CONSUMER FINANCIAL PROTECTION BUREAU | NOVEMBER 2020

Debt and delinquency after 

military service

A study of the credit records of young veterans in the first year 

after separation
Table of contents

Table of contents..............................................................................................................2

Executive Summary .........................................................................................................3

Introduction .......................................................................................................................4

Data.....................................................................................................................................6

Credit Scores.....................................................................................................................8

Account Ownership........................................................................................................12

Collections, Delinquency, & Derogatory Outcomes .................................................14

Conclusion.......................................................................................................................19
Executive Summary

This report shows that a sizeable fraction of young enlisted servicemembers go delinquent on 

debt payments or have severe derogatories (for example, defaults)appear on their credit record 

around the time they leave active duty. The report focuses on three types of credit accounts: 

auto loans, revolving credit accounts (credit cards), and personal or retail installment loans. 

The report also analyzes medical and non-medical debt. These types of accounts were found in 

prior research to be the most likely sources of delinquency and default among young 

servicemembers.

The findings show that among those who serve at least seven months, delinquencies and 

defaults are between two and 10 times more likely to appear on a credit record in the six months 

after separation as compared to the six months before.

Late payments are more common among those who served between seven and 35 months—

those who likely reached their first permanent assignment but separated before the end of their 

first contract—compared to those who serve shorter or longer terms. For example, of all 

servicemembers who exit with auto debt after seven to 35 months of service, one-third become 

90 days delinquent or default on that debt within one year. By comparison, less than 15 percent 

of auto debt holders with longer terms of service went delinquent or defaulted within one year 

after separation. For both groups the post-separation rates of delinquencies and defaults for 

revolving account holders and for those with less-common types of installment debt (such as 

personal loans) are even higher than for auto debt.

As a result of these negative outcomes, servicemembers’ credit scores decline just after 

separation, and do not recover for at least one year after leaving the military. The drop is most 

severe for those with tenures between seven and 35 months and for those who exit with a Near 

prime credit score or below, as opposed to a Prime score or better.

The data used in this report cannot explain what causes the observed patterns of delinquency 

and default. Publicly-available statistics suggest medical and less-than-honorable discharges 

are not common enough to explain delinquency and default among young veterans. 

Employment rates and average income of young veterans in the first year after service may 

explain some of the patterns, but ultimately the root causes remain important open questions 

for further study.
Introduction

Poor financial decisions canlower an individual’s credit score and stay on his or her credit 

record for years. For example, an auto, personal, or credit card loan that goes to collections 

stays on for seven years. Similarly, late payments may stay on one’s credit history for equally as 

long, with more damage to one’s credit score the longer the delay in payment and the greater the 

number of accounts with late payments. 1 A lower credit score canin turn affect eligibility for or 

terms of a loan, and other adverse information on a credit record can even affect eligibility for an 

apartment or a job.2

The findings of this report reveal a decrease in credit scores for enlisted servicemembers 

immediately following departure from active-duty military service. This drop coincides with 

increases in delinquencies and defaults, especially for revolving credit. These financial 

difficulties lessen six months after separation, partly because of the earlier account closures; 

however, their credit scores remain lower than they were prior to exiting. 

The report focuses on two main groups of young veterans: those that make it through basic 

training but most likely leave service prior to the end of their first term contract and those that 

likely complete their first term. Policies to address these financial difficulties post-service may 

differ for these two groups given that some do not meet their service obligations, while others

do. The report also includes results for those that serve less than six months in the military and 

thus did not make it to their first duty assignment. However, because these servicemembers do 

not build up much debt during military service they are not a primary focus of the analysis. 

The individuals who have the most financial trouble are those who leave active duty prior to 

completing their first term contract (i.e., before completing three years of service). Their credit 

records decline in the months preceding exit, and they continue to decrease after service. 

Exiting (also called “separation” in military parlance)may occur for many reasons, and the

current data do not indicate why a servicemember separated. It may be that part of the reason is 

because of financial difficulties. If so, helping servicemembers make better financial decisions 

may assist the Service branches in increasing retentionwith potentially large cost-savings.3

 

1

 For th is and more information about the credit reporting sy stem: Consumer Financial Protection Bureau “ Key 

Dim ensions and Processes in the US Credit Reporting System: A Rev iew of How the Nation’s Largest Credit Bureaus 

Ma n age Consumer Data,” (December 2012), available at https://files.consumerfinance.gov /f/201212_cfpb_creditr eporting-white-paper.pdf, hereinafter “Key Dimensions and Pr ocesses...”

