

Regional Perspectives
 

TABLE 2 

Growth Rates for High LTA Banks Greatly Exceeded Those of Low LTA Banks, 

Affecting Funding Decisions and Costs 

CORE NONCORE 

ASSET LOAN DEPOSIT FUNDING COST OF 

GROWTH GROWTH GROWTH GROWTH FUNDS 

’92–’99 ’92–’99 ’92–’99 ’92–’99 1999 

LOW LTA–LOW NIM 4.4 7.3 3.0 15.8 4.36 

LOW LTA–HIGH NIM 3.7 5.5 2.9 10.6 3.95 

MIDDLE CROSS 5.7 8.7 4.3 17.5 4.31 

HIGH LTA–LOW NIM 8.0 12.3 6.2 22.8 4.62 

HIGH LTA–HIGH NIM 8.4 12.0 7.0 22.0 4.31 

AGGREGATE TOTAL 6.2 9.6 4.8 18.5 4.34 

Source: Bank Call Reports, Community Banks 

These banks exhibit a relatively high loan growth rate, a 

relatively higher overall credit risk profile, and relatively lower capital and loan loss reserve levels. 

Banks with low LTAs but high NIMs, represented in the 

upper left quadrant, report relatively low funding 

expenses and high loan yields, which offset low loan 

levels. This group of banks maintains a relatively low 

loan volume that produces yields consistent with those 

of banks with high LTAs and high NIMs, despite a 

much lower concentration in traditionally higher risk 

loan types. However, this group of banks also reports 

the lowest asset and loan growth rates of any group. 

TABLE 3 

Coupled with maintenance of high capital and reserve 

levels (the highest of any group), this group experiences 

a very low cost of funds (see Table 5). 

Banks that report high LTA ratios but low NIMs are represented in the lower right quadrant of the matrix. 

Lower NIMs, for the most part, are the result of relatively high interest expenses and relatively low loan 

yields. Although this group reports a relatively high 

LTA ratio, its loan composition tends to be conservative, 

similar to banks with low LTAs and low NIMs. For 

example, residential real estate loans are 27.8 percent of 

this group’s portfolio, the highest percentage of any 

Loan Composition Is a Proxy for Management’s 

Risk Tolerance and Affects Yields and NIMs 

LOAN COMPOSITION, % OF TOTAL LOANS, 1999 

YIELD ALLL/ 

1 TO 4 CONST. & FARM ON TOTAL 

FAMILY NONRES. DEVEL. PRODUCTION COMM. & LOANS LOANS 

RES. RE RE RE AND RE INDUS. (%) (%) 

LOW LTA–LOW NIM 22.6 13.2 2.8 35.6 14.9 8.63 1.59 

LOW LTA–HIGH NIM 19.1 16.6 2.3 30.8 18.1 9.31 1.88 

MIDDLE CROSS 23.0 16.5 3.2 30.5 16.2 8.83 1.49 

HIGH LTA–LOW NIM 27.8 15.6 2.7 29.3 14.5 8.52 1.23 

HIGH LTA–HIGH NIM 20.4 21.8 4.5 23.7 18.6 9.33 1.38 

AGGREGATE TOTAL 22.8 17.3 3.4 29.3 16.5 8.91 1.45 

Notes: RE = loans secured by real estate.
 

Nonresidential real estate loans include commercial real estate, multifamily residential, and construction loans.
 

Construction and development loans are included in both the Residential Real Estate columns and a separate 


column.
 

ALLL = Allowance for Loan and Lease Losses
 

Source: Bank Call Reports, Community Banks
 

Kansas City Regional Outlook 6 First Quarter 2001
 
 

 

 

Regional Perspectives
 

TABLE 4 

Capital and Reserve 

Levels Vary Significantly 

EQUITY ALLL/TOTAL 

RATIO LOANS 

(%) (%) 

LOW LTA–LOW NIM 10.5 1.59 

LOW LTA–HIGH NIM 11.9 1.88 

MIDDLE CROSS 9.5 1.49 

HIGH LTA–LOW NIM 8.2 1.23 

HIGH LTA–HIGH NIM 8.8 1.38 

AGGREGATE TOTAL 9.5 1.45 

Notes: All ratios are as of 12/31/1999. 

ALLL = Allowance for Loan and Lease Losses 

Source: Bank Call Reports, Community Banks 

group. As a result, loan yields for this group are the lowest in the group. On the liability side, however, this 

group of insured institutions reports a higher level of 

interest expense than any other group because of relatively high leverage and cost of funds, resulting in the 

second-lowest reported NIM of any group. 

Do External Factors Determine Banks’ 

Placement in the LTA-NIM Matrix? 

Having created this matrix, we wondered whether a 

bank’s placement in the matrix is the result of local economic conditions. If location and the local economy 

played a significant role in placement, we would expect 

TABLE 5 

to see little movement within the matrix over time. 

Small banks rarely move operations to another county, 

and economic conditions remained somewhat constant 

in the Region during the 1990s (e.g., agricultural counties remained agricultural). However, although the relative numbers of banks in the quadrants remained 

relatively static from 1992 to 1999, placement of individual banks in the matrix has changed over time. Only 

37 percent of banks in the lower left quadrant and 27 

percent of banks in the upper right quadrant remained 

there from 1992 to 1999. Only 62 banks in total 

remained in the middle cross group and the upper left 

and lower right quadrants during this period. 

If location were the critical factor, we would see homogeneity among banks’ LTA ratios within smaller geographic areas. However, this is not the case when we 

look at the Region’s 306 counties that are home to three 

or more community banks. In fact, a large percentage of 

these counties (214 counties, or 70 percent) contain at 

least one bank with a relatively low LTA ratio and at 

least one bank with a relatively high LTA ratio. Only 29 

of these counties were home to banks characterized by 

either all low or all high LTA ratios.4 

Although location does not necessarily dictate placement of a bank within the matrix, it does influence management decisions. For instance, although a bank 

operating in a geographic area that is characterized by 

low loan demand (such as an area that is economically 

depressed) can choose to have a relatively high LTA 

ratio, that decision could heighten the level of credit 

risk. A bank that makes the strategic decision to 

Funding Decisions, Especially the Use of Noncore 

Funds, Have Affected Costs and Net Interest Margins 

CORE CHANGE NONCORE CHANGE EQUITY COST 

DEP/ASSETS FROM FUNDING/ FROM RATIO OF FUNDS 

(%) 1992 ASSETS (%) 1992 (%) (%) 

LOW LTA–LOW NIM 74.4 –7.4 14.3 7.3 10.5 4.36 

LOW LTA–HIGH NIM 78.4 –4.2 8.9 3.2 11.9 3.95 

MIDDLE CROSS 75.8 –7.3 14.0 7.3 9.5 4.31 

HIGH LTA–LOW NIM 73.7 –9.5 17.6 10.4 8.2 4.62 

HIGH LTA–HIGH NIM 75.9 –7.7 15.1 8.5 8.8 4.31 

AGGREGATE TOTAL 75.4 –7.5 14.5 7.8 9.5 4.34 

Note: All ratios are as of 12/31/1999. 

Source: Bank Call Reports, Community Banks 

4 We ranked the 1,754 community banks by LTA ratio and grouped them into five quintiles. We defined a low LTA ratio as falling in the lower 40 

percent (quintiles 1 and 2) and a high LTA ratio as falling in the upper 40 percent (quintiles 4 and 5). Similar findings resulted when we substituted the 1992 to 1999 change in LTA ratio for the 1999 LTA ratio. 

Kansas City Regional Outlook 7 First Quarter 2001
 
 

Regional Perspectives
 

TABLE 6 

The Location and Type of Bank Do Not Necessarily 

Dictate the Placement of the Bank within the Matrix 

FARM BANKS VERSUS 

NONFARM BANKS (%) COUNTY POPULATION TRENDS 

LOW LTA–LOW NIM 

LOW LTA–HIGH NIM 

MIDDLE CROSS 

HIGH LTA–LOW NIM 

HIGH LTA–HIGH NIM 

FARM NONFARM GROWING DECLINING 

ACCELERATED 

DECLINING 

76.6 

63.3 

66.9 

65.5 

53.2 

23.4 

36.7 

33.1 

34.5 

46.8 

38.4 

50.9 

49.2 

41.7 

57.3 

48.0 

39.1 

39.7 

52.4 

33.2 

13.6 

10.0 

11.1 

5.9 

9.5 

AGGREGATE TOTAL 65.6 34.4 47.9 41.3 10.8 

Notes: Refer to Regional Outlook, first quarter 2000, article for discussion of population trends: 

Growing Counties have had increased population since 1970. 

Declining Counties have lost population since 1970, but declines were not higher in the 1990s. 

Accelerated Declining Counties have lost population since 1970, and declines accelerated in the 1990s. 

Source: Bank Call Reports, Community Banks 

increase its LTA ratio to a relatively high level could 

experience particularly high funding costs. On the other 

hand, a more risk-averse institution may exhibit a relatively low risk profile; however, this may come at the 

expense of lost earnings and market share. 

Table 6 shows how local conditions contribute to where 

a bank falls in the matrix. Compared with institutions in 

the two higher NIM quadrants, insured institutions in 

the two lower NIM quadrants are more likely to be farm 

banks located in rural areas; institutions in the two higher NIM quadrants tend to be located in counties with 

growing populations. However, these are tendencies and 

not absolutes. Not all banks in rural areas report low 

TABLE 7 

LTA ratios and low NIMs, and not all banks in metropolitan areas report high LTA ratios and high NIMs. 

Matrix Group Characteristics 

Influence Risk Profiles 

How do loan growth, portfolio mix, noncore funding, 

and capital and reserves influence the risk profile of 

each group in the matrix? Table 7 shows the relative level 

of risk associated with each of these characteristics. 

