Treasury Presentation to TBAC
Office of Debt Management

Fiscal Year 2016 Q3 Report
Table of Contents

2

I. Executive Summary p. 4

II. Fiscal

A. Quarterly Tax Receipts p. 6

B. Monthly Receipt Levels p. 7

C. Eleven Largest Outlays p. 8

D. Treasury Net Nonmarketable Borrowing p. 9

E. Cumulative Budget Deficits p. 10

F. Deficit and Borrowing Estimates p. 11

G. Budget Surplus/Deficit p. 12

III. Financing

A. Sources of Financing p. 15

B. OMB’s Projections of Net Borrowing from the Public p. 17

C. Interest Rate Assumptions p. 18

D. Net Marketable Borrowing on “Auto Pilot” Versus Deficit Forecasts p. 19

IV. Portfolio Metrics

A. Weighted Average Maturity of Marketable Debt Outstanding with Projections p. 24

B. Projected Gross Borrowing p. 25

C. Maturity Profile p. 26

V. Demand

A. Summary Statistics p. 31

B. Bid-to-Cover Ratios p. 32

C. Investor Class Awards at Auction p. 37

D. Primary Dealer Awards at Auction p. 41

E. Direct Bidder Awards at Auction p. 42

F. Foreign Awards at Auction p. 43
Section I:

Executive Summary

3
Receipts and Outlays

• Corporate taxes have been weaker than during the equivalent period last year, potentially attributable to the extension of bonus

depreciation and smaller corporate profits.

• Fiscal year-to-date, Treasury net outlays were $106 billion higher than last year, mainly attributable to larger interest expenses ($28 

billion) due to higher inflation compensation on TIPS and higher interest expense on Government Account Series (GAS) debt.

• Medicare outlays were higher by $27 billion, mostly due to a $11 billion increase in payments made to prescription drug plans.

Sources of Financing in Fiscal Year 2016 

• Based on the Quarterly Borrowing Estimate, Treasury’s Office of Fiscal Projections currently projects a net marketable borrowing need 

of $774 billion for FY 2016. This estimate includes a $151 billion year-over-year increase in the cash balance. In FY 2017, OMB projects 

that borrowing from the public will decline to $572 billion.

Projected Net Marketable Borrowing

• Between FY 2017 and 2018, Treasury’s borrowing from the public could rise notably if the Federal Reserve allows the Treasury securities 

held in the SOMA portfolio to mature.

• There are $565 billion of Treasury securities in the SOMA portfolio that will mature between now and the end of FY 2018.

Bid-to-Cover Ratios (BTC)

• BTC ratios for TIPS and shorter-dated coupons have fallen slightly in recent months, while bills have been little changed.

• Longer-dated coupon BTCs are broadly higher.

Investor Class Allotments

• Since the beginning of April, auction awards are lower for Other Dealers and Brokers, particularly in Bills. This is largely due to the 

addition of a new primary dealer. Accordingly, primary dealer awards increased in Bills. 

• Direct bidder awards were modestly lower across most tenors.

Highlights of Treasury’s August 2016 Quarterly Refunding Presentations

to the Treasury Borrowing Advisory Committee (TBAC)

4
Section II:

Fiscal

5
6 Source: United States Department of the Treasury 

(50%)

(40%)

(30%)

(20%)

(10%)

0 %

10%

20%

30%

40%

50%

60%

Jun-06 Oct-06 Feb-07 Jun-07 Oct-07 Feb-08 Jun-08 Oct-08 Feb-09 Jun-09 Oct-09 Feb-10 Jun-10 Oct-10 Feb-11 Jun-11 Oct-11 Feb-12 Jun-12 Oct-12 Feb-13 Jun-13 Oct-13 Feb-14 Jun-14 Oct-14 Feb-15 Jun-15 Oct-15 Feb-16 Jun-16 Year-over-Year % Change

Quarterly Tax Receipts

Corporate Taxes Non-Withheld Taxes (incl SECA) Withheld Taxes (incl FICA)
7

Individual Income Taxes include withheld and non-withheld. Social Insurance Taxes include FICA, SECA, RRTA, UTF deposits, FUTA and 

RUIA. Other includes excise taxes, estate and gift taxes, customs duties and miscellaneous receipts. 

Source: United States Department of the Treasury 0

2 0

4 0

6 0

8 0

100

120

140

Jun-06 Oct-06 Feb-07 Jun-07 Oct-07 Feb-08 Jun-08 Oct-08 Feb-09 Jun-09 Oct-09 Feb-10 Jun-10 Oct-10 Feb-11 Jun-11 Oct-11 Feb-12 Jun-12 Oct-12 Feb-13 Jun-13 Oct-13 Feb-14 Jun-14 Oct-14 Feb-15 Jun-15 Oct-15 Feb-16 Jun-16 $ bn

Monthly Receipt Levels

(12-Month Moving Average)

Individual Income Taxes Corporation Income Taxes Social Insurance Taxes Other
8 Source: United States Department of the Treasury 0

100

200

300

400

500

600

700

800

900 HHS SSA Defense Treasury

Agriculture Labor V A Transportation OPM Education Other Defense Civil $ bn

Eleven Largest Outlays

Oct - Jun FY 2015 Oct - Jun FY 2016
9 Source: United States Department of the Treasury 

(40)

(30)

(20)

(10)

0

1 0

2 0

3 0 Q3-06 Q4-06 Q1-07 Q2-07 Q3-07 Q4-07 Q1-08 Q2-08 Q3-08 Q4-08 Q1-09 Q2-09 Q3-09 Q4-09 Q1-10 Q2-10 Q3-10 Q4-10 Q1-11 Q2-11 Q3-11 Q4-11 Q1-12 Q2-12 Q3-12 Q4-12 Q1-13 Q2-13 Q3-13 Q4-13 Q1-14 Q2-14 Q3-14 Q4-14 Q1-15 Q2-15 Q3-15 Q4-15 Q1-16 Q2-16 Q3-16 $ bn

Fiscal Quarter

Treasury Net Nonmarketable Borrowing

Foreign Series State and Local Govt. Series (SLGS) Savings Bonds
10 Source: United States Department of the Treasury 

0

100

200

300

400

500

600

700 October November December January

February March April

May

June

July

August

September $ bn

Cumulative Budget Deficits by Fiscal Year

FY2014 FY2015 FY2016
11

FY 2016-2018 Deficits and Net Marketable Borrowing Estimates In $ billions

Primary 

Dealers1 CBO2 CBO3 OMB MSR4 OMB5

FY 2016 Deficit Estimate 567 529 534 600 616

FY 2017 Deficit Estimate 592 433 550 437 504

FY 2018 Deficit Estimate 696 383 549 481 454

FY 2016 Deficit Range 504 - 650

FY 2017 Deficit Range 522 - 700

FY 2018 Deficit Range 550 - 800

FY 2016 Net Marketable Borrowing Estimate 635 829 834 774* 774*

FY 2017 Net Marketable Borrowing Estimate 652 508 621 572 635

FY 2018 Net Marketable Borrowing Estimate 751 452 606 435 561

FY 2016 Net Marketable Borrowing Range 483 - 740

FY 2017 Net Marketable Borrowing Range 550 - 760

FY 2018 Net Marketable Borrowing Range 650 - 900

Estimates as of: Jul-16 Mar-16 Mar-16 Jul-16 Feb-16

1Based on primary dealer feedback on July 25, 2016. Estimates above are averages. 