2 For in formation on how credit records are used outside of the financial industry, see: TransUnion (2015), “5 Things 

La n dlords Look for When Screening Potential Tenants,” blog post, September 5, available at

h ttps://www.transunion.com/blog/credit-advice/5-things-landlords-look-for-when-screening-potential-tenants; and 

Ex per ian, “Do Em ployers Look at Credit Reports?” blog post, August 6, 20 available at

h ttps://www.experian.com/blogs/ask-experian/do-employers-look-at-credit-reports/. 3

 The GAO reports that between 2005 and 2015 the average cost to recruit, screen, and train a new enlistee was 

$75,000. In approximately the same time period, between 19 and 30 percent of enlistees separated within three 

years, depending on the service branch. See: Government Accountability Office, “Improvements Needed in the 

Management of Enlistees’ Medical Early Separation and Enlistment Information,” (July 2017), available at

https://www.gao.gov/assets/690/685843.pdf; and James V. Ma rrone, Predicting 36-Month Attrition in the U.S. 

Military: A Com parison Across Service Branches, Santa Mon ica, CA: Rand Corporation Report RR-4258-OSD 

(2 020), hereafter Predicting 36-Month Attrition.
Even for those servicemembers who mostlikely completed their service contracts, the report 

reveals that credit scores also fall in the two quarters after leaving. In fact, across all groups, 

regardless of length of service, the two quarters after separation appear to be a critical time in 

which servicemember borrowers fall delinquent on payments and sustainsevere derogatories 

such as repossessions, charge-offs, and debt being sent to collections.

This report is a follow-on to our Financially Fit research report that was an extensive study of 

the credit histories of young servicemembers as they join the military compared to similar aged 

civilians.4 That study highlighted some key patterns explored more in depth in this report:

namely, that servicemembers who join by age 21 have more trouble with debt than older 

servicemembers or civilians; that most debt problems are associated with auto loans, revolving 

credit accounts, and personal loans; and that severe debt problems appear to arise around the 

time servicemembers leave active duty. This report provides a more detailed analysis of these 

particular patterns andverifies the timing of severe derogatory outcomes with respect to the 

date of exit from active duty. This more precise analysis is made possible as a result of the 

omissionof civilians from the sample and the use of a quarterly panel of credit report 

information, rather than annual. 

 

4 Con sumer Financial Protection Bureau, “Financially Fit? Comparing the credit records of young servicemembers 

and civilians,” (2020), available athttps://www.consumerfinance.gov/data-research/research-reports/financially-fitcomparing-credit-records-young-servicemembers-civilians/, hereinafter “Financially Fit?”
Data

The analysis in this report utilizes data from the Consumer Financial Protection Bureau’s 

(CFPB) Consumer Credit Panel (CCP), a de-identified, nationally-representative panel of credit 

records. The data consist of a 1-in-48 random sample of credit files provided by one of the three 

nationwide consumer reporting agencies (NCRA). 5 The credit agency matchedindividuals in 

the CCP to the Servicemembers Civil Relief Act (SCRA) Website maintained by the U.S. 

Department of Defense (DoD).6 The website provides the dates of active duty service along with 

the service component and service branch. The credit agency furnishedthe CFPB with active 

duty service information for people who served since December 2007. This information was 

then merged to the quarterly CCP panel to determine the active duty or veteran status of each 

person at each point in time, up to December 2018. 7

This analysis includes quarterly credit record information for each individual in the merged 

CCP/SCRA panelwho met three characteristics: they entered full-time active duty by the age of

21, they were observed at the time their service began, andthey left active duty at least one year 

prior to the end of the observation window.8 The age cutoff was chosento focus on the group

that was previously identifiedto have the most vulnerability to debt problems – those who enter 

service at a young age. Although the data provide no information on paygrade, entrants under 

age 21 are virtually all enlistees, and they account for the majority of enlisted accessions.9

The sample comprises 10,872 servicemembers. The plurality (40 percent) served in the Army,

with 14, 20, and 24 percent respectively in the Air Force, Navy, and Marine Corps. One percent 

of the sample served inthe Coast Guard. By construction, everyone enteredactive duty by age 

21, but there is wide variation in age at separation: from 17 years old for those who enter at the 

youngest age and serve for a very short time, to 32 for those who serve for nearly the entire 

observation window. 

The analysis splits servicemembers into groups based on how long they had served at the time of 

separation. Those in the shortest-tenure group separated within six months and were unlikely 

to ever reach their first permanent assignment (1,751 people). Contract length is unobservable 

in the data, but the majority of servicemembers have contracts that are at least three years long. 

Servicemembers who stay for at least six months but separate within 35 monthswere thus 

unlikely to have completed their first contract. 1 0 Around two thousand (2,219) people are in 

this group. Servicememberswho complete at least 36 months of active duty are more likely to

 

5 For m ore information about servicemembers in the CCP and the construction of the panel u sed h ere and in prior 

r esearch, see “Financially Fit?” Appendix B.

6 Depa r tment of Defense (2019), “ Servicemembers Civil Relief Act (SCRA) Website,” available at h ttps://scraw .dmdc.osd.mil/scra/#/home. 7 Beca use new credit a ccounts are sometimes reported to the NCRA at a lag, a cutoff of December 2018 allowed for 

cr edit accounts to be identified retrospectively based on information through December 2019.