Not surprisingly, banks in the upper right quadrant of 

the matrix (those with high LTAs and high NIMs) 

Groups’ Risk Profiles Are Ranked Using Five Characteristics 

GROUP’S RISK BY CHARACTERISTIC RELATIVE TO OTHER GROUPS 

GROWTH NONCORE CAPITAL AND 

MATRIX GROUP LTA RATIO LOAN MIX TREND FUNDING RESERVES 

LOW LTA–LOW NIM LOWER LOWER AVERAGE AVERAGE LOWER 

LOW LTA–HIGH NIM LOWER AVERAGE LOWER LOWER LOWER 

MIDDLE CROSS AVERAGE AVERAGE AVERAGE AVERAGE AVERAGE 

HIGH LTA–LOW NIM HIGHER LOWER HIGHER HIGHER HIGHER 

HIGH LTA–HIGH NIM HIGHER HIGHER HIGHER HIGHER HIGHER 

RISK EXPOSURE CATEGORIES ARE RATED AS LOWER, AVERAGE, OR HIGHER. 

Note: An “average” ranking was assigned to the Middle Cross, a proxy for the total, and each quadrant was ranked 

relative to the Middle Cross. If these figures were close, an “average” rating was assigned to the quadrant. Otherwise, a “higher” or “lower” rating was assigned. Our assessment of the loan mix characteristic focused on each 

group’s concentration in traditionally higher risk loan types as well as any strong concentration in residential 

real estate loans. 

Source: Bank Call Reports, Community Banks 

Kansas City Regional Outlook 8 First Quarter 2001
 
 

 

Regional Perspectives
 

TABLE 8 

Profitability Increases 

as an Institution Adopts 

a Higher Risk Profile 

BANKING 1999 

RISK ROE 

LOW LTA–LOW NIM LOWEST 8.64 

LOW LTA–HIGH NIM LOWER 9.68 

MIDDLE CROSS AVERAGE 11.91 

HIGH LTA–LOW NIM HIGHER 12.43 

HIGH LTA–HIGH NIM HIGHEST 14.33 

Note: “Banking Risk” signifies our subjective placement 

of each group along a spectrum of characteristics 

commonly thought to affect banking risk. 

ROE = Return on equity 

Source: Bank Call Reports, Community Banks 

appear to exhibit a higher risk profile relative to the 

other groups. Banks in the lower left quadrant (those 

with low LTAs and low NIMs) appear to exhibit a lower 

risk profile. However, when we look at institutions 

falling in the other two quadrants, the results are not so 

straightforward. Banks with low LTAs but relatively 

high NIMs appear to exhibit a lower risk exposure, 

while banks with relatively high LTAs but low NIMs 

generally exhibit higher exposures (except for loan 

mix, which represents a very low exposure). 

Table 7 suggests that the two groups of banks characterized by high LTA ratios may be somewhat more vulnerable during an economic downturn than banks with low 

loan levels. Moreover, given similar LTA ratios, banks 

with higher NIMs are more vulnerable than banks with 

lower NIMs. Taking this one step further, Table 8 shows 

that insured institutions that exhibit a higher level of risk 

are being compensated in terms of higher levels of profitability. As one might expect, return on equity appears 

to increase as institutions adopt a higher risk profile. 

In the 1980s, Higher LTA Ratios Tended 

to Boost Net Interest Margins but Were 

Associated with Increased Risk of Failure 

Regional Outlook, third quarter 1999, discussed the 

1980s agricultural crisis and cited the results of studies 

that showed that LTA ratio was a significant indicator of 

bank failure.5 Accordingly, groups of institutions with 

higher LTA ratios failed at a significantly higher rate 

than banks with lower LTA ratios. Does our LTA-NIM 

matrix add any value to that discussion? 

TABLE 9 

Quadrant Placement in 1982 Was an Indicator of Potential for Failure 

LOW LTA–HIGH NIM HIGH LTA–HIGH NIM

>5.10% BANKS: 463 BANKS: 647 

FAILURES: 8 FAILURES: 86 

FAIL RATE: 1.73% FAIL RATE: 13.29% 

MIDDLE CROSS

4.57%– BANKS: 1,230 

5.10% FAILURES: 55 

FAIL RATE: 4.47% 

<4.57% LOW LTA–LOW NIM HIGH LTA–LOW NIM

BANKS: 643 BANKS: 449 

FAILURES: 8 FAILURES: 40 

FAIL RATE: 1.24% FAIL RATE: 8.91% 

<48.5% 48.5%–54.5% >54.5% 

LOAN-TO-ASSET RATIO PERCENT RANGE, 1982 

Source: Bank Call Reports, commercial banks with less than $250 million in assets, excluding credit card banks and 

de novo banks as of year-end 1982 

NET INTEREST 

MARGIN 

PERCENT 

RANGE, 1982 

5 See “Agricultural Sector Under Stress: The 1980s and Today,” Regional Outlook, third quarter 1999, for more detail on these studies. 

Kansas City Regional Outlook 9 First Quarter 2001
 
 

Regional Perspectives
 

To answer this question, we looked at community 

banks6 in existence in 1982, before the last banking crisis in the Region. As the 1982 matrix (see Table 9) 

shows, the distribution of community banks by LTA and 

NIM in 1982 was similar to the distribution in 1999; 

most banks’ LTA ratios and NIMs trended in the same 

direction. We filtered bank failures from 1983 through 

1989 through the 1982 matrix to determine if any 

matrix group failed at a relatively higher rate than the 

others. 

The 1982 matrix shows that failure rates differed significantly among the groups. Table 9 reaffirms that, at least 

during the 1980s agricultural crisis, LTA ratio was 

strongly correlated with failure. Banks represented in 

the two low LTA quadrants failed at a combined 1.5 percent rate. In contrast, banks represented in the two high 

LTA quadrants failed at a combined 11.5 percent rate, 

more than two and one-half times that of the banks in 

the middle cross. 

6 The 1982 matrix includes community banks that, as of year-end 

1982, met the following criteria: in operation for at least three years as 

of January 1, 1982; are not considered credit card banks (banks with 

at least 50 percent of total loans in credit card receivables); and have 

not used pushdown accounting because of mergers during the 1990s. 

The 1982 matrix also shows that NIMs, as a proxy for 

other performance variables, may indicate heightened 

management tolerance for risk and the potential for failure. Banks reporting low LTA ratios failed at relatively 

low rates; however, banks with low LTA ratios but high 

NIMs failed at somewhat higher rates than banks with 

low LTA ratios and low NIMs. However, as the LTA 

ratio rises, the NIM also appears to be an indicator of 

the potential for a bank to fail. For example, High 

LTA–High NIM banks failed at the highest rate, almost 

one and one-half times that of High LTA–Low NIM 

banks. 

It should be noted that the 1982 matrix is an academic 

study of historical data and is not intended to predict 

community bank failure rates. Certainly, banking conditions have changed since 1982, and should the Region 

experience another banking crisis, the effects may not 

be the same. However, the 1982 matrix supports our 

contention that banks that report high LTA ratios and 

high NIMs have a higher tolerance for risk than banks 

that report low LTA ratios and low NIMs. Also, the 

1982 matrix shows that groups of banks can realize 

comparable earnings while exhibiting significantly different risk profiles. 

Richard D. Cofer, Jr., Senior Financial Analyst 

John M. Anderlik, CFA, Regional Manager 

Kansas City Regional Outlook 10 First Quarter 2001
 
In Focus This Quarter
 

Credit Problems for U.S. Businesses 


Continue to Increase
 

•	 Commercial credit quality trends have been slipping since 1998, despite generally favorable U.S. 

business conditions. 

•	 The recent economic slowdown, coupled with 

tighter credit conditions, points to continued deterioration in business credit quality over the coming months. 

•	 Trends in bond defaults, syndicated lending, corporate profitability, and expected default levels 

reveal a number of industry sectors that pose a 

heightened degree of risk to lenders. 

Introduction 

Continuing increases in problem commercial loans have 

focused the spotlight on business lending conditions. 

On September 30, 2000, commercial banks reported the 

highest relative level of noncurrent1 commercial 

loans—at 1.52 percent of total commercial loans— 

since third quarter 1994. In fact, commercial banks have 

been reporting steadily higher rates of noncurrent 

domestic commercial loans since the second quarter of 

1999. The first quarter 2000 edition of Regional Outlook identified several factors contributing to the 

decline in business credit quality despite the strong economic indicators then in place. These factors, which are 

still relevant today, include the rise in financial leverage 

for domestic corporations, greater investment risk 

appetite and looser underwriting standards from 1996 to 

1999, and increasing financial stress within various 

industry sectors. More recently, an apparent slowdown 

in economic growth increases prospects for further 

deterioration in business credit conditions. 

Large Banks Experience a Reversal 

in Commercial Credit Quality Trends 

Through much of the 1990s, a sustained period of economic growth produced improving commercial loan 

credit quality indicators for insured commercial banks. 

This trend reversed itself in 1998, when banks began 

1 Nonaccrual loans plus loans 90 days or more delinquent. 

experiencing a steady rise in nonperforming and delinquent commercial loans. While the initial catalyst for 

this reversal was related mainly to events abroad,2 a 

slowing domestic economy has since taken center stage 

as the underlying driving force behind worsening commercial credit quality trends. 

As of September 30, 2000, noncurrent commercial and 

industrial (C&I) loans held by commercial banks stood 

at $15.6 billion, a 46 percent increase over the previous 

year. Roughly 97 percent of this increase is attributable 

to the rise in nonaccrual and delinquent credit to U.S. 

domiciled borrowers. Net C&I loan loss rates are also 

rising. Through the first three quarters of 2000, annualized C&I loan loss rates reached 0.64 percent, up from 

0.58 percent in 1999. The last time banks saw C&I loss 

rates this high was in 1993 (0.74 percent). 