2Table 1 and 2 of CBO's "An Analysis of the President's 2017 Budget"

3

Table 1 and 2 of CBO's "The Budget and Economic Outlook: 2016 to 2026"

4

Table S-11 of OMB's “The FY2017 Mid-Session Review” 

5Table S-13 of OMB's “Budget of the United States Government, Fiscal Year 2017” 

*OFP's FY 2016 Net Marketable Borrowing Estimate
(12%)

(10%)

(8%)

(6%)

(4%)

(2%)

0 %

(1,600)

(1,400)

(1,200)

(1,000)

(800)

(600)

(400)

(200)0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 % of GDP $ bn

Fiscal Year

Budget Surplus/Deficit

Surplus/Deficit (LHS) Surplus/Deficit (RHS)

Projections are from Table S-11 of “The FY2017 Mid-Session Review.” 12

OMB’s Projection
Section III:

Financing

13
14

Assumptions for Financing Section (pages 15 to 22)

• Portfolio and SOMA holdings as of 6/30/2016.

• SOMA reinvestments until 2H CY2017, followed by SOMA redemptions until and including February 

2022. These assumptions are based on Chair Yellen’s December 2015 press conference and the median 

expectations from the June FRB-NY survey of primary dealers. 

• Assumes announced issuance sizes and patterns constant for Nominal Coupons, TIPS, and FRNs as of 

6/30/2016, while using an average of ~$1.5 trillion of Bills outstanding. 

• The principal on the TIPS securities was accreted to each projection date based on market ZCIS levels 

as of 6/30/2016. 

• No attempt was made to match future financing needs. 
15

Sources of Financing in Fiscal Year 2016 Q3

*An end-of-June 2016 cash balance of $364 billion versus a beginning-of-April 2016 cash balance of $314 billion. By keeping the cash balance 

constant, Treasury arrives at the net implied funding number. 

Gross issuance values include SOMA add-ons

Net Bill Issuance (110) Security Gross Maturing Net Gross Maturing Net

Net Coupon Issuance 8 5 4-Week 540 575 (35) 1,695 1,610 8 5

Subtotal: Net Marketable Borrowing (25) 13-Week 388 445 (57) 1,200 1,114 8 6

26-Week 328 331 (3) 1,047 963 8 4

Ending Cash Balance 364 52-Week 6 0 7 5 (15) 170 250 (80)

Beginning Cash Balance 314 CMBs 0 0 0 9 5 120 (25)

Subtotal: Change in Cash Balance 5 0 Bill Subtotal 1,316 1,426 (110) 4,207 4,057 150

Net Implied Funding for FY 2016 Q2* (74)

Security Gross Maturing Net Gross Maturing Net

2-Year FRN 4 5 4 1 4 127 8 2 4 5

2-Year 9 5 9 3 2 267 285 (18)

3-Year 7 8 9 6 (18) 224 288 (64)

5-Year 125 111 1 3 353 329 2 3

7-Year 103 8 2 2 1 291 130 161

10-Year 6 8 2 3 4 5 200 6 8 132

30-Year 4 2 1 9 2 4 126 3 0 9 6

5-Year TIPS 1 6 4 1 (25) 3 2 4 1 (9)

10-Year TIPS 1 4 0 1 4 5 5 2 0 3 5

30-Year TIPS 6 0 6 2 2 0 2 2

Coupon Subtotal 592 506 8 5 1,697 1,274 423

Total 1,908 1,932 (25) 5,904 5,331 573

Coupon Issuance Coupon Issuance

April - June 2016 April - June 2016 Fiscal Year-to-Date

Bill Issuance Bill Issuance

April - June 2016 Fiscal Year-to-Date
16

Sources of Financing in Fiscal Year 2016 Q4

*Keeping announced issuance sizes and patterns constant for Nominal Coupons, TIPS, and FRNs as of 6/30/2016. Gross issuance does not 

reflect SOMA reinvestments. 

**Assumes an end-of-September 2016 cash balance of $350 billion versus a beginning-of-July 2016 cash balance of $364 billion.

Financing Estimates released by the Treasury can be found here: http://www.treasury.gov/resource-center/data-chart-center/quarterlyrefunding/Pages/Latest.aspx

Assuming Constant Coupon Issuance Sizes*

Treasury Announced Net Marketable Borrowing** 201

Net Coupon Issuance 5 2

Implied Change in Bills 149

Security Gross Maturing Net Gross Maturing Net

2-Year FRN 4 1 4 1 (0) 168 123 4 5

2-Year 7 8 8 7 (9) 345 372 (27)

3-Year 7 2 9 5 (23) 296 383 (87)

5-Year 102 108 (6) 455 438 1 7

7-Year 8 4 8 7 (3) 375 217 158

10-Year 6 3 2 3 4 0 263 9 1 172

30-Year 3 9 0 3 9 165 3 0 135

5-Year TIPS 1 4 0 1 4 4 6 4 1 5

10-Year TIPS 2 4 2 4 0 7 9 4 4 3 5

30-Year TIPS 0 0 0 2 2 0 2 2

Coupon Subtotal 517 465 5 2 2,214 1,739 476

July - September 2016

July - September 2016 Fiscal Year-to-Date

Coupon Issuance Coupon Issuance
1011

572

435

534 530 550

652 667 650

739 808

55%

60%

65%

70%

75%

80%

(400)

(200)

0

200

400

600

800

1,000

1,200 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $bn

OMB's Projection of Borrowing from the Public

Primary Deficit Net Interest Other Debt Held by Public

as % of GDP (RHS)

Debt Held by Public Net of

Financial Assets as a % of GDP (RHS)

17

OMB’s projections of net borrowing from the public are from Table S-11 of “The FY2017 Mid-Session Review.” Data labels at the top represent 

the change in debt held by the public in $ billions. “Other” represents borrowing from the public to provide direct and guaranteed loans.

* 2016 estimate reflects adjustments to account for the unwind in extraordinary measures.

$ bn %

Primary Deficit 600 8.4

Net Interest 5,233 73.2

Other 1,315 18.4

Total 7,148

FY2016 - FY2026 Cumulative Total
OMB's economic assumption of the 10-Year Treasury Note rates are from Table S-11 of “The FY2017 Mid-Session Review.” The forward rates 18

are the implied 10-Year Treasury Note rates on June 30 of that year. 1

1.5

2

2.5

3

3.5

4

4.5 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 1 0-Year Treasury Note Rate, %

Interest Rate Assumptions: 10-Year Treasury Note

OMB FY 2017 MSR Implied Forward Rates as of 06/30/2016

1 0-Year Treasury Rate of 1.47% 

as of 6/30/2016
19

Treasury’s primary dealer survey estimates can be found on page 11. OMB's projections of net borrowing from the public are from Table S-11 of 

“The FY2017 Mid-Session Review.” CBO's estimates of the borrowing from the public are from Table 1 of “An Analysis of the President’s 2017 

Budget.” See table at the end of this section for details.

0

200

400

600

800

1,000

1,200 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $ bn

Fiscal Year

Projected Net Borrowing Assuming Constant Future Issuance

Projected Net Borrowing CBO's "An Analysis of the President's 2017 Budget "

OMB's FY 2017 Mid-Session Review PD Survey Net Marketable Borrowing Estimates

OFP's FY 2016 Net Marketable Borrowing Estimate
20

Impact of SOMA Actions on Projected Net Borrowing Assuming Future 

Issuance Remains Constant

Treasury’s primary dealer survey estimates can be found on page 11. OMB's projections of net borrowing from the public are from Table S-11 of 

“The FY2017 Mid-Session Review.” CBO's estimates of the borrowing from the public are from Table 1 of “An Analysis of the President’s 2017 

Budget.” See table at the end of this section for details.