8 A t a ges for which a consumer has no credit record, they were a ssumed to have zero a ctive accounts and zero 

ba lances. In this way servicemembers can be “ observed” during periods of a ctive duty prior to their establishing a 

cr edit record.

9 See “ Financially Fit?” page 25 and footnote 29.

10 A sm all fraction of servicemembers may have two-y ear contracts; see “Financially Fit?” footnote 51.
be leaving at or after the end of their first contracts. Just under seven thousand (6,857) people 

are in this group. 

The choice of sample maximizes the analytic sample size relative to the core question of what 

happens to credit profiles at the end of active duty. This allows for greater statistical power and 

precision in estimates compared to the prior study that used a sampling window based on age 

and birthyear. It is important to note that unlike the sample used in the prior report, this

sample is not representative. The merged CCP/SCRA panel lists military service history only 

between 2007 and 2018, and individuals are sampled by the CCP only if they have a credit 

history. 1 1 Both of these facts imply thatthose who entered and separated during the observation 

window would not be a random set of all servicemembers who entered prior to age 21 and ever 

served during that time. 1 2 Instead, the population consists of all servicemembers who entered 

and separatedduring this time period and had a credit recordby the time they separated. 

The report focuses on the following credit outcomes: credit scores, third-party collections debt, 

90-day delinquencies, and severe derogatory outcomes. Third-party collections are divided into 

medical and non-medical collections. Delinquencies and derogatories are analyzed for auto 

loans, revolving credit accounts (general credit cards and retail credit cards), and “other” 

installment debt grouped together. The study does not include mortgages and student loans, as 

these are used less often for this population. 1 3

“Other” installment debt includes several types of loans. Eighty percent of these are personal 

loans, 10 percent are retail installment loans, 10 percent are of an unknown type, and only a 

negligible fraction are of other known types. Of the personal loans, 90 percent are unsecured 

and 10 percent are loan notes from banks or credit unions. Of the retail installment loans, the 

main types of retailers are jewelers (40 percent), sales financing companies (27 percent), 

department/variety stores (12 percent), and home furnishing stores (five percent). Of the

unknown types of loans, 92 percent are secured and 97 percent are from banks or credit unions.

Severe derogatory actions refer to any of the following: repossession, surrender, charge-off, 

collections, foreclosure, or discharge in bankruptcy court. For the products and population 

analyzed here, repossession, surrender, charge-off, and collections are by far the most common 

types of severe derogatory actions.1 4 

The analysis proceeds first by analyzing changes in credit scores around the time of separation.

Then, the report showshow account ownership grows over the course of military service and 

declines shortly thereafter. The last sectionof analysisdescribes the rate of delinquencies and 

severe derogatories just prior to and just after separation. It shows how severe derogatories 

explain much of the decline in account ownership and decrease in credit scores following 

separation.

 

11 In div iduals without a credit record are called credit invisible. Prior CFPB r esearch estimates the fraction of the 

popu lation that is invisible. Calculations in “Financially Fit” suggest that the fraction of y oung servicemembers who 

a r e invisible is n o higher than for civilians of the same age. See: CFPB, CFPB, “Credit Invisibles,” (May 2015), at 10, 

available at https://files.consumerfinance.gov /f/201505_cfpb_data-point-credit-invisibles.pdf. 12 Th e r esearchers confirmed that the r esults show the same patterns when the analysis is limited the analysis to the 

sm aller but r epresentative sample of u nder-21 year-old entrants studied in the earlier report.

13 For in formation a bout mortgages and student loans in this population, see “ Financially Fit?” 14 Wh en a credit account is sent to a third-party collections agency, that debt will be counted in this analysis a s both a 

sev ere derogatory for the original type of a ccount, a s well a s third-party n on-medical debt. Financial debt is a 

m inority of a ll third-party collections debt, which a lso includes debt from residential leases, utility accounts, phone or 

ca ble bills, and a v ariety of other non-credit expenses.
Credit Scores

The analysis beginsby examining credit scores of servicemembers prior to and after leaving 

service. Although not a perfect measure of creditworthiness, credit scores take into 

consideration variables such as debt levels, debt usage, length of credit history, and payment 

history (delinquencies, collections, and bankruptcies).1 5 Consumers with higher credit scores 

are considered to be more reliable borrowerswith a lower probability of default. 

Credit agencies and lenders often group credit scores into tiers based on credit riskiness. Those 

that have a credit score below 580 are considered Deep subprime. Those with a credit score 

between 580 to 619 are Subprime, those between 620 and 659 are Near prime, those between 

660 and 719 are Prime, and those with scores above 720 are considered Superprime. 

By the time of separation, 82 percent of servicemembers in the sample have a credit score. The 

likelihood of having a credit score, as well as the average credit score, varies by the length of 

service, as shown in Table 1. The longer they serve, the more likely servicemembers are to have 

a credit score at the time they exit. Those who stay in for at least three years have higher credit 

scores than those who leave earlier. Servicemembers who exit with between sevenand 35 

months of service have, on average, Subprime scores, and those who serve 36 months or more 

exit, on average, with Near prime scores.