Larger banks, which have the greatest exposures to 

large- and middle-market corporate credits, have been 

hardest hit by the turnaround in business credit conditions. As shown in Chart 1, banks with over $1 billion 

in assets have experienced most of the recent deterioration in C&I noncurrent loan rates. Since the fourth 

quarter of 1997, the noncurrent C&I loan rate of large 

CHART 1 

Noncurrent Loan Rates
 

Are Rising at Larger Banks
 

Percentage of C&I loans on nonaccrual
 

and 90 days or more past-due 5.2 

4.8 

4.4 

4.0 

3.6 

3.2 

2.8 

2.4 

2.0 

1.6 

1.2 

0.8 

0.4 

4Q 1Q 2Q 3Q 4Q 1Q 2Q 3Q 4Q 1Q 

Small Banks 

(< $1 billion in assets) 

Large Banks 

(> $1 billion in assets) 

’88 ’90 ’91 ’92 ’93 ’95 ’96 ’97 ’98 ’00 

Source: Bank Call Reports 

2 Significant events that contributed to higher levels of problem foreign loans in 1998 include the collapse of Asian currency exchange 

rates and default by the Russian government on its sovereign debts. 

Some domestic industries that were highly dependent on exports 

(steel, for example) were also adversely affected by these events. 

Kansas City Regional Outlook 12	 First Quarter 2001
 
In Focus This Quarter
 

banks has increased from 0.74 percent to 1.50 percent. 

Over the same period, noncurrent C&I loan rates at 

small banks were unchanged at 1.64 percent. While the 

increase in noncurrent loan rates at larger banks is significant, these higher rates remain well below those that 

preceded the 1990 to 1991 recession, when noncurrent 

loan rates at large banks were in the 3.40 percent to 3.60 

percent range. 

Much of the recent deterioration in banks’ business 

credit quality is attributable to the seasoning of credits 

underwritten during a period of relaxed lending standards. Each of the three bank supervisory agencies has 

recognized and warned about the potential impact of 

loosened loan underwriting standards in the event of a 

slowdown in the economy. For example, just over a year 

ago, the Office of the Comptroller of the Currency 

(OCC) issued a warning to banks about the “...cumulative effect of the past four years of easing standards...” 

for commercial loans.3 The shift toward more liberal 

credit standards from 1996 to 1999 was fueled by various factors, including a robust economy, intense competition to originate syndicated credits, and an increased 

appetite for risk. During this period, a number of banks 

moved aggressively into non-investment-grade lending to 

combat narrowing interest margins and declining investment-grade yields. According to a recent Standard & 

Poor’s commentary, several banks have acknowledged 

the role of 1997 and 1998 vintage credits in producing 

higher levels of problem loans.4 

Business Loan Performance Is Not Likely 

to Improve Any Time Soon 

Prospects for any near-term reversal in deteriorating 

commercial loan trends are dimming as signs of slower 

economic growth and tighter credit conditions emerge. 

Economic indicators suggest an aging economic expansion that is losing momentum. In third quarter 2000, the 

U.S. economy recorded its 39th consecutive quarter of 

growth. However, real gross domestic product growth 

for the third quarter was only 2.2 percent, well below 

the previous quarter’s growth of 5.6 percent and below 

the 4.9 percent average quarterly growth rate during the 

past eight quarters. Corporate earnings also appear to be 

slowing. Annualized corporate profit growth in the third 

3 Office of the Comptroller of the Currency Press Release. October 5,
 

1999.
 

4 July 20, 2000. “U.S. Bank Loan Portfolios Reflect Rise in Corporate
 

Bond Defaults.” Standard & Poor’s Commentary.
 

quarter slowed to 5.1 percent, down from a 15.6 percent 

annualized growth rate in second quarter 2000 and a 

10.4 percent average growth rate over the past eight 

quarters.5 Corporate earnings are widely anticipated to 

slow even further based on the number of companies 

that have warned of profits falling below expectations 

in the fourth quarter.6 

Prospects for slower economic growth prompted the 

Federal Reserve to lower its target for the federal funds 

rate (the rate charged on overnight lending) by 1/2 percentage point to 6 percent on January 3, 2000. This cut 

follows a 175-basis-point increase in the targeted federal funds rate since the end of June 1999. Although higher interest rates have undoubtedly raised borrowing 

costs for U.S. corporations, business borrowing rates— 

even before the Federal Reserve cut interest rates in January 2001—are well below those prevalent during much 

of the 1980s (see Chart 2, next page). Moreover, 

changes in rates have been far less volatile in the latter 

part of the 1990s than they were during the 1980s and 

early 1990s. 

Tolerance for risk on the part of investors and lenders is 

waning. In a November 2000 survey of underwriting 

practices, the Federal Reserve Board noted that 44 percent of U.S. banks tightened credit terms for large- and 

middle-market borrowers in the past three months, the 

highest incidence of tightening since fourth quarter 

1990. This tightening of credit terms is primarily in 

response to economic concerns, industry-specific problems, and a lower tolerance for risk. Banks appear to be 

especially apprehensive about taking on additional 

credit risk related to merger and acquisition financing 

deals, new borrowing prospects, and specific industry 

segments such as health care, movie theaters, and communications.7 

Tighter credit terms by banks will have the greatest 

impact on high-risk companies, which have fewer 

financing options in an environment of slumping bond 

and stock prices. Moreover, there appears to be a significant increase in the volume of maturing debt that 

could be forced into default if capital market or bank 

5 These figures are taken from the U.S. Department of Commerce’s 

statistics on corporate profits with inventory valuation adjustments. 

6 According to First Call/Thomson Financial, 505 companies released 

warnings that fourth quarter 2000 earnings would fall below expectations, up 96 percent from the 257 companies with negative profit 

warnings for fourth quarter 1999. 

7 See the Federal Reserve Board’s November 2000 Senior Loan Officer Opinion Survey on Bank Lending Practices. 

Kansas City Regional Outlook 13 First Quarter 2001
 
 

In Focus This Quarter
 

CHART 2 

Business Borrowing Rates Have Risen but Are Less Volatile than in Past Cycles 

Percent 

1Q82 3Q83 1Q85 3Q86 1Q88 3Q89 1Q91 3Q92 1Q94 3Q95 1Q97 3Q98 1Q00 

Note: LIBOR = London Interbank Offer Rate 

Sources: Federal Reserve Board, Moody's, FT London Interbank 

3-Month LIBOR 

Moody’s Baa Average Yield 

Prime Rate 

0 

2 

4 

6 

8 

10 

12 

14 

16 

18 

funding is not available. According to Moody’s, some 

$108 billion of rated speculative-grade corporate debt 

held by banks matures over the next three years, a 40 

percent increase over year-earlier levels. 

Higher-risk companies also have a lower capacity to 

absorb the cost of higher interest rates. Yet many companies with debt maturing in the near term will likely be 

forced to pay higher risk premiums than in the past. For 

example, Moody’s notes that in November 2000, speculative-grade bond yield spreads over seven-year Treasuries reached their widest level since February 1991, at 

771 basis points.8 Chart 3 illustrates further how credit 

spreads between just-investment-grade bond issues and 

near-investment-grade bond issues have widened considerably compared with spreads between lower-investment-grade bond issues since the beginning of 2000. 

Some of the most significant increases in credit spreads 

have been observed in the high-yield telecommunications sector, where credit spreads over seven-year Treasuries widened by 688 basis points in 2000.9 

The effects of tighter credit conditions and a reduced 

appetite for risk are beginning to emerge in loan origination volumes. According to Loan Pricing Corporation, originations of highly leveraged loans10 through 

8 December 2000. Moody’s Leveraged Finance Commentary. 

9 Merrill Lynch Global Bond composites. Issues facing the telecommunications industry are explored further in the article entitled 

“Three Industries Navigating in a Competitively Charged Environment” in this issue of the Regional Outlook. 10 Loan Pricing Corporation defines highly leveraged loan transactions as those carrying interest rates of 250 basis points or more over 

the London Interbank Offer Rate (LIBOR). 

the first three quarters of 2000 fell to $117 billion from 

$140 billion for the same period in 1999. 

Corporate bond trends provide further evidence of 

financial stress in the domestic market and suggest 

more near-term deterioration in problem business 

loans. Corporate bond default rates have climbed significantly since 1997 (see Chart 4). Through November 2000, trailing 12-month default rates on 

speculative-grade corporate bonds reached 6.8 percent, up from 3.5 percent at the end of 1998. Higher 

default rates have been accompanied by an accelerated 

pace of negative ratings revisions, which, according to 

Moody’s, reached a rate of 3.2 speculative-grade 

downgrades for every speculative-grade upgrade 

through the first 11 months of 2000.11 More signifiCHART 3 

Credit Risk Premiums for High-Yield 

Bond Issues Have Increased Sharply 

Basis Point Yield Spread Between 

220 

200 

180 

160 

140 

120 

100 

80 

60 

40 

20 

0 

A-rated and 

BBB-rated bonds 

BBB-rated and 

BB-rated bonds 

Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov 

’99 ’99 ’99 ’99 ’99 ’99 ’00 ’00 ’00 ’00 ’00 ’00 

Source: Merrill Lynch 

11 See Moody’s Credit Perspectives, December 4, 2000. 

Kansas City Regional Outlook 14 First Quarter 2001
 
In Focus This Quarter
 

cant, Moody’s projects that speculative-grade corporate bond defaults will continue to move higher to 9.1 

percent over the coming year. Given a fairly strong 

correlation between speculative bond default rates and 

banks’ noncurrent loan rates, these projections suggest 

a continuing rise in the relative level of problem commercial loans.12 

Loan Default Risk Is Rising 

in a Number of Industry Sectors 

Evidence from Corporate Bond Defaults 

Corporate bond defaults provide clues as to which 

industries may experience a higher rate of defaults. 