0

200

400

600

800

1,000

1,200

20162017201820192020202120222023202420252026

Fiscal Year

Without Fed Reinvestments ($ bn)

Projected Net Borrowing

CBO's "An Analysis of the President's 2017 Budget "

OFP's FY 2016 Net Marketable Borrowing Estimate

0

200

400

600

800

1,000

1,200

20162017201820192020202120222023202420252026

Fiscal Year

With Fed Reinvestments ($ bn)

OMB's FY 2017 Mid-Session Review

PD Survey Marketable Borrowing Estimates
Additional Funding Gap Assuming No SOMA Roll

21

(31)

(181)

(357)

(384)

(259)

(196)

(97)

(450)

(400)

(350)

(300)

(250)

(200)

(150)

(100)

(50)

0 2016 2017 2018 2019 2020 2021 2022 $ bn

Fiscal Year
22

Historical Net Marketable Borrowing and Projected Net Borrowing 

Assuming Future Issuance Remains Constant, $ billions

Net Borrowing capacity does not reflect SOMA reinvestments. 

Treasury’s primary dealer survey estimates can be found on page 11. OMB's projections of net borrowing from the public are from Table S-11 of 

“The FY2017 Mid-Session Review.” CBO's estimates of the borrowing from the public are from Table 1 of “An Analysis of the President’s 2017 

Budget.”

*OFP's FY 2016 Net Marketable Borrowing Estimate

Fiscal 

Year Bills 2/3/5 7/10/30 TIPS FRN

Historical/Projected 

Net Borrowing 

Capacity

OMB's FY 2017 MidSession Review

CBO's "An Analysis of 

the President's 2017 

Budget "

Primary Dealer 

Survey

2011 (311) 576 751 88 0 1,104 

2012 139 148 738 90 0 1,115 

2013 (86) 86 720 111 0 830 

2014 (119) (92) 669 88 123 669 

2015 (53) (282) 641 88 164 558 

2016 79 (97) 466 62 45 554 774* 829 635 

2017 76 (84) 221 47 (0) 259 572 508 652 

2018 0 (17) 202 42 (4) 223 435 452 751 

2019 0 14 67 43 0 124 534 578 

2020 0 (12) 83 17 0 88 530 637 

2021 0 (47) 99 (1) 0 51 550 697 

2022 0 36 133 (11) 0 158 652 838 

2023 0 66 140 (8) 2 200 667 876 

2024 0 10 160 (11) (0) 159 650 870 

2025 0 (13) 155 (53) (2) 88 739 977 

2026 0 (16) 169 (37) (0) 115 808 1,038 
Section IV:

Portfolio Metrics

23
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 24

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. 4 0

4 5

5 0

5 5

6 0

6 5

7 0

7 5

8 0

8 5 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Weighted Average Maturity (Months)

Calendar Year

Weighted Average Maturity of Marketable Debt Outstanding

Historical Adjust Nominal Coupons to Match Financing Needs Historical Average from 1980 to end of FY 2016 Q3

70.0 months on

6/30/2016

59.1 months

(Historical Average

from 1980 to Present)
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 25

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. 0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $ bn

Projected Gross Borrowing excluding Bills for Fiscal Year

Maturing in < 1 Year excluding Bills Projected Net Borrowing
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 26

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. See table on following page for details. 0

5

1 0

1 5

2 0

2 5 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $tr

Projected Maturity Profile from end of Fiscal Year

<= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10
27

This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. Portfolio composition by original issuance type 

and term can be found in the appendix (Page 45).

Recent and Projected Maturity Profile, $ billions

End of Fiscal Year <= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10 Total (0,5]

2008 2,152 711 280 653 310 499 617 5,222 3,796

2009 2,702 774 663 962 559 643 695 6,998 5,101

2010 2,563 1,141 895 1,273 907 856 853 8,488 5,872

2011 2,620 1,334 980 1,541 1,070 1,053 1,017 9,616 6,476

2012 2,951 1,373 1,104 1,811 1,214 1,108 1,181 10,742 7,239

2013 2,939 1,523 1,242 1,965 1,454 1,136 1,331 11,590 7,669

2014 2,935 1,739 1,319 2,207 1,440 1,113 1,528 12,281 8,199

2015 3,097 1,775 1,335 2,382 1,478 1,121 1,654 12,841 8,589

2016 3,213 1,852 1,587 2,456 1,529 1,200 1,823 13,659 9,108

2017 3,366 2,088 1,529 2,508 1,529 1,240 1,988 14,249 9,491

2018 3,632 2,019 1,611 2,511 1,554 1,266 2,112 14,705 9,773

2019 3,567 2,176 1,650 2,630 1,676 1,304 2,257 15,260 10,023

2020 3,691 2,222 1,623 2,767 1,734 1,306 2,470 15,812 10,302

2021 3,737 2,184 1,836 2,853 1,730 1,349 2,698 16,386 10,609

2022 3,699 2,442 1,829 2,955 1,828 1,346 2,964 17,063 10,925

2023 3,957 2,418 1,947 2,938 1,877 1,372 3,250 17,759 11,260

2024 3,974 2,581 1,930 3,072 1,962 1,396 3,524 18,438 11,556

2025 4,097 2,601 1,959 3,322 1,975 1,429 3,826 19,210 11,979

2026 4,117 2,616 2,190 3,400 2,092 1,512 4,125 20,051 12,323
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the basic 28

trajectory of average maturity absent changes to the mix of securities issued by Treasury. See table on following page for details. 0 %

10%

20%

30%

40%

50%

60%

70%

80%

90%

100% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 Percent Compositioin

Projected Maturity Profile from end of Fiscal Year

<= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10
29

Recent and Projected Maturity Profile, percent

This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. Portfolio composition by original issuance type 

and term can be found in the appendix (Page 45).

End of Fiscal Year <= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10 (0,3] (0,5]

2008 41.2 13.6 5.4 12.5 5.9 9.6 11.8 60.2 72.7

2009 38.6 11.1 9.5 13.7 8.0 9.2 9.9 59.1 72.9

2010 30.2 13.4 10.5 15.0 10.7 10.1 10.0 54.2 69.2

2011 27.2 13.9 10.2 16.0 11.1 10.9 10.6 51.3 67.3

2012 27.5 12.8 10.3 16.9 11.3 10.3 11.0 50.5 67.4

2013 25.4 13.1 10.7 17.0 12.5 9.8 11.5 49.2 66.2

2014 23.9 14.2 10.7 18.0 11.7 9.1 12.4 48.8 66.8

2015 24.1 13.8 10.4 18.5 11.5 8.7 12.9 48.3 66.9

2016 23.5 13.6 11.6 18.0 11.2 8.8 13.3 48.7 66.7

2017 23.6 14.7 10.7 17.6 10.7 8.7 14.0 49.0 66.6

2018 24.7 13.7 11.0 17.1 10.6 8.6 14.4 49.4 66.5

2019 23.4 14.3 10.8 17.2 11.0 8.5 14.8 48.4 65.7

2020 23.3 14.1 10.3 17.5 11.0 8.3 15.6 47.7 65.2

2021 22.8 13.3 11.2 17.4 10.6 8.2 16.5 47.3 64.7

2022 21.7 14.3 10.7 17.3 10.7 7.9 17.4 46.7 64.0

2023 22.3 13.6 11.0 16.5 10.6 7.7 18.3 46.9 63.4

2024 21.6 14.0 10.5 16.7 10.6 7.6 19.1 46.0 62.7

2025 21.3 13.5 10.2 17.3 10.3 7.4 19.9 45.1 62.4

2026 20.5 13.0 10.9 17.0 10.4 7.5 20.6 44.5 61.5
Section V:

Demand

30
31

*Weighted averages of Competitive Awards.