TABLE 1: CREDIT SCORES AT TIME OF EXIT FROM ACTIVE DUTY, BY MONTHS SERVED

Time spent in 

active duty service

Percent with 

credit score at 

time of exit

Average 

credit score, 

if scored

Tier for average 

credit score

0-6 months 41% 627 Near prime

7-35 months 81% 607 Subprime

36 months or more 92% 654 Near prime

Sou rce: Author calculations from CFPB’s CCP merged to DoD’s SCRA database.

To examine how individual borrowers’ credit information changes over time and to take 

advantage of the panel nature of the data, the first analysis uses a fixed-effect regression atthe 

individual level. The advantage of a fixed-effect regression is that it controls for individual-level, 

time-invariant characteristics such as race, gender, hometown, birth year, and initial wealth 

levels, which are unobserved in the CCP data but may affect credit scores. The regressions then 

measure within-person changes in credit score around the time of exit from active duty. 

Equation 1 gives the regression specification.

YYiiii = ααii + ∑ ββqq ⋅ {QQQQQQQQQQQQQQ ssssssss ee = qq} 4

qq=−2 + YY + εεiiii (1)

YYiiii is credit score for individual i at observation number t. The variable ααii represents an 

individual-level fixed effect which controls for the characteristics about the individual that do 

not change over time. The dummy variablesQQQQQQQQQQQQQQ ssssssss ee indicate the timing of each 

 

15 Con sumer Financial Protection Bureau, “You have many different credit scores,” available at

h ttps://files.consumerfinance.gov/f/documents/201702_cfpb_credit-score-explainer.pdf. 
observation relative to the date of exit, from two quarters prior to exit to four quarters after exit. 

YY represents a dummy variable for the year of observation, which helps control for 

macroeconomic factors which may be affecting credit score in that year for all individuals. A 

separate regression is calculated for eachtenure group listed in Table 1, restricted to 

servicemembers who have a credit score at least two quarters prior to exit to ensure a balanced 

panel. 

The coefficients on quarter relative to exit (ββqq) are plotted in Figure 1. The omitted quarter is 

the quarter of exit (q=0). ββqq can then be interpreted as the credit score in a particular quarter 

relative to the quarter of separation. Positive coefficients mean that, on average, credit scores 

are greaterin that quarter relative to the quarter of separation and negative coefficients indicate 

credit score is lowerin that quarter. As the figure shows, credit scores are falling for two 

quarters prior to separation. They continue to fall after separation, with the largest drop in the 

two quarters after separation. 

FIGURE 1: CREDIT SCORE RELATIVE TO QUARTER OF SEPARATION, BY TIME SPENT IN ACTIVE DUTY

Sou rce: Author calculations from CFPB’s CCP merged to DoD’s SCRA database. See text for details on sampling 

str ategy. The graph plots coefficients from the regression specification in Equation 1, run separately by time spent in 

a ctive duty. 

The biggest downward trends throughout the time periodare for those who serve between seven 

and 35 months, for whom credit scores drop by an average of 15 points in the two quarters prior 

-50

-40

-30

-20

-10

0

10

20

-2 -1 0 1 2 3 4

Credit Score Relative to Quarter of Separation

Quarters since separation from active duty

0-6 months served 7-35 months served 36 months served or more
to separation and an additional 36 points in the two quarters after separation. The average 

score in this group moves from Subprime to Deep subprime. 

For those who spent at least three years in the military, credit scores were fairly steady prior to 

exiting the service, dropping by just 5 points on average in the two quarters prior to separation. 

However, by fourquarters after separation credit scores had dropped by 21 points. The largest 

drop was again within the first two quarters of separation. 

Comparing transitions betweencredit tiers in the six months after separationshows that the 

decreases in Figure 1 occur across all tiers, and dropping to a lower tier is more common than 

moving up to a higher tier. In the sample as a whole 23 percent of servicemembers moved down 

to a lower score tier within six months of separation, compared to 12 percentthat moved up. 

Those with Near prime or Subprime scores were more likely to have downwardmovements: 40 

and 47 percent, respectively, drop down to a lower tier. Ninety percent of those who were Deep 

subprime at the time of separation were still Deep subprime six months later. 