Chart 4 shows the historical trend in speculative-grade 

bond defaults since 1988. The initial upward spike in 

default rates in 1998 was largely the result of events 

abroad, when 74, or 59 percent, of 126 defaulted issues 

were attributed to foreign-domiciled issues.13 In 1999, 

the distribution of defaults shifted decidedly toward 

domestic issues, with U.S. firms accounting for 99, or 

67 percent, of 147 defaults. Of the U.S.-domiciled 

defaults in 1999, 64 percent were related to industrial 

CHART 4 

sectors, with concentrations in price-sensitive commodity and trade-dependent sectors such as oil and gas, 

shipping, and steel. Other domestic sectors that experienced a noteworthy rise in defaulted issues in 1999 were 

telecommunications and health care. Year-to-date 2000 

defaults continue to be dominated by U.S. firms.14 

According to Moody’s, year-to-date defaulted bond 

issues have been concentrated in health care; telecommunications; and textiles, leather, and apparel.15 

Evidence from Syndicated Loan Trends 

Past growth in syndicated loans may be another indicator of default risk. Many lenders appeared to increase 

their appetite for risk from 1996 through 1999, judging 

by the growth in leveraged loan and highly leveraged 

loan volumes during this period (see Chart 5, next 

page).16 Because rapid loan growth can be an indicator 

of aggressive risk taking, it is important to review some 

significant borrowing industries that experienced rapid 

credit growth from 1996 to 2000. It is also worthwhile 

to review industries where higher-risk (high-yield) borrowing accounted for a substantial proportion of syndicated loan transactions. 

Pace of Speculative Bond Defaults Expected to Rise Significantly 

Bond Rating Downgrades to Upgrades (right axis) 

Trailing 12-Month Speculative-Grade Bond Default Rate 

Bank C&I Noncurrent Rate Projected 

Default and Noncurrent Loan Rate (%) Bond Downgrades to Upgrades 

0 

1 

2 

3 

4 

5 

6 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

’88 ’89 ’90 ’91 ’92 ’93 ’94 ’95 ’96 ’97 ’98 ’99 3Q’00 3Q’01 

YTD* 

* Bond default rates through November 30, 2000 

Sources: Moody’s, Call Reports 

12 There is a strong correlation between historical speculative-grade corporate bond defaults and noncurrent loan rates. The correlation coefficient 

between these two variables for the period 1984 to the present is 0.67. 

13 Indonesia alone accounted for 32 defaulted issues in 1998, and sovereign issuers accounted for 36 percent of defaulted debt volume. Historical 

Default Rates of Corporate Bond Issuers, 1998. Moody’s Investor Service. 14 Historical Default Rates of Corporate Bond Issuers, 1999. Moody’s Investor Service. 15 Moody’s Credit Perspectives, December 11, 2000. Issues facing the health care and textile industries are explored further in the article entitled 

“Three Industries Navigating in a Competitively Charged Environment” in this issue of the Regional Outlook. 16 Loan Pricing Corporation defines leveraged transactions as those that carry interest rate spreads of 150 basis points or more over LIBOR and 

highly leveraged transactions as those that carry spreads of 250 basis points or more over LIBOR. Because these definitions are spread-driven, the 

rise in the proportion of higher-yield issuance is attributable in part to a general increase in credit spreads. This was the case particularly during 

the 1998 period, when credit spreads rose significantly. 

Kansas City Regional Outlook 15 First Quarter 2001
 
In Focus This Quarter
 

CHART 5 

Source: Loan Pricing Corporation 

High-Yield Loan Syndications More 

Prevalent from 1996 through 1999 

Leverage Lending to Total 

Syndicated Lending (%) 

Syndicated Loan 

Originations ($ billions) 

High-Yield Leverage Lending 

to Total Syndicated 

Lending (left scale) 

0 

5 

10 

15 

20 

25 

30 

35 

0 

200 

400 

600 

800 

1,000 

1,200 

’90 ’91 ’93 ’95 ’97 ’99 ’92 ’94 ’96 ’98 ’00

Table 1 lists selected industries17 that accounted for a 

significant proportion of syndicated loan volumes from 

1996 to 2000, according to Thomson Financial Securities Data. Industries that experienced some of the most 

rapid growth rates in syndicated loan volumes during 

that time include utilities, telecommunications, and real 

estate investment trusts (REITs). Industries that recorded a particularly significant proportion of high-yield 

TABLE 1 

transactions during that period include real estate and 

construction, REITs, health care, and entertainment/ 

lodging/leisure. 

Evidence from Corporate Profit Trends 

Industry sector earnings trends may also be an indicator 

of industry default risk, because higher defaults are 

more likely in sectors with weak earnings. As noted 

above, profit growth rates of domestic firms appear to 

be decelerating following two years of strong earnings 

growth overall. Rapid growth in previous quarters 

appears to have been driven in large part by high-tech 

and related sectors, such as electronic equipment and 

communications. These sectors have to a large extent 

overshadowed noteworthy declines in profit growth in 

other sectors, such as metals, chemical production, 

medical services, property casualty insurance, apparel 

and textiles, manufactured housing, agriculture, transportation, and wholesale trade (see Table 2). 

Evidence from Credit Risk Models 

Credit default models have proliferated in recent years 

because of advances in technology, data availability, and 

financial theory. One such model is KMV LLC’s CredHistorical U.S. Syndicated Loan Trends 

Help Identify Possible Sources of Industry Credit Risks 

1996 TO 2000 

SHARE OF AVG. ANNUAL 2000 

1996 TO 2000 ISSUANCE ISSUANCE HY AS A % 

ISSUANCE GROWTH GROWTH 1996 TO 2000 

INDUSTRY (%) (%) (%) ISSUANCE 

WHOLESALE AND RETAIL TRADE 7.8 –2 –12 34 

ELECTRIC, GAS AND SANITARY 

UTILITIES 6.5 34 15 19 

TELECOMMUNICATIONS 5.4 28 54 29 

NONDEPOSITORY INVESTMENT 

COMPANIES 5.2 19 24 33 

OIL AND GAS 4.1 23 83 18 

SECURITIES BROKERS/DEALERS 3.7 15 13 4 

ENTERTAINMENT/LEISURE/LODGING 3.3 5 31 42 

REAL ESTATE INVESTMENT TRUST 2.7 27 25 49 

HEALTH CARE 2.6 –4 –41 44 

REAL ESTATE AND CONSTRUCTION 2.5 25 46 50 

Note: HY (high-yield) issuance includes deals priced at 125 basis points or more over LIBOR. 

Source: Thomson Financial Securities Data 

17 This list is taken from a group of 50 sectors defined using Standard Industrial Codes (SICs). Only industries that accounted for more than 2 percent of 1996 to 2000 origination volumes were considered for inclusion. 

Kansas City Regional Outlook 16 First Quarter 2001
 
In Focus This Quarter
 

it Monitor®. This model, which uses publicly available 

information to estimate the likelihood of default for 

individual firms, is widely used by lenders to monitor 

and evaluate obligor risk and credit risk trends. While it 

is not the only model available, the KMV model can be 

applied consistently and easily to the analysis of industry sector credit risk across a broad range of industry 

groupings. 

In brief, the KMV model uses options-pricing theory to 

derive market-based expected default probabilities or 

an expected default frequency (EDFTM).18 The model 

relies mainly on three pieces of information: (1) a 

firm’s asset market value; (2) the volatility of a firm’s 

asset market values; and (3) the firm’s capital structure 

or financial leverage. Although EDFTM scores are company-specific, median industry expected default probTABLE 2 

abilities can be constructed and compared across 

industries and across time to discern relative rankings 

of industry risk and industry risk trends. These median 

EDFTM scores also can be mapped to other default measurement scales, such as external rating agency ratings, 

based on individual EDFTM scores of firms with rated 

debt. 

Since the second quarter of 1998, median EDFTM scores 

have risen significantly across a wide range of U.S. nonfinancial industry sectors (see Chart 6, next page). The 

service and trade sector includes the greatest proportion 

of firms with high default risk. The median probability 

of default for the manufacturing sector firms is lower, 

but it is rising and roughly equaled that of Standard & 

Poor’s BB-grade (sub-investment-grade) obligors as of 

December 2000. 

Various Industries Have Exhibited Negative Profitability Trends 

ANNUAL GROWTH IN NET INCOME 

1998 1996 TO 1999 1994 TO 1999 

INDUSTRY TO 1999 (%) AVERAGE (%) AVERAGE (%) 

STEEL –1,237.9 –428.6 –187.4 

COPPER –80.7 –65.5 13.2 

INTERNET –43.2 –42.7 –35.5 

TIRES AND RUBBER –81.9 –28.6 –12.7 

ALUMINUM –13.2 –13.9 156.4 

CHEMICALS –38.1 –3.9 18.4 

MEDICAL SERVICES AND 

INFORMATION SYSTEMS –48.2 –2.5 44.8 

PROPERTY CASUALTY INSURANCE –3.9 –2.0 3.8 

RECREATIONAL GOODS AND SERVICES .5 2.5 17.1 

APPAREL AND TEXTILES 2.5 10.4 3.3 

MANUFACTURED HOUSING AND 

RECREATIONAL VEHICLES –9.8 11.7 27.3 

AGRICULTURE –1.3 12.3 4.6 

WHOLESALE TRADE –8.8 13.7 13.7 

CEMENT AND AGGREGATES 1.2 21.6 60.5 

OILFIELD SERVICES AND PRODUCTION –373.7 39.9 19.3 

AIRLINES AND FREIGHT –13.2 1,085.5 666.5 

ALL CORPORATE PROFITS (WITH 

INVENTORY VALUATION AND CAPITAL 

CONSUMPTION ADJ.) 5.0 4.4 13.6 

Sources: Economy.com Precis Reports; U.S. Department of Commerce, Survey of Business Conditions 

18 Typically expressed as the probability of default over the coming year. 

Kansas City Regional Outlook 17 First Quarter 2001
 
 

In Focus This Quarter
 

Although no one factor can explain the rise in expected CHART 6 

default measures for U.S. nonfinancial firms, rising 

financial leverage is clearly a major determinant. U.S. 

corporate debt burdens continue to rise in conjunction 

with the longest-running economic expansion in U.S. 

history. The debt-to-net-worth ratio (book value) of 

nonfarm, nonfinancial businesses rose to 83 percent in 

the second quarter of 2000, up from 72 percent at yearend 1996. Although these figures remain below the relative debt levels experienced in the late 1980s and early 

1990s,19 U.S. businesses are nevertheless becoming 

increasingly vulnerable to rising credit costs and disruptions in credit availability. Higher asset value volatility20 has also played a role in rising EDFTM scores, 

which, as in any options-based credit risk model, leads 

to a greater likelihood of default. 