**Approximated using prices at settlement and includes both Competitive and Non-Competitive Awards. For TIPS’ 10-year equivalent, a 

constant auction BEI is used as the inflation assumption.

Summary Statistics for Fiscal Year 2016 Q3 Auctions

Security 

Type Term Stop Out Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards 

($bn)

% 

Primary 

Dealer*

% 

Direct*

% 

Indirect*

Non-Competitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)**

Bill 4-Week 0.225 3.4 535.3 65.5 5.0 29.5 3.6 0.0 4.5

Bill 13-Week 0.266 3.6 379.3 62.5 5.8 31.7 4.9 0.0 10.6

Bill 26-Week 0.397 3.8 318.5 49.9 3.9 46.2 4.6 0.0 17.9

Bill 52-Week 0.616 3.7 59.1 52.7 2.3 45.0 0.6 0.0 6.6

Coupon 2-Year 0.836 2.8 77.5 32.9 19.0 48.1 0.5 17.3 20.8

Coupon 3-Year 0.898 2.8 71.7 33.9 10.9 55.2 0.2 5.6 25.4

Coupon 5-Year 1.341 2.4 101.9 30.2 7.4 62.4 0.1 22.7 66.3

Coupon 7-Year 1.594 2.6 83.9 21.3 13.4 65.2 0.1 18.7 74.8

Coupon 10-Year 1.725 2.7 62.9 19.3 11.4 69.2 0.1 5.3 69.0

Coupon 30-Year 2.566 2.3 39.0 27.8 9.2 63.0 0.0 3.5 98.3

TIPS 5-Year (0.195) 2.4 15.9 32.8 8.2 59.1 0.1 0.0 8.8

TIPS 10-Year 0.275 2.3 11.0 32.5 4.1 63.4 0.0 2.8 14.1

TIPS 30-Year 0.905 2.7 5.0 23.0 0.0 77.0 0.0 0.7 16.1

FRN 2-Year 0.189 3.4 41.0 57.1 0.6 42.3 0.0 4.0 0.0

Total Bills 0.297 3.6 1,292.2 60.2 4.8 35.0 13.6 0.0 39.6

Total Coupons 1.392 2.6 437.0 27.8 11.9 60.3 0.9 73.1 354.6

Total TIPS 0.138 2.4 31.9 31.2 5.5 63.4 0.1 3.5 39.0

Total FRNs 0.189 3.4 41.0 57.1 0.6 42.3 0.0 4.0 0.0
1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6 Jun-06

Jun-07Jun-08Jun-09Jun-10Jun-11Jun-12Jun-13Jun-14Jun-15Jun-16 Bid-to-Cover Ratio

Bid-t o-Cover Ratios for Treasury Bills

4-Week (13-week moving average) 13-Week (13-week moving average)

26-Week (13-week moving average) 52-Week (6-month moving average)

32
2

2.5

3

3.5

4

4.5

5 Jun-14

Jul-14

Aug-14

Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15

May-15

Jun-15

Jul-15

Aug-15

Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16

May-16

Jun-16 Bid-to-Cover Ratio

Bid-to-Cover Ratios for FRNs

33
34

1

1.5

2

2.5

3

3.5

4

4.5

Jun-11

Sep-11 Dec-11 Mar-12 Jun-12Sep-12 Dec-12 Mar-13 Jun-13Sep-13 Dec-13 Mar-14 Jun-14Sep-14 Dec-14 Mar-15 Jun-15Sep-15 Dec-15 Mar-16 Jun-16 Bid-to-Cover Ratio

Bid-to-Cover Ratios for 2-, 3-, and 5-Year Nominal Securities

( 6-Month Moving Average)

2-Year 3-Year 5-Year
35

1

1.5

2

2.5

3

3.5

Jun-11

Sep-11 Dec-11 Mar-12 Jun-12Sep-12 Dec-12 Mar-13 Jun-13Sep-13 Dec-13 Mar-14 Jun-14Sep-14 Dec-14 Mar-15 Jun-15Sep-15 Dec-15 Mar-16 Jun-16 Bid-to-Cover Ratio

Bid-t o-Cover Ratios for 7-, 10-, and 30-Year Nominal Securities

( 6-Month Moving Average)

7-Year 10-Year 30-Year
1

1.5

2

2.5

3

3.5

Jun-06Jun-07Jun-08Jun-09Jun-10Jun-11Jun-12Jun-13Jun-14Jun-15Jun-16 Bid-to-Cover Ratio

Bid-t o-Cover Ratios for TIPS

5-Year 10-Year (6-month moving average) 20-Year 30-Year

36
37 Excludes SOMA add-ons. The “Other” category includes categories that are each less than 2%, which include Depository Institutions, Individuals, 

Pension and Insurance. 0 %

5 %

10%

15%

20%

25%

30%

Jun-12

Aug-12 Oct-12 Dec-12 Feb-13 Apr-13

Jun-13

Aug-13 Oct-13 Dec-13 Feb-14 Apr-14

Jun-14

Aug-14 Oct-14 Dec-14 Feb-15 Apr-15

Jun-15

Aug-15 Oct-15 Dec-15 Feb-16 Apr-16

Jun-16 1 3-week moving average

Percent Awarded in Bill Auctions by Investor Class 

(13-Week Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
38 Excludes SOMA add-ons. The “Other” category includes categories that are each less than 2%, which include Depository Institutions, Individuals, 

Pension and Insurance. 0 %

5 %

10%

15%

20%

25%

30%

35%

40%

45%

50%

Jun-12

Aug-12 Oct-12 Dec-12 Feb-13 Apr-13

Jun-13

Aug-13 Oct-13 Dec-13 Feb-14 Apr-14

Jun-14

Aug-14 Oct-14 Dec-14 Feb-15 Apr-15

Jun-15

Aug-15 Oct-15 Dec-15 Feb-16 Apr-16

Jun-16

6-month moving average

Percent Awarded in 2-, 3-, and 5-Year Nominal Security 

Auctions by Investor Class (6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
39 Excludes SOMA add-ons. The “Other” category includes categories that are each less than 2%, which include Depository Institutions, Individuals, 

Pension and Insurance. 0 %

10%

20%

30%

40%

50%

60%

Jun-12

Aug-12 Oct-12 Dec-12 Feb-13 Apr-13

Jun-13

Aug-13 Oct-13 Dec-13 Feb-14 Apr-14

Jun-14

Aug-14 Oct-14 Dec-14 Feb-15 Apr-15

Jun-15

Aug-15 Oct-15 Dec-15 Feb-16 Apr-16

Jun-16

6-month moving average

Percent Awarded in 7-, 10-, 30-Year Nominal Security Auctions 

by Investor Class (6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
40 Excludes SOMA add-ons. The “Other” category includes categories that are each less than 2%, which include Depository Institutions, Individuals, 

Pension and Insurance. 0 %

10%

20%

30%

40%

50%

60%

70%

Jun-12

Aug-12 Oct-12 Dec-12 Feb-13 Apr-13

Jun-13

Aug-13 Oct-13 Dec-13 Feb-14 Apr-14

Jun-14

Aug-14 Oct-14 Dec-14 Feb-15 Apr-15

Jun-15

Aug-15 Oct-15 Dec-15 Feb-16 Apr-16

Jun-16

6-month moving average

Percent Awarded in TIPS Auctions by Investor Class

( 6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
41 Excludes SOMA add-ons. 