Table 2 disaggregates the transitions based on time spent in active duty. Panel A shows the 

transitions for those who serve between seven and 35 months, and Panel B shows the transitions 

for those who serve at least 36 months. A comparison of the two panels shows that conditional 

on a servicemember’s credit score tier a decrease was more likely if they served less than 36 

months. For example, among those with Subprime scores at the time of exit, 62 percent who 

served less than 36 months were Deep subprime six months later, compared to 44 percent who 

served at least 36 months. Further, among those with a Superprime score at the time of exit, 58 

percent of those with less than 36 months of service were still Superprime six months later, 

compared with 79 percent of those with at least 36 months of service. 
TABLE 2: TRANSITIONS BETWEEN CREDIT SCORE TIERS IN TWO QUARTERS AFTER EXIT

PANEL A: 7-35 MONTHS SERVED

Credit score tier two quarters after exit

Credit score tier

in quarter of exit Deep subprime Subprime Near prime Prime Superprime

Superprime 7% 5% 6% 24% 58%

Prime 23% 8% 14% 41% 15%

Near prime 39% 9% 29% 19% 3%

Subprime 62% 23% 14% 0% 0%

Deep subprime 93% 6% 1% 0% 0%

PANEL B: 36 MONTHS SERVED OR MORE

Credit score tier two quarters after exit

Credit score tier

in quarter of exit Deep subprime Subprime Near prime Prime Superprime

Superprime 1% 1% 2% 16% 79%

Prime 7% 5% 13% 58% 17%

Near prime 22% 18% 39% 19% 2%

Subprime 44% 33% 19% 3% 1%

Deep subprime 88% 10% 2% 0% 0%

Sou rce: Author calculations from CFPB’s CCP merged to DoD’s SCRA database.
Account Ownership

The analysis above reveals that regardless of tenure length, some servicemembers experience

financial issues after leaving service. To begin understandinghow this relates to credit product 

usage, this section examines the probability of having particular types of accounts at the time of 

entry, just before exit, and one year after exit. Figure 2 plots the fraction of servicemembers

with auto debt, revolving credit accounts (mostly general-purpose and retail credit cards), and 

other installment debt at each point in time.

FIGURE 2: ACCOUNT OWNERSHIP AT VARIOUS POINTS OF ACTIVE DUTY SERVICE, BY LENGTH OF 

SERVICE

Sou rce: Author calculations from CFPB’s CCP merged to the DoD SCRA database. Other installment debt includes: 

per sonal loan, r etail installment loan, home equity loan, business installment loan, agricultural, commercial, or 

u n specified debt. 

Six percent or less of any tenure group had auto loan debt when entering service; around 25 

percent had revolving credit accounts; and only three percent or less of each grouphad other 

installment debt prior to service. 

By the time of separation, servicemembers who leave within two quarters tended not to have 

openednew accounts. But for those who serve longer, a significant number have opened some 

sort of account. “Financially Fit?” shows that servicemembers take on auto debt around a year 

0

10

20

30

40

50

60

70

80

90

0-6

months

served

7-35

months

served

36 months

served or

more

0-6

months

served

7-35

months

served

36 months

served or

more

0-6

months

served

7-35

months

served

36 months

served or

more

Auto Loan Revolving Account Other Installment

Percent of sample

Quarter of Entry Quarter of Exit 4 Quarters After Exit
after they join and that the fraction with an auto loan continues to rise during service.1 6 Figure 2 

shows that at the time of exit, over one-third of servicemembers who served at least seven 

months have an auto loan (and over half of those who served at least three years). Even more 

have revolving accounts: almost two-thirds of those who serve between seven and 35 months, 

and over 80 percent of those who serve at least three yearshave revolving accounts. Over onequarter of both groups have other installment debt. 

In the four quarters after leaving service people tend to close these accounts. The net decrease in 

account ownership is particularly true of those who serve between seven and 35 months. Over 

half of those servicemembers who exited with other installment debt close those accounts within 

a year, and about one-third of those with revolving accounts close them in the same period. The 

decline in account ownership is smaller among those who spent more than three years in 

service. Only the group that serves six months or less has an opposite pattern, with these 

servicemembers having a netincrease in account ownership after separation rather than a 

decrease. 

Account closures are not necessarily a bad sign. They may be a sign that new veterans no longer 

need the same types of loans or credit that they required during active duty, and if accounts are 

closed by paying off a loan or credit card balance then it would be a sign that borrowers are 

managing their debt well. Closing an account due to default, however, can have serious 

implications for young veterans’ credit scores. The next section shows that a substantial fraction 

of accounts are closed through charge-offs, repossessions and surrenders, or because the debt is 

sent to collections. These constitute severe derogatory actions that help explain the declines in 

credit score highlightedin Figure 1. 

 

16 See “ Financially Fit?” Figures 5 and 8.
Collections, Delinquency, & 

Derogatory Outcomes

At the time of entry, few servicemembers had delinquencies or derogatories on their credit 

records, partly because most barely had any credit history at all. In total, only 8 percent of the 

sample had any delinquency, default, or third-party collections account. Most often, people had 

some non-medical debt in collections, such as a telecommunicationsbill or utility bill (around 6 

percent of the sample). About 3 percent had medical debt in collections, and barely 1 percent 

had been 120 days delinquent on a revolving account. Therefore, these servicemembers 

typically didnot appear to be saddled with poor credit histories at the time they joinedthe 

military.