Default Risk Is Rising Broadly 

among U.S. Nonfinancial Firms 

Source: Credit MonitorTM ©2000, KMV LLC, all rights reserved 

3Q 

’00 

1Q 

’96 

3Q 

’96 

3Q 

’97 

1Q 

’99 

3Q 

’98 

3Q 

’99 

1Q 

’00 

1Q 

’97 

1Q 

’98 

0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

7.0 

Service & Trade 

Manufacturing 

One-Year EDFTM in Percent

Comparative Median EDFTM 

of S&P Bonds Rated BB 

(as of December 2000) 

Chart 7 shows eight of the highest-risk industries in 

terms of changes in median EDFTM scores over the past 

two years. These industries were drawn from a list of 50 

financial and nonfinancial sectors segregated by Standard Industrial Codes (SICs). For each of these 50 sectors, median EDFTM scores were determined for 

December 2000 and compared with median EDFTM 

scores for the same sector in December 1998. Consistent with general industry observations, entertainment 

and leisure, health care, and telecommunications are 

among the sectors where default risk has risen most significantly over the past two years. 

CHART 7 

While Chart 7 illustrates sectors undergoing financial 

stress, it does not provide information on the relative 

importance of these sectors to lenders. Thomson 

Financial Securities Data provides information on the 

volumes of syndicated loan originations by banks and 

nonbanks. Matching industry-expected default trends 

with syndicated loan origination trends by industry is 

one way to determine the relative importance of higherrisk industry credit exposures.21 

Chart 8 shows median EDFTM and syndicated loan origination pairs for selected industries during the past three 

Industries That Experienced the Greatest Increase 

in Expected Default Risk over the Past Two Years 

Median Expected Default

Frequency (EDFTM) in Percent 14

12 

10 

8 

6 

4 

2 

0 

December 1998

 December 2000 

Comparative Median EDFTM 

of S&P Bonds Rated BB 

(as of December 2000) 

Entertainment Health Wholesale Apparel Business Agriculture Telecom Retail 

& Leisure Care Trade & Textile Services 

Source: Credit MonitorTM ©2000, KMV LLC, all rights reserved 

19 The debt-to-net worth ratio for U.S. nonfarm, nonfinancial businesses averaged slightly under 87 percent from 1988 to 1992. 

20 Implicit in changes in stock prices. 

21 Syndicated loan originations are an imperfect measure of actual loan exposures in the financial industry. For example, it is not possible to determine the level of outstanding exposures simply by summing up origination levels from year to year, because payments on long-term debt are not 

considered. Moreover, a substantial volume of debt represents revolving lines of credit where credit exposures roll over on a periodic basis. Nevertheless, trends in originations do contain some information on the relative level of industry exposures, because they show which industries are 

borrowing more or less during any given year. 

Kansas City Regional Outlook 18 First Quarter 2001
 
In Focus This Quarter
 

years. Of the industries shown, the telecommunications 

industry appears to present the greatest degree of risk, 

given a nearly $50 billion increase in loan volumes from 

1998 to 2000, coupled with a 170 percent increase in 

median expected default levels over the same period. In 

contrast, loans to securities brokers and dealers can be 

considered relatively less risky—despite a $17 billion 

rise in originations from 1998 to 2000—because of a 

fairly modest rise in median expected defaults. It is also 

interesting to contrast the health care and entertainment 

and leisure sectors. Firms in both sectors have experienced a dramatic rise in expected defaults. However, 

since 1998, Thomson Financial Securities Data shows a 

significant curtailment in lending to health care companies, while entertainment and leisure originations have 

held steady over the same period. Because banks appear 

to be reducing credit exposures to health care firms, 

banks should eventually see a decline in the level of 

defaulting debt related to this sector. 

Chart 8 illustrates how U.S. syndicated loan issuance 

and expected default measures can be linked to produce 

a better sense of risk-weighted industry exposure volumes held by lenders. On the basis of this type of analysis, producing a list of industry sectors that appear to 

pose the greatest degree of syndicated loan default risk 

is relatively straightforward. Perhaps not surprisingly, 

industries such as telecommunications, wholesale and 

retail trade, entertainment and leisure, health care, and 

apparel and textiles rank high in terms of risk-weighted 

industry credit exposures using this analysis.22 

Conclusion
 

Many U.S. banks are experiencing deterioration in business loan quality measures. The adverse effects of higher interest rates, a tightening of credit terms, slowing 

profit growth, and industry sector weaknesses are the 

primary contributing factors to this deterioration. Several indicators—including a projected increase in corporate bond default rates, rising expected default trends 

in certain industry sectors, and evidence of lax underwriting practices in previous periods—suggest that 

banks could experience substantial further deterioration 

in business loan quality in the near term. 

Although worsening business loan quality is a concern, these negative trends must be put into perspective. In relative terms, current indicators of business 

loan problems do not approach the experience of 

banks during the last economic downturn of the early 

1990s. Moreover, continued strong earnings and capital provide a significant buffer for banks to weather 

the effects of higher levels of nonperforming business 

loans and business loan losses. Nevertheless, the 

prospect of a slowdown in the economy raises concerns about the possible severity of commercial loan 

problems, a situation that will undoubtedly be watched 

closely by both banks and bank supervisors in the 

coming months. 

Steven Burton, Senior Banking Analyst 

CHART 8 Median EDFTM in Percent 

Expected Default Data Can Be Used to Risk-Weight Industry Credit Risk 

Sources: Credit MonitorTM ©2000, KMV LLC, all rights reserved; Securities Data Corporation 

Health Care 

Syndicated Loan Originations by Industry Sector ($ Billions) 

0 

2 

4 

6 

8 

10 

12 

14 Entertainment & Leisure 

Wholesale Distributors 

Telecommunications 

Securities Brokers & Dealers 

0 20 40 60 80 100 

2000 

1999 1998 

Legend: 

2000 Originations and Dec. ’00 EDFTM 

1999 Originations and Dec. ’99 EDFTM 

1998 Originations and Dec. ’98 EDFTM 

22 Fifty sectors, grouped by SIC codes, were considered. 

Kansas City Regional Outlook 19 First Quarter 2001
 
In Focus This Quarter
 

Three Industries Navigating 


in a Competitively Charged Environment
 

The rising tide of a booming economy in the United 

States has lifted the boats of a broad spectrum of industries over the past nine years. Some industries, however, 

have fallen on hard times despite continued economic 

expansion. These industries represent a broad crosssection of the economy. Problems in these industries were 

precipitated by diverse factors, reflecting the differences 

among sectors in industries ranging from old economy 

(such as textiles) to services (such as health care) to those 

on the horizon (such as telecommunications). 

These industries will navigate in turbulent waters over 

the next few years. All three face an uncertain economic outlook, changing public policies that can influence 

their operating environment, and fierce competition. 

The importance of these industries to the U.S. economy 

varies based on employment. The telecommunications 

industry accounts for about 1.4 million jobs, or 0.85 

percent of total U.S. employment.1 Health care, on the 

other hand, contributes over 11 million jobs, or 7 percent of total employment. Textile industry employment 

has been falling steadily for many years and is now 

under 550,000, accounting for less than 0.40 percent of 

total U.S. employment. 

As diverse as these industries are, a common denominator exists. Intense competition characterizes their 

operating environment, leaving little room for strategic 

missteps. Indeed, there have been reports that these 

industries have been significant contributors to the 

recent rise in problem bank loans. 

With a better grasp of the origins of stress in these 

industries comes a basis for understanding the lending 

risks associated with a changing policy and economic 

environment in the years to come. The following discussion describes trends and developments contributing 

to stress in these industries and looks at the near- and 

long-term outlook. Our discussion also looks at the 

implications for the insured institutions lending to the 

telecommunications, health care, and textiles industries. 

1 Source: Economy.com. Includes employment in telecommunications 

services, telecommunications equipment manufacturing, and cable 

television. 

Telecommunications 

The telecommunications sector consists of several 

industry subsectors, including telecommunications services, cable television, and telecommunications equipment, all of which are facing significant challenges. 

Telecommunications Services 

Rapid growth in the telecommunications services 

industry has been fueled by strong domestic consumer 

demand. However, the pace of consumption of telecommunications services has slowed in recent months. This 

sector has experienced booming growth in revenues 

from computer network access since 1998, while local 

and long distance revenues have grown at a much more 

moderate pace (see Chart 1). 

Rapid change and intense competition characterize the 

industry environment. Long distance businesses, in particular, have experienced fierce competition, resulting 

in severe pricing pressures. Competitors include both 

established and new wireline long distance providers, as 

well as wireless services. Local telephone companies, 

however, have fared well in recent years, as residences 

and small businesses have added phone lines to accommodate the growing demand for Internet access. However, as high-speed DSL and cable Internet access 

become more readily available, the demand for additional telephone lines may diminish, cutting into a 

lucrative source of revenue for local phone companies. 

Capital spending by telecommunications services companies has soared in recent years, although it was 

expected to level off in 2000 in response to higher interest rates and reduced earnings growth. Nevertheless, 

high levels of telecommunications equipment investment are expected to continue for the foreseeable future, 

as telecom service firms require additional equipment 

upgrades to accommodate increased network traffic and 

wireless applications (see Chart 2). 