20%

30%

40%

50%

60%

70%

80%

Jun-12

Aug-12 Oct-12 Dec-12 Feb-13 Apr-13

Jun-13

Aug-13 Oct-13 Dec-13 Feb-14 Apr-14

Jun-14

Aug-14 Oct-14 Dec-14 Feb-15 Apr-15

Jun-15

Aug-15 Oct-15 Dec-15 Feb-16 Apr-16

Jun-16

% of Total Competitive Amount Awarded

Primary Dealer Awards at Auction

4/13/26-Week (13-week moving average) 52-Week (6-month moving average)

2/3/5 (6-month moving average) 7/10/30 (6-month moving average)

TIPS (6-month-moving average)
42 Excludes SOMA add-ons. 

0 %

5 %

10%

15%

20%

25%

30%

Jun-12

Aug-12 Oct-12 Dec-12 Feb-13 Apr-13

Jun-13

Aug-13 Oct-13 Dec-13 Feb-14 Apr-14

Jun-14

Aug-14 Oct-14 Dec-14 Feb-15 Apr-15

Jun-15

Aug-15 Oct-15 Dec-15 Feb-16 Apr-16

Jun-16

% of Total Competitive Amount Awarded

Direct Bidder Awards at Auction

4/13/26-Week (13-week moving average) 52-Week (6-month moving average)

2/3/5 (6-month moving average) 7/10/30 (6-month moving average)

TIPS (6-month-moving average)
43 Foreign includes both private sector and official institutions.

0

2 0

4 0

6 0

8 0

100

120

Jun-14

Jul-14

Aug-14

Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15

May-15

Jun-15

Jul-15

Aug-15

Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16

May-16

Jun-16 $ bn

Total Foreign Awards of Treasuries at Auction, $ billions

Bills 2,3,5 7,10,30 TIPS FRN
Appendix

44
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the basic 45

trajectory of average maturity absent changes to the mix of securities issued by Treasury. See table on following page for details. 0 %

10%

20%

30%

40%

50%

60%

70%

80%

90%

100% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026

End of Fiscal Year

Projected Portfolio Composition by Issuance Type

Bills 2,3,5 7,10,30 TIPS (principal accreted to projection date) FRN
46

Recent and Projected Portfolio Composition by Issuance Type, Percent

This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. 

End of Fiscal 

Year Bills 2-, 3-, 5-Year Nominal Coupons

7-, 10-, 30-Year 

Nominal 

Coupons

Total 

Nominal 

Coupons

TIPS (principal accreted 

to projection date) FRN

2008 28.5 34.5 26.9 61.4 10.0 0.0

2009 28.5 36.2 27.4 63.6 7.9 0.0

2010 21.1 40.1 31.8 71.9 7.0 0.0

2011 15.4 41.4 35.9 77.3 7.3 0.0

2012 15.0 38.4 39.0 77.4 7.5 0.0

2013 13.2 35.8 43.0 78.7 8.1 0.0

2014 11.5 33.0 46.0 79.0 8.5 1.0

2015 10.6 29.4 49.0 78.3 8.8 2.2

2016 10.5 27.9 50.3 78.2 8.8 2.4

2017 10.6 27.3 50.8 78.1 8.9 2.3

2018 10.3 27.1 51.3 78.4 9.1 2.2

2019 9.9 27.4 51.3 78.8 9.2 2.1

2020 9.6 27.7 51.6 79.3 9.1 2.1

2021 9.2 27.7 52.2 79.8 8.9 2.0

2022 8.9 27.8 52.8 80.6 8.6 1.9

2023 8.5 28.0 53.2 81.2 8.4 1.9

2024 8.2 27.9 53.9 81.8 8.2 1.8

2025 7.9 27.9 54.7 82.6 7.8 1.7

2026 7.5 28.1 55.3 83.4 7.4 1.6
*Weighted averages of Competitive Awards. 47

**Approximated using prices at settlement and includes both Competitive and Non-Competitive Awards.

Issue Settle Date Stop Out 

Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards ($bn)