Even if they didnot have a credit history when they enter the military, Figure 1 showed that 

most servicemembers had opened at least a revolving account by the time they exit. They may 

also have opened other accounts, such as for cellphones or utilities, that constitute further 

payment obligations and which could go to collections if the servicemember falls behind on 

payments. To observe if and when delinquencies or defaults occur, this sectioncompares three 

periods in time: the two quarters prior to exit, the two quarters following exit, and the third and

fourth quarter following exit. The quarter of separation is excludedbecause the timing of debt 

relative to the precise date of separationcannot be determined. 

First, Figure 3 shows the fraction of servicemembers with a third-party collections account in 

each of these time periods. The calculations reflect all third-party collections accounts that are 

open at the time, so the debt must have been incurred some time before and the account could 

remain open for several months or years until the debt is discharged. Changes between time 

periods in Figure 3 show whether servicemembers have a net increase or decrease in open 

collections accounts. 

The figure reveals that during service, some servicemembers have had non-medical debt enter 

collections. At the time of entry, about 3 percent had such debt in collections. Among those 

who serve at least seven months, over 15 percent have some such debt just prior to separation. 

(In contrast, the fraction with medical debtjust prior to separationis approximately the same as 

at the time of entry.) 

After separation, the rates of non-medical collections debt go even higher. This is particularly 

true among those who servedbetween seven and 35 months,for whom there is a net increase in 

non-medical collections account of 11percentage points (on a base of 17 percent) in the six 

months after separation. Around 40 percent of these non-medical debt accounts are from a 

telecommunications account; another 15 percent are from a utility account; 15 percent from a 

residential lease; and about 10 percent from a retailer.
FIGURE 3: COLLECTIONS DEBT AROUND THE TIME OF SEPARATION FROM ACTIVE DUTY

Sou rce: Author calculations from CFPB’s CCP merged to the DoD SCRA database. 

Medical debt collections increase, as well, but not until three or four quarters after separation. 

Again, this is most significant for those who served less than three years, for whom the fraction 

with medical debt collections nearly doubles. It is not possible to determine from the data if this 

debt was incurred prior to, during, or after service, or whether the debt is due to injuries or 

conditions developed during service. Moreover, it is not clear whether those with medical debt 

in collections were eligible for or made use of veterans health benefits. 

Figure 4 shows 90-day delinquencies on credit accountsbefore versus after separating from 

military service. The calculations include all servicemembers, not just those who have accounts. 

The graphs show time-period-specific outcomes: the fraction of the sample that was currently 

delinquent in the respective time period. 

Two patterns are consistent across all account types: delinquencies are more common after 

separation than before, and they rise by substantially more for those who serve between seven 

and 35 months than for those who serve at least 36. Notably, in the six months before 

separation delinquency rates are fairly similar for both groups. 

For those who exit within seven to 35 months, the figure shows 7.2 percent are 90 days behind 

on auto loan payments, 21 percent are late on revolving debt, and 19 percent are late on other 

installment debt. These represent four- or five-fold increases compared to the six months prior 

to separation. In the third and fourth quarter after separation, delinquency ratesdecrease by 

about half but remain higher than prior to separation.

0

5

10

15

20

25

30

35

40

0-6 months

served

7-35 months

served

36 months

served or more

0-6 months

served

7-35 months

served

36 months

served or more

Medical

 collections

debt

Non-medical

collections

debt

Percentage of the Population

2 Qtrs. Prior to Exit 2 Qtrs. Post-Exit 3&4 Qtrs. Post-Exit
For those who serve at least 36 months, delinquency rates across account types are: 4 percent 

(auto), 13 percent (revolving), and 7 percent (other installment) in the six months after 

separation. These are smaller fractions than for the shorter-tenure group, but are still roughly 

four times as large as the delinquency rates in the six months prior to separation. The 

delinquency rates fall slightly in the next six months, remaining lower than among those who 

servedbetween seven and 35 months. 

FIGURE 4: 90-DAY DELINQUENCY RATES AROUND TIME OF SEPARATION FROM ACTIVE DUTY

Sou rce: Author calculations from CFPB’s CCP merged to the DoD SCRA database.

Figure 5 shows the fraction of individuals having a new severe derogatory or default appear on 

their credit report in each time period. As a reminder, a severe derogatory action is any of the 

following: repossession, surrender, foreclosure, charge-off, collections, or discharge in 

bankruptcy court. In any of these instances, the individual is losing possession of property or 

having their account closed with negative repercussions on his or her credit record.

As was true of delinquencies, those who leave within seven to 35 months are more likely to have 

a severe derogatory than are those who serve at least 36 months. For both groups, severe 

derogatories appear on credit records most often in the six months after separation. Among

those who served seven to 35 months, 6 percent default on an auto loan, 8.6 percent default on a 

revolving account, and 10.9 percent default on other installment debt in the six months after 

separation. These are between four and ten times the rates observed in the six months prior to 

0.00

5.00

10.00

15.00

20.00

25.00

0-6

months

served

7-35

months

served

36 months

served or

more

0-6

months

served

7-35

months

served

36 months

served or

more

0-6

months

served

7-35

months

served

36 months

served or

more

Auto Loan Revolving Account Other Installment

Percent of sample

2 Qtrs. Prior to Exit 2 Qtrs. Post-Exit 3&4 Qtrs. Post-Exit
separation. By comparison, the rates among those with longer tenures are 2.8, 6.8, and 3.8 

percent, between two and seven times the rates in the six months prior to separation.