Cable TV 

Cable TV is another important component of the 

telecommunications services industry. According to 

Economy.com, “among the current technologies available, cable is viewed as the leading option for delivering 

Kansas City Regional Outlook 20 First Quarter 2001
 
In Focus This Quarter
 

CHART 1 

* Forecast 

Source: Economy.com 

Growth in Telecom Services’ Network Access Revenues Soared in Recent Years 

Annual % Change in Residential

Service Revenues

Residential—Local Residential—Long Distance 

Residential—Network Access 

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50 

55 

60 

65 

’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00* 

video, telephony, entertainment, and computing services to households and businesses.”2 Cable TV sales 

revenue has grown more than 19 percent a year since 

1995. In spite of this stellar revenue growth, most cable 

companies are not earning a profit because of the high 

levels of capital investment required. 

Telecommunications Equipment 

The telecommunications equipment industry is growing 

rapidly, as telecom service providers rush to upgrade 

infrastructure to enhance their offerings of high-speed 

broadband services. Telecommunications service 

providers are not only upgrading fiber optic and cable 

line networks; they are rapidly upgrading antiquated 

circuit-switched networks to more efficient packetswitch networks. However, the growth in revenues and 

profits was expected to moderate in 2000 because of 

higher interest rates and slower growth in the domestic 

economy (see Chart 3, next page). 

The wireless phone industry also has experienced problems since late 2000. The major mobile phone companies have missed earnings projections, casting doubt on 

the growth potential of the industry. Much is riding on 

the development of third-generation (3G) wireless technology, which is expected to allow wireless access to the 

Internet, transmission of video and other images, and 

videoconferencing—all from a handheld mobile phone. 

Although huge amounts of money are being invested to 

develop 3G technology, it is unclear what applications 

will generate the demand to make the investments profitable. 

CHART 2 

90,000 

80,000 

70,000 

(In $ millions)

60,000 

50,000 

40,000 

30,000 

20,000 

10,000 

0 

Telecom Services’ Capital Spending Growth Soars 

’92 ’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00* 

* Forecast 

Source: Economy.com 

2 September 2000. Economy.com, Precis: Industry: Cable TV. 

Kansas City Regional Outlook 21 First Quarter 2001
 
In Focus This Quarter
 

CHART 3 

Telecom Equipment Sales Revenue 

Moderates in 2000 

* Forecast 

Source: Economy.com Annual % Change in Telecom Equipment Sales Revenue 

0 

5 

10 

15 

20 

25 

30 

’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00* 

Outlook 

The telecommunications industry has been badly battered in both equity and bond markets in the past several months. A spate of bad news has resulted in sharply 

lower stock prices and higher costs in debt markets. As 

a result, the availability of financing for some higherrisk firms is now questionable. Investors are concerned 

about the prospect of slowing wireless subscriber 

growth, continuing capital expenditures, intense competition, and the rapid rise in telecom debt3 (see Chart 4). 

The long-term outlook for the telecommunications services industry is positive. The emergence of highmargin technologies and continued growth in wireless 

subscriber rates should enhance profitability in the 

future. Consumers and businesses are also expected to 

CHART 4 

spend an increasing share of their incomes on telecom 

services. Nevertheless, strong competition, huge investments in equipment upgrades, and rapidly changing 

technology will force firms to be nimble and innovative. 

The long-term outlook for the telecommunications 

equipment industry is positive, as the demand for data, 

Internet, and wireless services continues to grow 

strongly. Nevertheless, individual firms in the industry 

face a highly competitive environment and rapidly 

changing technology. 

Cable TV’s long-term outlook is also positive because 

of growing advertising sales and technological developments that should allow cable firms to offer a broader 

array of services. Still, the competitive environment is 

fierce. In addition to competing with a host of “traditional” telecommunications firms, cable firms must 

contend with satellite TV providers, which are partnering with major firms to offer sophisticated communications and entertainment services. 

Implications for Banks 

The most important characteristics of the telecom 

industry with respect to lending risks are its highly competitive environment and its pace of technological 

change. These characteristics suggest that the mediumto long-term outlook for a particular credit may not be 

well represented by current conditions. The success of 

telecom firms will be based on management’s ability to 

adapt to change and compete with a fluid set of competitors. 

Source: Standard & Poor's Compustat 

Growth in Telecom Debt since 1995 Dwarfs Other Sectors’ Debt Growth 

Telecom Industries 

Percent Change in Debt

(1995–1999) 

Radio/Tel. Broadcast/

Commun. Equip.

Basic Materials

ConsumerCyclical

Consumer

Staples

Health Care

Energy

Capital Goods

Technology

Communication

Services

Utilities 

Transportation

Radiotelephone

(Wireless)

Telephone,

Except Wireless

Cable and Other

Pay TV Services 

0 

50 

100 

150 

200 

250 

300 

350 

400 

450 

500 

3 Solomon, Deborah, and Nicole Harris. October 18, 2000. “Talks on Merger By AT&T Wireless Face Investor Static.” Wall Street Journal. 

Kansas City Regional Outlook 22 First Quarter 2001
 
 

In Focus This Quarter
 

CHART 5 

HMO Enrollment Rose Sharply through 1998 

as Employers Sought to Contain Health Care Costs 

HMO Enrollment as a

Percentage of Population 

’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00* 

0 

5 

10 

15 

20 

25 

30 

35 

* Forecast 

Sources: Economy.com, Interstudy 

With both equity and bond markets turning against the 

telecommunications industry, cash-hungry telecom 

firms may have difficulty obtaining financing. This 

could pose a serious risk for banks with a significant 

exposure to telecom start-ups without a major partner or 

an investor sponsor. 

The high capital requirements and financial leverage of 

many telecommunications firms complicate these lending risks. Some of these firms are borrowing heavily to 

put into place an infrastructure to accommodate a 

demand for services that is yet to come on-stream, 

meaning that the payback on this investment may not 

occur for a number of years. 

Health Care 

Industry trends such as declining hospital occupancy 

rates and rising outpatient visits to hospitals, intense 

competition, and the unexpected results of new 

Medicare policy combined to put the health care industry in difficult financial straits during the past few 

years. However, subsequent industry consolidation and 

streamlining and revised Medicare rules have helped to 

stabilize prospects for many health care providers. 

Recent Trends and Developments 

The health care industry has been suffering since the 

implementation of the Balanced Budget Act of 1997 

(BBA), which cut Medicare payments much more than 

expected. However, two subsequent bills were passed to 

“give back” a portion of the Medicare payment cuts 

implemented in the BBA. The Balanced Budget Refinement Act of 1999 should restore some $16 billion of the 

cuts to health care facilities over five years.4 Also, the 

recently passed Benefits Improvement and Protection 

Act of 2000 (BIPA) will restore about $35 billion in 

benefits to the industry over the next five years. BIPA 

will provide the greatest benefit to hospitals, managed 

care plans, nursing homes, and home health agencies. 

The health care industry’s financial situation has stabilized somewhat in the past year because of widespread 

consolidation of hospitals and other health care 

providers. This has helped the industry reach greater 

levels of efficiency as well as improved bargaining 

power in negotiations with managed care organizations. 

Notwithstanding these favorable developments, other 

trends continue to pose serious challenges to many 

firms. Higher labor costs, continued HMO penetration, 

breakthrough pharmaceutical therapies resulting in 

reduced demand for services, and increased outpatient 

volumes have buffeted many health care facilities (see 

Chart 5 and Chart 6, next page). 

Higher-Risk Sectors 

A better understanding of risks and trends in health care 

can be gained by discussing its specific sectors. We 

have segregated these sectors based on the results of an 

option-pricing model of firm default risk. These models 

estimate the probability that the market value of a firm’s 

assets will fall below a level that would trigger default. 

Firms that have low stock prices, volatile stock prices, 

or high debt levels will tend to be flagged as having 

high default risk by such models. 

4 June 15, 2000. Healthcare: Facilities. Standard & Poor’s Industry 

Surveys. 

Kansas City Regional Outlook 23 First Quarter 2001
 
In Focus This Quarter
 

CHART 6	 Health care industry subsectors have been grouped into 

three categories: higher risk, moderate risk, and lower Outpatient Visits to Hospitals Grow Steadily risk, which refer to the degree of default risk relative to 

700 other subsectors in the industry. The estimated default 

Outpatient Visits to Hospitals

(millions) 

600 

500 

400 

300 

200 

100 

0 

’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00* 

* Forecast 

risk across these subsectors varies substantially. The 

highest-risk health care sectors include Offices of Medical Doctors; Skilled Nursing Care Facilities; Home 

Health Care Services; Specialized Outpatient Facilities, 

NEC; and Health Services (see Chart 7). 

Offices of Medical Doctors are largely physicians’ 

practice management firms. These firms acquire a practice of physicians based on a multiple of the practice’s 

discounted cash flow. The multiple can be several times 

the practice’s asset value at the time of purchase. However, these firms have had difficulty achieving profitability because of legal restrictions on referrals among 

affiliated groups of physicians, as well as the reluctance 

of physicians to submit their medical practice to the criteria of cost control.6 Total liabilities in this sector have 

grown rapidly over the past few years. 

Skilled Nursing Care Facilities’ earnings have been 

hurt badly by the BBA. However, they stand to benefit 

from the Medicare “giveback” provided by the recently 

enacted BIPA, which seeks to rectify the deeper-thanexpected cuts in funding resulting from the BBA. 

Skilled nursing care facilities’ performance has also 

been adversely affected by (1) declining occupancy 

Sources: Economy.com, Morgan Quinto 

One such model that is readily available is Credit MonitorTM, which was developed by KMV LLC.5 We stratify 

health care sectors based on their median one-year 

default probability as estimated by expected default frequenciesTM (EDFsTM) generated by Credit MonitorTM. 