% Primary 

Dealer* % Direct* % Indirect*

NonCompetitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)*

4-Week 4/7/2016 0.185 3.58 34.7 58.4 5.3 36.3 0.2 0.0 0.3

4-Week 4/14/2016 0.200 3.60 34.7 70.9 4.8 24.3 0.3 0.0 0.3

4-Week 4/21/2016 0.175 3.55 34.7 66.5 6.5 27.0 0.3 0.0 0.3

4-Week 4/28/2016 0.190 3.83 34.7 56.9 5.8 37.3 0.3 0.0 0.3

4-Week 5/5/2016 0.170 3.63 39.7 62.6 6.8 30.6 0.2 0.0 0.3

4-Week 5/12/2016 0.245 3.33 44.7 63.3 5.4 31.3 0.3 0.0 0.4

4-Week 5/19/2016 0.240 3.36 44.7 66.8 5.5 27.7 0.3 0.0 0.4

4-Week 5/26/2016 0.265 3.45 44.2 67.6 4.1 28.4 0.3 0.0 0.4

4-Week 6/2/2016 0.265 3.06 39.7 70.6 8.9 20.5 0.2 0.0 0.3

4-Week 6/9/2016 0.190 3.52 39.6 64.0 2.1 33.9 0.3 0.0 0.3

4-Week 6/16/2016 0.240 3.33 44.7 69.1 4.0 26.9 0.3 0.0 0.4

4-Week 6/23/2016 0.250 3.39 49.7 51.9 4.8 43.3 0.3 0.0 0.4

4-Week 6/30/2016 0.260 3.09 49.6 81.1 2.1 16.7 0.3 0.0 0.4

13-Week 4/7/2016 0.235 3.97 27.5 60.0 6.9 33.1 0.4 0.0 0.8

13-Week 4/14/2016 0.230 3.91 27.5 51.3 8.3 40.4 0.4 0.0 0.8

13-Week 4/21/2016 0.220 4.02 27.6 58.8 9.6 31.7 0.4 0.0 0.8

13-Week 4/28/2016 0.250 3.66 26.8 65.7 1.4 32.9 0.3 0.0 0.8

13-Week 5/5/2016 0.220 3.80 27.4 67.6 4.2 28.2 0.4 0.0 0.8

13-Week 5/12/2016 0.240 3.34 30.5 78.1 4.6 17.2 0.4 0.0 0.9

13-Week 5/19/2016 0.275 3.70 30.5 58.1 4.5 37.3 0.4 0.0 0.8

13-Week 5/26/2016 0.350 3.40 29.8 52.5 9.9 37.7 0.4 0.0 0.8

13-Week 6/2/2016 0.340 3.35 30.3 58.3 7.1 34.6 0.4 0.0 0.8

13-Week 6/9/2016 0.285 3.54 30.6 54.3 2.7 43.0 0.3 0.0 0.8

13-Week 6/16/2016 0.270 3.43 30.5 66.5 5.5 28.0 0.4 0.0 0.8

13-Week 6/23/2016 0.270 3.61 30.5 65.4 8.5 26.0 0.4 0.0 0.8

13-Week 6/30/2016 0.260 3.42 29.7 75.6 2.4 22.0 0.3 0.0 0.8

26-Week 4/7/2016 0.385 4.10 23.3 60.6 7.4 31.9 0.4 0.0 1.3

26-Week 4/14/2016 0.350 3.83 23.3 56.6 8.6 34.9 0.3 0.0 1.3

26-Week 4/21/2016 0.350 3.85 23.5 51.3 6.0 42.7 0.3 0.0 1.3

26-Week 4/28/2016 0.400 3.76 22.7 53.5 1.7 44.8 0.3 0.0 1.3

26-Week 5/5/2016 0.395 3.89 23.2 51.0 3.2 45.7 0.4 0.0 1.3

26-Week 5/12/2016 0.380 4.26 25.4 30.9 2.0 67.1 0.4 0.0 1.4

26-Week 5/19/2016 0.370 4.00 25.4 54.6 2.0 43.4 0.4 0.0 1.4

26-Week 5/26/2016 0.480 3.65 24.9 38.3 8.6 53.1 0.3 0.0 1.4

26-Week 6/2/2016 0.475 3.62 25.6 50.9 3.8 45.3 0.3 0.0 1.4

26-Week 6/9/2016 0.430 3.39 25.6 63.5 2.3 34.2 0.3 0.0 1.4

26-Week 6/16/2016 0.400 4.15 25.5 32.3 1.6 66.1 0.4 0.0 1.4

26-Week 6/23/2016 0.400 3.53 25.5 60.6 3.1 36.2 0.4 0.0 1.4

26-Week 6/30/2016 0.340 3.72 24.7 45.9 0.6 53.5 0.3 0.0 1.4

52-Week 4/28/2016 0.605 3.57 19.8 53.1 2.5 44.4 0.2 0.0 2.2

52-Week 5/26/2016 0.685 3.77 19.5 62.9 2.1 35.0 0.2 0.0 2.2

52-Week 6/23/2016 0.560 3.71 19.8 42.2 2.3 55.5 0.2 0.0 2.2

Bills
48

*Weighted averages of Competitive Awards.

**Approximated using prices at settlement and includes both Competitive and Non-Competitive Awards. For TIPS’ 10-Year Equivalent, a 

constant auction BEI is used as the inflation assumption.

Issue Settle Date Stop Out 

Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards ($bn)

% Primary 

Dealer* % Direct* % Indirect*

NonCompetitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)*

2-Year 5/2/2016 0.842 2.64 25.9 38.4 14.5 47.1 0.1 6.9 7.2

2-Year 5/31/2016 0.920 3.00 25.8 17.7 32.5 49.8 0.2 6.6 7.1

2-Year 6/30/2016 0.745 2.72 25.9 42.7 9.9 47.4 0.1 3.8 6.5

3-Year 4/15/2016 0.890 2.72 23.8 32.6 11.5 56.0 0.1 0.2 7.9

3-Year 5/16/2016 0.875 2.93 23.9 28.3 10.2 61.5 0.1 5.4 9.7

3-Year 6/15/2016 0.930 2.79 24.0 40.8 11.1 48.1 0.0 0.0 7.8

5-Year 5/2/2016 1.410 2.41 33.9 29.8 6.8 63.4 0.1 9.0 23.1

5-Year 5/31/2016 1.395 2.60 33.9 21.8 11.6 66.6 0.1 8.7 22.5

5-Year 6/30/2016 1.218 2.29 34.0 39.1 3.7 57.2 0.0 5.0 20.8

7-Year 5/2/2016 1.634 2.65 28.0 20.2 14.2 65.5 0.0 7.4 26.0

7-Year 5/31/2016 1.652 2.57 28.0 18.5 16.9 64.6 0.0 7.1 25.3

7-Year 6/30/2016 1.497 2.56 28.0 25.3 9.1 65.6 0.0 4.1 23.5

10-Year 4/15/2016 1.765 2.75 20.0 24.8 15.3 60.0 0.0 0.1 20.1

10-Year 5/16/2016 1.710 2.68 23.0 14.7 11.8 73.5 0.0 5.2 28.9

10-Year 6/15/2016 1.702 2.70 20.0 19.2 7.2 73.6 0.0 0.0 20.0

30-Year 4/15/2016 2.596 2.40 12.0 24.1 10.8 65.1 0.0 0.1 27.8

30-Year 5/16/2016 2.615 2.19 15.0 31.5 8.8 59.7 0.0 3.4 42.9

30-Year 6/15/2016 2.475 2.42 12.0 27.0 8.1 64.9 0.0 0.0 27.6

2-Year FRN 5/2/2016 0.190 3.57 15.0 46.8 0.0 53.2 0.0 4.0 0.0

2-Year FRN 5/27/2016 0.188 3.35 13.0 66.1 1.9 31.9 0.0 0.0 0.0

2-Year FRN 6/24/2016 0.188 3.15 13.0 59.9 0.0 40.1 0.0 0.0 0.0

Issue Settle Date Stop Out 

Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards ($bn)

% Primary 

Dealer* % Direct* % Indirect*

NonCompetitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)*

5-Year TIPS 4/29/2016 (0.195) 2.42 15.9 32.8 8.2 59.1 0.1 0.0 8.8

10-Year TIPS 5/31/2016 0.275 2.27 11.0 32.5 4.1 63.4 0.0 2.8 14.1

30-Year TIPS 6/30/2016 0.905 2.69 5.0 23.0 0.0 77.0 0.0 0.7 16.1

Nominal Coupons

TIPS
August 2016

T B A C C H A R G E Q U E S T I O N : C Y B E R S E C U R I T Y

 
August 2nd 2016

Charge Question

Recent cyber security related incidents have demonstrated that breaches in critical financial services IT infrastructure could have 

the potential to disrupt domestic and global business practices. What can Treasury and market participants learn from these 

incidents? What measures are market participants taking to counter these types of threats and what are cyber security best 

practices for operating critical IT infrastructure in the financial services industry? Please comment specifically on best practices as 

they relate to electronic trading, exchange platforms, clearing and settlement systems, and payment systems. What, if any, actions 

should Treasury contemplate to mitigate cyber threats specifically?

1
Cybersecurity Facts 

 Cybersecurity is a critical risk today. It is estimated that there are over 80mm events per year with 70% of 

attacks thought to be undetected. Cybercrime is estimated to have cost the global economy over $400bn in 

2014. (CSIS/McAfee Estimating the Global Cost of Cybercrime, June. 2014)

 62% of firms with more than $1bn in annual revenues reported attempted or actual fraud in 2015 (AFP 

survey of Payment Fraud)

 Only 30% of companies are discovering breaches internally while 70% learned of the breach from an 

outside entity such as law enforcement. The median number of days that attackers were present on a 

victim’s network before being discovered was 146 days in 2015 (Mandiant)

 Spending on cybersecurity, which is expected to reach $90 bn in 2016, has been growing at a 10% annual 

rate (ISI) . Meanwhile the number of attacks is growing exponentially with the number of records 

compromised in reported breaches more than tripling from 2013 to 2015 (Bernstein).

 The threat is dynamic and is rapidly changing. Four years ago, the majority of incidents appear related to 

social engineering; today they are primarily related to malware, email spoofing and business email 

compromise. Industry experts say there’s been a 91% year over year increase in the number of targeted 

phishing attacks recorded globally. 