FIGURE 5: FRACTION OF SERVICEMEMBERS WITH NEW SEVERE DEROGATORIES AROUND TIME OF 

SEPARATION FROM ACTIVE DUTY

Sou rce: Author calculations from CFPB’s CCP merged to the DoD SCRA database. 

Some of the delinquent accounts in one period could turninto defaults the next. Combining all 

delinquencies and defaults within the first year of separation, debt repayment issues are still 

more common among those who serve seven to 35 months. For example, 13 percent of the 

sevento 35-monthgroup are delinquent and/or have defaultedon auto debt within one year of 

separation, compared to 9 percent of those with longer tenures.

Conditioning on those who actually have an account at the time of separation (Figure 2), it is 

particularly likely that those with other installment loans will have trouble paying off that debt. 

Looking at the fraction of accountholderswith either a delinquency ordefault within one year

of separation, the numbers for those who serve seven to 35 months are as follows: 34 percent 

(auto loans), 38 percent (revolving accounts), and 64 percent (other installment accounts). For 

those who serve longer, the numbers are: 33 percent (auto loans), 21 percent (revolving 

accounts), and 33 percent (other installment accounts).

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0-6

months

served

7-35

months

served

36 months

served or

more

0-6

months

served

7-35

months

served

36 months

served or

more

0-6

months

served

7-35

months

served

36 months

served or

more

Auto Loan Revolving Account Other Installment

Percent of sample

2 Qtrs. Prior to Exit 2 Qtrs. Post-Exit 3&4 Qtrs. Post-Exit
Further, the increase in defaults immediately after separation are not due to an overall increase 

in account closures; rather, defaults constitute an increasing fraction of all account closures. 

Consider account closure rates: in the two quarters prior to separation, between six and seven

percent of all open accounts were closed. In the two quarters following separation, a similar 

fraction (seven percent)of open accounts were closed, and in the third and fourth quarter after 

separationsix percent of still-open accounts were closed. 

Now, consider the reasons for account closures. In the two quarters prior to separation, 74

percent of closures were because accountswere fully paid. Less than 10 percent of closureswere 

due to a severe derogatory action. The remainder were for a variety of other reasons, such as 

havingbeen transferred to another serviceror closed due a lost credit card. In the two quarters 

after separation, severe derogatories account for 25 to 30 percent of account closures, depending 

on the type of account(20 percent are due to chargeoffs alone). In the third and fourth quarters 

after separation, the fraction associated with a severe derogatory is only slightly lower, between 

20 and 25 percent.

Together these observations show that defaults increase both in absolute and relative terms 

soon after servicemembers leave active duty.
Conclusion

This report shows that a sizeable fraction of young enlisted servicemembers go delinquent on 

debt or have severe derogatory marks appear on their credit record around the time they leave 

active duty. These problems are most likely to arise in the six months following separation, 

compared to the six months before separation. Problems are also more likely to arise among 

servicemembers who left the military between seven and 35 months of service—those who likely 

reached their first permanent assignment but separated before the end of their first contract.

Servicemembers are particularly likely to default on a personal, retail, or other type of 

installment loan, if they have one at the time of separation. Because such loans are associated 

with a variety of different purposes and types of businesses, it is difficult to discern clear 

patterns for this type of debt. Further research could helpto better understand why 

servicemembers acquire such debt and whether those with these loans tend to be particularly 

credit-constrained.

Income and employment are unobserved factors that likely drive some of the patterns observed 

here. A servicemember with over three years of experience in 2015 made around $25,000 per 

year in base pay. On top of that, he or she either lived in the barracks or received money to 

cover monthly expenses, plus healthcare was covered and $4,400 per year was provided to cover 

meals. Altogether, but not including health care, a servicemember with over three years of 

experience made the equivalent of at least $35,000.1 7

Recently-released data from the U.S. Census Bureau show that across the years analyzed here, 

veteranswith zero to five years of service earneda median income of roughly $30,000 in the 

first year after separation. 1 8 For those who separate before the age of 25, the median is even 

lower, and for those who separate at paygrade E-3 or less, it is lower still. These statistics 

suggest that at least some young veterans may experience a significant drop in income in the 

year after separation. 