Sectors identified in this article as higher-risk sectors, 

therefore, are those with a relatively high percentage of 

firms with low stock prices, volatile stock prices, or 

high debt levels. Readers are cautioned that the risk profile of a specific company may be very different from 

the sector risk profiles described here. 

CHART 7 

Estimated Default Risk Varies Widely among Health Care Subsectors, December 2000 

Median Expected Default

FrequencyTM (EDFTM)

in Percent 

Source: Credit MonitorTM ©2001, KMV LLC, all rights reserved 

Comparative Median EDFTM 

of S&P Bonds Rated BB 

(as of December 2000) 

0 

2 

4 

6 

8 

10 

12 

14 

16 

18 

20 

22 

8011: 

Doctors 

Offices 

8051: 

Skilled 

Nursing 

8082: 

Home 

Health Care 

8093: 

Spec. 

Outpatient, 

NEC 

8000: 

Health 

Services 

8071: 

Medical 

Labs 

8060: 

Hospitals 

6324: 

HMOs 

8090: 

Misc. Health 

Services 

8062: 

Med. & 

Surgical 

Hospitals 

5 Credit MonitorTM’s Expected Default FrequencyTM (EDFTM) estimates the probability of default within one year. KMV LLC’s proprietary calculation for EDFTM is based on (1) the current market value of the firm, (2) the structure of the firm’s current obligations, and (3) the vulnerabiltiy of 

the firm to large changes in market value measured in terms of asset volatility. EDFsTM are one of many potential measures of industry risk, and 

their use in this article should not be construed as an endorsement by the FDIC or Credit MonitorTM. 6 Gruehn, Charles. April 2000. Healthcare Industry Manual. Federal Reserve Bank of Atlanta. 

Kansas City Regional Outlook 24	 First Quarter 2001
 
 

In Focus This Quarter
 

rates caused at least partly by increased competition 

from lower-acuity facilities such as assisted living facilities; (2) rising labor and legal costs; and (3) surging 

debt service costs. Many of these firms are experiencing severe financial stress. The stressed facilities have 

registered negative net income for the past year or so, as 

well as burgeoning debt levels. The high debt levels are 

the result of acquisitions of ancillary support services 

that in many cases are not generating adequate cash 

flow because of the BBA.7 Most of these firms have 

seen their interest coverage ratios decline sharply over 

the past few years. 

Home Health Care Services focus primarily on respiratory therapy programs and intravenous and infusion 

services. The industry is undergoing financial stress as 

a result of the Health Care Financing Administration’s 

implementation of a prospective payment system that 

reduced reimbursements on respiratory therapy and 

infusion therapy. 

Specialty Outpatient Facilities, NEC are primarily 

engaged in outpatient care of a specialized nature, such 

as alcohol and drug treatment and birth control/family 

planning. They have permanent facilities and medical 

staff to provide diagnosis, treatment, or both for patients 

who are ambulatory and do not require inpatient care. 

Many of the firms in this sector have experienced a rising debt burden over the past few years, pushing default 

risk to higher levels. 

Health Services firms are engaged primarily in furnishing medical, surgical, and other health services. Firms 

listed in this broad category rather than more specific categories include companies providing dental services, 

laser eye correction, and physical and occupational therapy. Many publicly traded firms in this category have 

experienced sharply rising liabilities over the past three to 

four years. 

Moderate-Risk Sectors 

Moderate-risk health care sectors include medical laboratories, hospitals, and HMOs. 

Medical Laboratories provide professional analytic or 

diagnostic services to the medical profession or to the 

patient as prescribed by a physician. Companies with 

diverse financial performance and risk of default are 

included in this sector. A number of medical laborato7 Ibid. 

ries have registered deteriorating interest coverage 

ratios in the past year or two. 

Hospitals, as defined for these purposes, are specialty 

hospitals. They are primarily engaged in providing diagnostic services, treatment, and other hospital services 

for specialized categories of patients. Only eight publicly traded firms are listed in this category. They are 

involved in providing specialized hospital care such as 

rehabilitation, diabetes treatment, and drug and substance abuse treatment. 

Hospital and Medical Service Plans (HMOs) are primarily engaged in providing hospital, medical, and 

other health services to subscribers or members in 

accordance with prearranged agreements or service 

plans. Generally, these service plans provide benefits to 

subscribers or members in return for specified subscription charges. Also included in this industry are separate HMOs that provide medical insurance. After 

several years of intense competition among HMOs, 

which restricted premium-rate hikes when medical 

costs were rising sharply, HMOs began to pursue a more 

aggressive approach toward price increases. This new 

approach has improved the near- and intermediate-term 

outlook for this sector. Yet, the prospect of the passage 

of a Patients’ Bill of Rights suggests that rising costs 

could be an issue for HMOs in the future. As an industry, HMOs are highly concentrated, with the top 10 

HMOs accounting for nearly two-thirds of total HMO 

enrollment in the United States.8 

Lower-Risk Sectors 

The lowest-risk sectors in the health care industry 

include miscellaneous health and allied services, and 

general medical and surgical hospitals. Many of these 

firms have an estimated default risk that puts them in 

speculative credit risk categories in spite of the fact that 

they are considered lower risk compared with other 

health care sectors. 

Miscellaneous Health and Allied Services firms are 

involved in providing kidney or renal dialysis services 

and outpatient care of a specialized nature, such as alcohol and drug treatment and birth control/family planning. Some firms are engaged in providing health and 

allied services such as blood banks, blood donor stations, childbirth preparation classes, medical photography and art, and oxygen tent services. 

8 August 31, 2000. Healthcare: Managed Care. Standard & Poor’s 

Industry Surveys. 

Kansas City Regional Outlook 25 First Quarter 2001
 
 

In Focus This Quarter
 

General Medical and Surgical Hospitals provide general medical and surgical diagnostic and treatment services, other hospital services, and continuing nursing 

services. They have an organized medical staff, inpatient beds, and equipment and facilities to provide complete health care. According to a study conducted by 

HCIA-Sachs and Ernst & Young, “The BBA created the 

greatest financial instability that hospitals have experienced since the creation of Medicare in 1965. Yet the 

most severe reductions have just begun to impact hospitals, and will continue to do so through 2002. The 

recently enacted Balanced Budget Refinement Act provides little sustained relief to the industry, and significant financial problems are likely to remain.”9 The study 

also indicates that smaller hospitals (fewer than 100 

beds) are in the “greatest financial jeopardy.” The recent 

enactment of BIPA will help to stabilize the finances of 

hospitals over the next several years. However, other 

trends adversely affecting hospitals include as much as 

40 percent estimated excess capacity, rising labor costs, 

a severe shortage of nurses, continued HMO penetration, breakthrough pharmaceutical therapies, and 

increased outpatient volumes (see Charts 5, 6, and 8). 

Outlook 

The outlook for the health care industry has improved 

substantially in the past year. Industry consolidation and 

legislation to give back some of the Medicare cuts 

implemented in the Balanced Budget Act of 1997 have 

gone a long way to stabilize health care providers’ 

financial prospects, particularly those of hospitals and 

nursing homes. 

The passage of a Patients’ Bill of Rights in 2001 could 

also strengthen the hand of health care providers relative to HMOs. Such a bill could contain provisions that 

would weaken the position of managed care organizations to contain costs and negotiate with health service 

providers. 

Longer term, the demographic trends are positive, with 

the population aging and life expectancy increasing. 

The result should be a growing demand for health care 

services in the future. On the negative side, however, the 

current trends toward greater use of outpatient procedures and drug therapies will dampen the demand for 

inpatient hospital services. 

9 HCIA-Sachs, LLC, and Ernst & Young, LLP. May 1, 2000. The 

Financial State of Hospitals: Post-BBA and Post-BBRA. 

CHART 8 

Hospital Occupancy Rate 

Continues Steady Decline 

Hospital Occupancy Rate

(percent) 

* Forecast 

Sources: Economy.com, Morgan Quinto 

52 

54 

56 

58 

60 

62 

64 

66 

’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00* 

Implications for Banks 

The opportunities for financing health care firms will 

continue to grow into the future. Recent experience has 

shown that the financial performance of many health 

care providers is profoundly influenced by changes in 

Medicare policy. As Medicare expenditures grow to 

occupy a greater and greater place in the federal budget, 

Medicare policy will be scrutinized to an unprecedented degree, magnifying the importance of understanding 

the policy risk associated with health care lending. 

Powerful demographic trends should lead to the growth 

in demand for many health care services over the next 

10 to 20 years. For example, demand for nursing homes 

and assisted living facilities will increase sharply as 

baby boomers reach old age. However, regional supply 

and demand for these services can get out of balance as 

providers add facilities to meet demand. Monitoring 

local demand and supply trends is an important part of 

assessing the credit risks in these loans. 

Textiles 

The textile industry has been plagued by excess capacity, fierce competition from cheaper imports, and sagging textile prices. The result was a sharp drop in 

industry profits in 1999 and continued weakness in 

2000. 

Recent Trends and Developments 

The textile industry is a mature industry that by a number of measures has been declining. Intense competition 

from low-cost imports has taken its toll on domestic 

Kansas City Regional Outlook 26 First Quarter 2001
 
 

In Focus This Quarter
 

textile businesses. Since 1995, textile imports have 

increased nearly 50 percent while exports have grown 

just under 10 percent. A strong dollar should help textile imports continue to outpace exports. As a result of 

industry consolidation and the movement of many operations offshore, textile employment has continued to 

fall steadily. Textile employment has dropped from 

663,000 in 1995 to an estimated 544,000 in 2000.10 

Closely linked to all these trends, labor productivity in
 

the textile industry is low relative to the average for 

other manufacturing industries because of low output 

prices and a heavier reliance on labor in the production 

process. 