Source: The New Yorker

2
Cyber Threats We Face Today

Malicious Insiders

Malicious activity from insiders 

including current and former 

employees, and 

consultants/contractors 

Social Engineering

Non-technical (e.g phone or email) art 

of manipulating people into performing 

compromising actions for the purpose 

of divulging confidential information or 

circumventing normal security 

procedures

Denial of Service

Denial-of-Service (DoS) attack is 

an attempt to make a machine or 

network resource unavailable to its 

intended users 

Reconnaissance

Activity meant to gather information 

about a network for purposes of 

understanding a network’s layout 

and composition 

Malware

Malware is malicious software which is 

designed to access a computer system 

without the user’s informed consent with 

the intent of compromising the 

confidentiality, integrity, or availability of 

the victim’s data, applications, or 

operation system 

Data Exfiltration

Intentional or unintentional use of 

IT to disclose or steal intellectual 

property including industrial 

espionage involving outsiders 

Information Tampering

Intended or unintended 

interference of data which 

causes damage or 

unauthorized alteration 

Unauthorized Access

An attempt by an external or 

internal actor, to gain unauthorized 

access to restricted systems, by 

way of exploitation of vulnerabilities 

or failed internal technology 

controls 

3
Largest data breaches at Financial firms and Government Organizations

Data Sensitivity, Y Axis: 1: Only email address / Online information, 2: SSN/Personal details, 3: Credit card information, 4: Email password / Health records, 5: Full bank account 

details

Source: informationisbeautiful.net database

0

1

2

3

4

5

6

2004 2005 2006 2008 2009 2010 2012 2013 2014 2016 Data Sensitivity

Year

Selected losses > 30k records; Bubble size = number of records compromized

Financial firms

Government Organizations

Cardsystems

Solutions

Heartland Payment 

Systems

Philippines Election 

Commission

Turkish Citizenship 

Database

US Banks, Payment 

processors and 

Court Ventures chain stores

(Experian)

US Office of 

Personnel 

Management

Korea Credit 

Bureau

Virginia 

Department of 

Health

Greek 

Government

UK Revenue and 

Customs

US Department of 

Veterans Affairs

JP Morgan 

Chase

European Central 

Bank

Citigroup

Office of Texas 

Attorney General

Educational Credit 

Management Corp

Countrywide 

Financial

BNY

Mellon

Chile Ministry of 

Education

4
Recent publicized breaches

Bangladesh Bank/SWIFT

 FBI suspects Bangladesh Central 

Bank (BCB) employees. Others 

suspect North Korea

 Malware, Social Engineering

Actors /Attack vectors Causes

 On February 4th 2016 hackers sent about three dozen requests to the Federal 

Reserve Bank of New York using the SWIFT credentials of Bangladesh Central 

Bank employees to transfer $951m to accounts in Sri Lanka and the Philippines

 The Federal Reserve Bank of New York blocked 30 transfers for $850m but 5 

transfers were processed. $20m was recovered in Sri Lanka but $81m was lost 

in the Philippines where the funds were laundered through casinos

BCB did not have proper firewalls. 

Hackers obtained valid credentials 

used by bank employees to initiate 

transactions as if they were legitimate 

bank employees

US Office of Personnel Management

 US intelligence believes the 

intrusion originated in China

 Malware

 One of the largest known thefts of US government data started around March 

2014 and was disclosed in June 2015

 Stolen data includes personal data records of 21.5 million individuals including 

social security numbers, addresses, financial and health histories , and 

fingerprints.

JP Morgan Chase

 US federal indictments issued 

against five hackers. Four were 

arrested in July 2015

 Malware

Actors /Attack vectors Causes

 The 2014 cyber attack against JP Morgan Chase compromised data of over 76 

million households. Account login information was not compromised but names, 

email and postal addresses were obtained 

 The breach was discovered while investigating a breach on the Chase Corporate 

Challenge website that was not connected to the Bank’s network

Malware on an employee’s personal 

computer gave hackers access to their 

login credentials. Failure to upgrade a 

network server with a dual password 

authentication scheme allowed hackers 

to access the network

Actors /Attack vectors Causes

Poor security software. Data was not 

protected by practices like data 

masking, redaction, and encryption. 

Hackers obtained credentials from a 

contractor used by OPM to conduct 

background checks

Anthem

 The FBI is still investigating the 

attack. News reports link the attack 

to hackers from China

 Malware, Social Engineering

 In February 2014, Anthem, Inc. disclosed that personal data of 79 million current, 

and former members and employees was stolen. Customers names, social 

security numbers, birth dates, addresses and income data was stolen

 The breach may have been ongoing for about nine months before it was 

discovered. 

Actors /Attack vectors Causes

Network credentials of at least five IT 

employees were stolen. Employees 

had more access to the network than 

was required by their roles. Stolen 

data was not stored in encrypted 

format on the internal servers

5
Costs

Financial Services

 Highest average cost of cybercrime across industries

 Attacked 300 times more frequently than businesses in 

other industries

Industry trends in spending 

 According to the “Banking & Financial Services 

Cybersecurity: US Market 2015-2020 Report”, the 2015 

U.S. financial services cybersecurity market reached 

$9.5 billion, making it the largest non-government 

cybersecurity market

 Increase of $2 billion expected over the next 2 years 

according to a recent PWC survey. Large banking 

institutions spending $300-500+ million in 2016 on 

cybersecurity 

8.2

8.7

9.4

9.8

11.0

11.4

12.0

12.1

12.9

14.9

16.5

23.2

27.6

28.3

5.2

5.4

6.9

6.7

6.6

9.6

5.5

7.8

7.4

10.0

10.4

21.0

21.7

19.4

0 10 20 30

Hospitality

Consumer Products

Public Sector

Healthcare

Industrial

Education and Research

Retail

Transportation

Services

Communications

Technology

Defense and aerospace

Energy & Utilities

Financial Services

Cost of Cybercrime, Average annualized cost per 

company, by industry sector, $m

Six Year Average

2015

Based on a study of 58 organizations asked to report cyber crime spend 

over a four week period, which is then annualized. “2015 Cost of Cyber 

Crime Study: United States”, Ponemon Institute. 

6
Lessons Learned

Multi-Faceted Risk

 Legal

 Financial

 Reputational

 Regulatory

 Market

Cross-Functional 

Impact

 Not solely an IT issue

 Serious risk across the organization

 Broader business challenge

Moving Target

 Threats continuously evolve

 Focus on detection and response

 Collaboration is critical 

Risk Perimeter

 Insider and outsider risks

 3rd party risk

 Identity (ensure people are who they say they are)

7
Best Practices

10 steps for better protection

Independent 

Assessment 1

Do a complete independent assessment of your firm's infrastructure and data identifying all the vulnerabilities around

cybersecurity. Engage an experienced engineering firm that understands the technical risks and complexities of enterprise

architecture.

Identify

Protect

Detect

Respond

Recover

9 Join FS-ISAC

Join an industry based sharing forum. If you are not already part of the FS-ISAC, join.

Identity and access 

management 2

Track/control/prevent secure access to critical assets according to the formal determination of which persons, computers, and

applications have a need and right to access these critical assets based on an approved classification

3 Security operations Continuously collect, manage, and analyze threat intelligence and security events to prevent, detect, understand, mitigate, and

recover from an attack

Secure data and 

infrastructure

4

Make security an inherent attribute of the enterprise by specifying, designing, and building-in features that allow high confidence 

systems operations while denying or minimizing opportunities for attackers.