Further, these median incomes post-service are based on the sample of veteranswho are 

employed and does not include those without jobs. The Congressional Budget Office estimates 

that around 92 percent of male veterans ages 22 to 24 were in the labor force, and of those in the 

labor force, just under 15 percent were unemployed between 2008 and 2015. For those aged 25 

to 34, the average labor force participation rate was94.5 percent and the average unemployment 

rate was 8.2 percent. 1 9 These rates likely varied with the macroeconomy, as around half of all 

 

17 A n E4 with ov er three years of service made $2,238 per month in base pay, and an E3 made $2,055.30 per month. 

Mon th ly Ba sic A llowance for Subsistence for all enlisted servicemembers was $367. Housing pay was at least $540 

per month. All numbers came from Defense Finance and Accounting Service, Basic Pay – Effective January 1, 2015, 

available at https://www.dfas.mil/Portals/98/2015MilitaryPayChart_2.pdf. 18 Ca lculations come from the U.S. Census Bureau, Longitudinal Employer-Household Dy namics, Veterans 

Em ployment Outcomes Ex plorer, available at https://lehd.ces.census.gov /applications/v eo/occupation/detail/. 

Ca lculations were based on all information available, i.e. n ot limited to particular years of service. Separate 

ca lculations were performed based on years of service, age at exit, and paygrade at exit, without conditioning on other 

ch aracteristics.

19 Con g ressional Budget Office, Labor Force Experience of Recent Veterans (May 2017), available at 

h ttps://www.cbo.gov/sy stem/files/115th-congress-2017-2018/reports/52418-laborforceveterans_0.pdf. For women

th e labor force participation rate was 75 and 76 for the two groups, respectively, a nd the unemploy ment rate was 15% 

a n d 10%.
active-duty servicemembers in the Army applied for unemployment insurance when leaving the 

Army in 2013, signaling that they did not have a job lined up; however, usage and duration of 

unemployment benefits fell significantly in the following years.20 

The reason for separation could be an additional unobserved factor behind defaults. 

Servicemembers leaving due to disability may face greater challenges on the civilian labor 

market and may therefore also have more trouble managing existing debt. Yet discharges due to 

disability are unlikely to explain the differences observed by time in service. Recent analyses 

show that medical discharges constitute the same share of separationsduring the first four years 

of service as in the next four years.21 Moreover, the number of medical discharges is too small to 

explain the number of delinquencies and defaults. Between 2002 and 2011, less than 4 percent 

of servicemembers in any service branch had a medical discharge in the first four years of 

service (and in most years it was around 1 percent). By comparison, 36-month attrition (for any 

reason) averaged at least 18 percent across all service branches.22 

Finally, servicemembers with less-than-honorable discharges may be unable to access veterans’ 

benefits and may also be more likely to have difficulty on the civilian labor market.23 Still, such 

discharges are too few to account for the fraction of delinquencies and defaults. For example, 

the Department of Defense reported that 9 percent of all 207,000 discharges in 2014 were lessthan-honorable, with 2 percent being Other Than Honorable. Only a few hundred were Bad 

Conduct or dishonorable discharges.24

The data for this report cannot connect credit outcomes with employment, so it is unclear 

whether those who were struggling with debt are also the ones without a job or with lower levels 

of income. To identify the proper policy response to young veterans struggling with debt, it 

would be criticalto understand the connection between delinquency and employment and 

whether they are in turn connected to veterans’ service histories.

 

20 Con g ressional Budget Office, Transitioning from the Military to the Civilian Workforce: The Role of 

Unem ployment Compensation for Ex-Servicemembers (2017) available at https://www.cbo.gov /sy stem/files/115thcon gress-2017-2018/reports/52503-transitionreport.pdf. 21 Com pare Figures 3.4 and 3.5 in Heather Krull, Philip Armour, Kathryn Edwards, Kristin Van A bel, Linda Cottrell, 

a n d Gulrez Shah Azhar, The Relationship Between Disability Evaluation and Accession Medical Standards, Santa 

Mon ica, CA: RAND Corporation Report RR-2429-OSD (2019).

22 Com pare Figure 3.4 in Krull, et al. (2019) to Table 2.2 of Predicting 36-Month Attrition. 23 Among less-than-honorable discharges, a general discharge under honorable conditions will still retain eligibility 

for veterans benefits. Other discharge categories may not. Further, military unemployment compensation is only 

available for discharges under honorable conditions. For the different types of discharges, see: 

MilitaryBenefits.info, “Types of Military Discharges” (undated), available at https://militarybenefits.info/types-ofmilitary-discharges-2/. For veterans benefits rules, see: Veterans Benefits Administration, “Applying for Benefits 

and Your Character of Discharge” (May 19, 2015), available at 

https://www.benefits.va.gov/benefits/character_of_discharge.asp. For unemployment compensation rules, see: 

Department of Defense, “Military Compensation: Unemployment Compensation (UCX)” (undated), available at

https://militarypay.defense.gov/Benefits/Unemployment-Compensation/. 24 Th e r emaining 7 percent of less-than-honorable discharges were general discharges under honorable conditions, 

w h ich may pose fewer barriers to accessing benefits or employment, a s noted in the previous footnote.