The Department of Commerce reports that the industry’s profit as a percentage of sales declined from 3.2 

percent in 1998 to just 1.3 percent in 1999 (see Chart 

9).11 Also, drought in the South has had an adverse effect 

on textile manufacturing firms, as these firms use a 

large amount of water in bleaching and dyeing fabric.12 

Because of improving global demand and plant closings 

in the United States, many analysts believe textile prices 

have now reached a low point. Indeed, data for 2000 

show a slight increase and some firming of prices in the 

first three quarters of the year (see Chart 10, next page). 

Nevertheless, the profit picture seems to have weakened 

further in 2000 because of an increase in nonoperating 

expenses. 

Publicly traded firms in the textile industry can be separated into six major categories: knitting mills, textile 

mill products, broadwoven fabric mills–cotton, broadwoven fabric mills–manmade fiber/silk, carpets/rugs, 

and miscellaneous fabricated textile products. The 

default risk characteristics of these sectors vary significantly as measured by the median EDFTM. 

Higher-Risk Sectors 

The higher-risk sectors include knitting mills, Broadwoven Fabric Mills–Cotton, and Textile Mill Products 

(see Chart 11, next page). 

10 Economy.com. November 2000. Apparel and Textiles, Precis Industry. 

11 Office of Textiles and Apparel, U.S. Dept. of Commerce. September 6, 2000. Current Situation in the U.S. Textile, Apparel, and Manmade Fiber Industries. 12 Kilman, Scott, and Amy Merrick. July 25, 2000. “Drought in the 

South Crimps Economy in Region.” Wall Street Journal. 

CHART 9 

Textile Industry Profits as a 

Percentage of Sales Fall in 1999 

4.0 

3.5 

3.0 

’90 ’91 ’92 ’93 ’94 ’95 ’96 ’97 ’98 ’99 

Percent 2.5 

2.0 

1.5 

1.0 

0.5 

0 

Source: U.S. Dept. of Commerce, Current Situation in the U.S. Textile,
 

Apparel, and Manmade Fiber Industries, September 6, 2000
 

Knitting Mills are engaged in knitting, dyeing, and finishing hosiery, stockings, outerwear, underwear, and 

other products from yarn or knitted fabrics. Two public 

firms in this industry accounted for 66 percent of the 

sector’s 1999 sales. Three out of eight firms in this sector reported net losses and six out of eight reported 

declining sales in 1999. The trends are similar in 2000 

based on incomplete available data. 

Broadwoven Fabric Mills–Cotton are engaged primarily in weaving fabrics more than 12 inches in width, 

wholly or chiefly by weight of cotton. One dominant 

firm accounted for nearly 38 percent of the sales of all 

publicly traded firms in this sector in 1999. The performance of firms in this sector was mixed in 1999. Six out 

of nine of these firms recorded negative net income in 

1999. Two companies reported a sizable increase in 

1999 net income. Incomplete 2000 results suggest that 

six firms are in the black, leaving just three with negative net income. 

Textile Mill Products is a broad category that includes 

establishments engaged in performing any of the following operations: (1) preparation of fiber and subsequent manufacturing of yarn, thread, braids, twine, and 

cordage; (2) manufacturing broadwoven fabrics, narrow 

woven fabrics, knit fabrics, and carpets and rugs from 

yarn; (3) dyeing and finishing fiber, yarn, fabrics, and 

knit apparel; (4) coating, waterproofing, or otherwise 

treating fabrics; (5) the integrated manufacture of knit 

apparel and other finished articles from yarn; and (6) 

the manufacture of felt goods, lace goods, nonwoven 

fabrics, and miscellaneous textiles. Two firms dominate 

this sector. Together, they accounted for over 60 percent 

of the sector’s sales in 1999 (considering publicly traded 

Kansas City Regional Outlook 27 First Quarter 2001
 
In Focus This Quarter
 

CHART 10 

Textile Prices Begin to Recover in 2000 

Producer Price Index

for Textile Mill Products

(NSA, Dec 1984=100) 

Source: Bureau of Labor Statistics 

113 

114 

115 

116 

117 

118 

119 

120 

’95 ’96 ’97 ’98 ’99 ’00 

firms only). Net income for both firms was off sharply 

in 1999. Still, some companies registered net income 

gains in 1999, building on several years of growth in net 

earnings. Although the 2000 data are incomplete, most 

firms in this sector have reported weak earnings. 

Indeed, several firms have reported more quarters of 

negative than positive net income. 

Moderate-Risk Sectors 

The moderate default risk sectors include Miscellaneous Fabricated Textile Products and Broadwoven Fabric Mills–Manmade Fiber/Silk. 

Miscellaneous Fabricated Textile Products includes 

businesses primarily involved in manufacturing curtains 

and draperies, house furnishings, textile bags, and canvas 

and related products; performing pleating, decorative and 

novelty stitching, and tucking for the trade; manufacturCHART 11 

ing automotive trimmings, apparel findings, and related 

products; Schiffli machine embroideries; and manufacturing fabricated textile products, not elsewhere classified. Net income for three out of the five publicly traded 

firms in this sector was negative in 1999. Two of those 

firms have experienced losses for at least two years’ running. Most of these firms reported negative net income 

through the first two or three quarters of 2000. The three 

largest firms’ total debt has grown considerably over the 

past few years. The increase is related primarily to 

financing acquisitions. 

Broadwoven Fabric Mills–Manmade Fiber/Silk are 

engaged in weaving fabrics more than 12 inches in 

width using primarily silk and manmade fibers, including glass. Net income for each of the six publicly traded firms in this category was down in 1999—in most 

cases down sharply. Earnings for most of these firms 

Estimated Default Risk in Textile Industry Subsectors, December 2000 

Median Expected Default

FrequencyTM (EDFTM)

in Percent 

Source: Credit MonitorTM ©2001, KMV LLC, all rights reserved 

2 

4 

6 

8 

10 

12 

14 

16 

18 

20 

22 

0 

Comparative Median EDFTM 

of S&P Bonds Rated BB 

(as of December 2000) 

2250: 

Knitting Mills 

2211: Brdwoven 

Fabric Mill, Cotton 

2200: 

Textile Mill 

Products 

2390: 

Misc Fabricated 

Textile Pds 

2221: 

Brdwovn Fabric 

Manmade, Silk 

2273: 

Carpets 

and Rugs 

Kansas City Regional Outlook 28 First Quarter 2001
 
 

 

 

In Focus This Quarter
 

appear to have continued to deteriorate in 2000. Interest 

coverage ratios for several firms were down in 1999 and 

2000 because of lower income, higher liabilities in 

some cases, and higher interest rates. 

Lower-Risk Sector 

Manufacturers of carpets and rugs represent the only 

lower-risk sector in the textile industry. 

Carpets/Rugs businesses are involved in manufacturing woven, tufted, and other carpets and rugs. This sector, as a group, experienced strong income growth in 

1999. Only one out of six publicly traded firms failed to 

make a profit in 1999, and several firms reported sizable profit increases. Available 2000 data suggest that 

each of these firms will have generated positive earnings. Two firms dominate the carpet and rug sector, 

accounting for about 65 percent of 1999 sales for the 

group. Carpet and rug manufacturing is capital and 

research intensive, which gives the U.S.-based firms a 

comparative advantage over overseas companies, which 

do not have the same level of access to capital markets 

and an educated workforce. 

Outlook 

Some positive factors could temper the adversity being 

experienced by the U.S. textile industry. Low fiber costs 

and an improved trade situation with Asia should 

strengthen the textile industry in the future. Labor productivity has been rising slowly, as firms continue to 

invest in labor-saving computer technology and equipment. The industry is pursuing various strategies to 

remain competitive, including consolidations and mergers and setting up operations in Mexico.13 Nevertheless, 

the current slowdown in the U.S. economy and the 

increased risk of an actual recession has posed challenges for the textile industry. 

Another concern for U.S. producers is trade liberalization and its effect on textile imports. The normalization 

of trade relations with China and the elimination of 

import quotas by 2005 according to the World Trade 

Organization (WTO) Agreement on Textiles and Clothing could lead to even greater imports. 

Implications for Banks 

Banks lending to textile firms face an array of risks 

emanating from the economic environment in which 

these firms operate. These risks include the ebb and 

flow of demand associated with the business cycle of 

the U.S. and world economies; the exchange rate of the 

U.S. dollar, which affects the competitiveness of domestically produced textile products; and the prices of both 

inputs and textile products. U.S. trade policy will also 

have a profound impact on the competitive environment 

in which domestic textile firms operate. Banks need to 

monitor these developments carefully. 

Concentration risk can be a significant issue for some 

banks. Textile mill employment is highly concentrated 

geographically. About 72 percent of all textile mill jobs 

are located in five southeastern states (North Carolina, 

Georgia, South Carolina, Alabama, and Virginia). 

Almost 29 percent of these jobs are in North Carolina 

alone. Another 18 percent are in Georgia. Even within 

these states, textile employment can be regionally concentrated, introducing concentration risk to banks with 

significant exposures to local textile firms. This risk is 

measured in terms of not only the volume of textile 

loans in the portfolio but also the spillover effects that 

plant layoffs can have in the community.14 

In an increasingly global market, credit risk in textiles 

will depend on decisions about production processes 

and intercompany linkages. For example, capitalintensive domestic producers may be in a better position 

to compete with offshore firms with greater access to 

cheap labor resources. Some textile firms may be able 

to enhance profitability and control risk by entering into 

partnerships with domestic and overseas organizations. 

Stephen Gabriel, Financial Economist 

13 Reichard, Robert. January 2000. “New Year Offers Problems and 14 See “Regional Economy,” Atlanta Regional Outlook, second quarOpportunities,” Textile World. ter 1998. 

Kansas City Regional Outlook 29 First Quarter 2001
 
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Federal Deposit Insurance Corporation 

Washington, DC 20429-9990 

OFFICIAL BUSINESS 

PENALTY FOR PRIVATE USE, $300 

BULK RATE
 

MAIL
 

Postage &
 

Fees Paid
 

FDIC
 

Permit No. G-36