Cyber resiliency

Develop capabilities, controls and procedures to ensure continuity and recovery of operations in the event of an infrastructure 

10 disruption, which may range from mild routine failure of computing devices to severe cyber catastrophes

5 Mandatory training

Establish a baseline training program for all employees that is mandatory and focuses on the specific actions employees need to 

take to protect the firm. Once you have trained your employees, actively test them. For example, send your employees targeted

phishing emails; require those who click in the phishing emails to take additional training.

Attack yourself

Third parties

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Run simulations and drills to assess your capabilities. Create a Red Team and have them attack your systems using the same

techniques bad guys do. Also consider establishing a program to harvest credentials and account numbers that might be in the 

underground related to your bank to detect compromises you may not otherwise be aware of. Learn lessons and repeat. Include

colleagues from the business, in addition to technologists, in the table top exercises

Understand your third party environment and upgrade your contract provisions to ensure they are following the same standards

you are striving for in your own environments.

7

Government 

engagement 8

Ensure you have a clear engagement model with the government, including law enforcement. Who are you going to call? Which

agency and under what circumstances? Have the relationship established up front and the engagement documented in a runbook.

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Resources

Financial Services Information Sharing and Analysis 

Center (FS-ISAC) 

•https://www.fsisac.com/

•Nearly 7,000 members - up approximately 75% since December 2013

•Treasury is a major government sponsor

•Real time communication on threats

•Best practice publications: 

https://www.fsisac.com/news/industry_best_practices

National Institute of Standards and Technology (NIST)

•http://www.nist.gov/

•Collaboration of industry and government

•Standards, guidelines, practices to manage cyber risks

•2014 Cybersecurity Framework for reducing cyber risks to critical 

infrastructure (Executive Order 13636)

•Regulators (SEC, FINRA, SIFMA, etc.) leveraging in their reviews

United States Computer Emergency Readiness Team 

(US-CERT)

•https://www.us-cert.gov/

•Broader public information sharing 

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Cybersecurity risks and Treasury auctions

Unforeseen and tragic incidents have disrupted regular market operations in the past, leading to market access risk 

for Treasury

Incident Disruption dates # of 

days

Description Auctions affected and sizes

September 11 

attack 

Sep 11, 2001 (market fully closed)

Sep 12, 2001 (market fully closed)

Sep 13, 2001 (open w/ limited 

trading)

2-3 Bond markets were closed on Sep 11 and 

Sep 12, and reopened with extremely 

limited trading on Sep 13 (equities were 

closed until Sep 17).

$10bn 4-week bill auction Sep 11, 

2001 was rescheduled for Sep 12, 

2001 and then finally cancelled

Super storm 

Sandy

Oct 29, 2012 (market closed early)

Oct 30, 2012 (market fully closed)

1.5 Bond markets were closed for a day and a 

half – it closed early on Oct 29, 2012 and 

was fully closed on Tuesday Oct 30.

(Note: Fed was open, so settlements could 

occur)

$25bn 4-week bill auction brought

forward from Oct 30, 2012 to Oct 

29, 2012

TAAPS 

(Treasury 

auction system) 

IT Issue

Dec 2, 2013 (auction postponed) 1 The noncompetitive and competitive

portion of the 13- and 26-week bill 

auctions, originally scheduled to close on 

Dec 2, had to be rescheduled to the next 

day due to an error that occurred during a 

test of Treasury’s auction system. 

Settlement date remained unchanged.

$32bn 13-week bills and $27bn 

26-week bills postponed from Dec 

2, 2013 to Dec 3, 2013

Technical issue Feb 25, 2016 (auction postponed) 1 The noncompetitive and competitive 

portion of the 7-year note auction originally 

scheduled to close on February 25, had to 

be rescheduled to the next day due to a 

technical issue

$28bn 7-year notes postponed 

from Feb 25, 2016 to Feb 26, 2016

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Treasury’s TAAPS system was introduced in 1993 and has improved the efficiency 

of the Treasury auction process. Nevertheless, TAAPS remains exposed to potential 

cybersecurity risks

Current operational relationships in the Treasury market

Source: Emerging Issues in the functioning of the US Treasury Market, April 2016, Promontory Financial Group LLC.

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 The Treasury Auction Automated Processing System (TAAPS) is a web-based system with an infrastructure that 

contains two channels for bid submission, a dealer private network and the capability to submit and receive bids over the 

public Internet. 
Treasury’s current resiliency plan involves multiple locations and annual testing with 

a manual phone-based contingency when TAAPs is unavailable 

 For contingency purposes, Treasury and its fiscal agent, The Federal Reserve Bank of New York have developed and fully 

staffed four geographically dispersed auction operations sites; Treasury also requires primary dealers conduct a live auction 

from an alternative Disaster Recovery site at least once a quarter.

 At least once a year, primary dealers participate in a test of Treasury’s capability to execute a same-day manual auction 

(announce, auction, and issue), with mock bids submitted over the phone to the Federal Reserve Bank of New York, and 

mock award notices prepared manually and forwarded by email or fax.

 If needed, the contingency also allows Treasury to use the Government Emergency Telecommunications System (GETS). 

GETS provides emergency access and priority processing in the Public Switched Telephone Network (PSTN), and is 

intended for use in an emergency or crisis situation where the PSTN is congested.

 One potential issue with conducting a phone-based manual auction is the speed with which the Treasury can manually 

process multiple bids from multiple primary dealers via the phone; the process likely requires dealers to submit bids well in

advance of the auction deadline

 Longer processing times (and restricting phone participation to primary dealers) likely mean less competitive pricing 

for Treasury. To be sure, this is a less important consideration in an emergency situation where TAAPs is 

unavailable for a prolonged period and Treasury cash balances are depleted

 In addition to testing the phone-based contingency through mock auctions, Treasury should periodically conduct 

small-scale live auctions of its phone-based contingency. This would be similar to what is done with buybacks where 

Treasury conducts small size repurchase operations as a test of its buyback program. 

 Treasury should also consider alternative independent secured communication systems for dealers to submit 

encrypted files as a contingency bidding process when TAAPs is unavailable

 This should be more efficient than a manual phone based system and allow for shorter processing times but will 

require additional investment on the part of Treasury

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Lengthening the time period between auction and settlement

 Lengthening the time period between auction and 

settlement has the advantage of giving the Treasury more 

flexibility to delay auctions in the event of a cyber incident. 

However, extending the settlement period creates a longer 

un-margined credit exposure between the purchase/sale of 

the WI and settlement date. 

 Treasury might consider splitting mid-month and end-ofmonth auctions across multiple weeks to gain additional 

flexibility (e.g. conducting the 2-year auction the week 

before the 5-year and 7-year auction). When keeping 

auction date and settlement date in the same calendar 

week, this can force Treasury to auction securities on a 

Monday. Market depth and trading volumes are lower on 

Mondays, and have resulted in lower auction coverage 

ratios, end-user share, and less negative auction tails

Auction statistics for 2- and 3-year Treasury note 

auctions, data over the last 2 years; units as 

indicated

Maturity

Monday 

auction

All other 

days

Monday 

auction

All other 

days

Monday 

auction

All other 

days

2y 2.96 3.28 56.2 61.5 0.06 -0.21

3y 3.01 3.12 57.5 60.4 0.14 -0.08

Bid to cover End-user demand (%) Tail (bp)

Average Treasury trading volumes by day of the 

week for select on-the-run Treasuries, 2-year 

average; $bn

2y 5y 10y 30y

Monday 16 38 32 8

Tuesday 20 47 39 10

Wednesday 22 53 43 11

Thursday 22 52 44 12

Friday 21 49 40 10

Source: Brokertec

Source: Treasury, J.P. Morgan

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