What Do We Know About Student Loans? Less Than You Think

Students walk on their university campus in July 2013, New York, NY.

Despite the fact that nearly 1 of every 5 American adults is saddled with student loan debt—a total of $1.5 trillion—little is known about the various, often-treacherous paths borrowers take as they navigate repayment. The landscape remains such a mystery because there are limited public data on student loans.

This lack of transparency may seem impossible to fathom, particularly because headlines about student loans have become ubiquitous in recent years. But much of the information available to researchers, policymakers, and the public comes from cobbled-together data from surveys, colleges, nonprofits, and credit bureaus, which provide snapshots of borrower experiences rather than the full story. As a consequence, the public is largely in the dark about what student loan repayment looks like for millions of Americans.

Little is known about how borrowers move through higher education and in and out of repayment. Are students more likely to default when they attend multiple schools? How soon after entering repayment do borrowers change repayment plans? Do borrowers who default churn through delinquency after delinquency, or do they take a straight shot to default?

These questions cannot be answered with public data. Lacking these data not only stymies collective understanding of student loan debt, but it also allows for inaccurate narratives such as the assumption that high-debt borrowers are the ones who are in the most trouble. This could cause students to make poorly informed decisions about borrowing and policymakers to propose ineffective reforms.

The Department of Education could fix this situation—and fairly simply. The department’s Office of Federal Student Aid (FSA) holds more than 56 billion records on federal student loans in the National Student Loan Data System (NSLDS). Although researchers occasionally use limited NSLDS data to provide insight into the federal student loan portfolio, the data are never used to chart students’ paths through repayment, even though all of the necessary information is stored within the system. FSA could release NSLDS data without much effort but seems to lack the will do to so. Ultimately, it may take congressional action to force the regular publication of student-level data that can help everyone understand the state of federal loan repayment and what’s at stake if things don’t change.

Why are student loan data so poor?

The systems that house student aid data were built in a different time, before the expansion of federal education lending. As federal programs were created, new data systems sprung up, forming a network of administrative data systems that house billions of records of aid data on millions of students, some of which date back more than 30 years.

In the meantime, other datasets were culled together in order to answer policy-relevant questions. But these data suffer from three shortfalls: 1) They almost always report highly aggregated findings rather than offer data about individual borrowers. As a result, it is impossible to understand how, for example, low-income students’ repayment experiences differ from high-income students’; 2) Most of the more detailed data are published infrequently, meaning the most current available information is almost always out of date; and 3) Data on student loans are nearly always static and viewed at a single point in time. They can’t be used to understand, for example, the paths student borrowers take from leaving school to full repayment of their loans.

Borrowers are in trouble when policymakers are left to fly blind

With such poor publicly available student loan data, policymakers are more likely to base their proposals off anecdotal observations or conventional wisdom as opposed to research. There are significant problems with student loan repayment that currently available data do not address. Below are just three of the many areas of student loan borrowing and repayment where making NSLDS data available would be invaluable to policymakers looking for ways to improve borrowers’ repayment processes.

Information on who uses income-driven repayment plans, their monthly payments, and their incomes

  • What we know: The FSA Data Center publishes information on how many borrowers use income-driven repayment (IDR) plans, which allow borrowers to pay a certain share of their income every month toward their student loan balances.
  • What we don’t know: The published data say nothing about how long borrowers stay in these plans, the balances of borrowers in these plans, the default rates of borrowers who use these plans, the amount that borrowers in these plans pay on a monthly basis, and the incomes of those who use the plans. There are also no demographic data on borrowers who participate in IDR plans.
  • Why it matters: There is significant interest in reducing the number of IDR plans, as there are several options available to borrowers, and it is unclear which plans work best for borrowers in distress. But the lack of data on who uses them and for how long makes it difficult to determine who reforms would benefit and harm the most.

Data on borrowers who default, such as the number of payments they make and postponements they use

  • What we know: Recently released data show that 27 percent of borrowers who started college in 2004 defaulted within 12 years of entering repayment. A majority of these borrowers did not complete a degree or earn a certificate. The majority were also enrolled in a community or for-profit college. The data also show that African American borrowers, in particular, have high default rates, even when they earn bachelor’s degrees.
  • What we don’t know: Little is known about the paths borrowers take to default. Available data do not provide information on how many payments borrowers make or how many deferments or forbearances they use before defaulting. It is also unclear how many borrowers cycle through periods of delinquency and never default, and the data available provide no insight into default rates for current loan servicers.
  • Why it matters: Policymakers can’t expect to improve repayment processes for student loan borrowers if they are operating on best guesses or worse, baseless assumptions as to why borrowers do not repay their debt. A better understanding of how borrowers move through repayment, including in and out of default, could indicate how best to smooth out stumbling points for vulnerable students.

Insight into paths through repayment, including how long it takes for borrowers to repay their loans

  • What we know: The standard repayment plan, which provides borrowers with a fixed monthly payment over a 10-year term, is the most common path toward repayment. Full repayment, however, likely takes longer than that, as 70 percent of borrowers use a deferment or forbearance at some point during the repayment process.
  • What we don’t know: Available data do not show how long it takes borrowers to fully repay their loans. Re-enrollment, default, postponements, delinquencies, and opting into other repayment plans can all cause borrowers to pay for a longer period of time, but it is unclear how long these occurrences prolong repayment, how often borrowers experience each of them, and how much more they pay in the long run.
  • Why it matters: With more and better information on repayment trajectories, policymakers could better understand how well various repayment tools serve borrowers’ circumstances and if there are appropriate options for all types of borrowers. Furthermore, it would allow policymakers to better understand if current and proposed accountability measures—such as cohort default rates and repayment rates—are worthwhile benchmarks.

FSA already has better data, but a congressional push is needed to make it available

FSA periodically publishes summary tables using NSLDS data, proving that the dataset is capable of answering important questions. But these tables cannot be combined with one another, which allows for little leeway in drawing more specific conclusions.

FSA has developed tools to allow for more flexible internal analyses of NSLDS data. In 2004, it built the Enterprise Data Warehouse and Analytics, a system that draws a representative sample of records from NSLDS to allow for new insights into borrowing and repayment. However, FSA does not make these data available to the research community or the public, even though federal law does not prevent it from doing so.

If FSA regularly published a representative sample of NSLDS, it would provide researchers, policymakers, and the public with reliable, up-to-date data on borrowers’ paths through repayment. And if those data were matched with data from other federal agencies, such as the Treasury Department, the Department of Health and Human Services, and Department of Defense, there would be more comprehensive information about student loan borrowers’ earnings, reliance on federal means-tested public benefits, or how servicemembers are faring in repayment.

Pressure from U.S. Education Secretary Betsy DeVos or Congress could push FSA to release these data. Past secretaries have been hesitant to push FSA, however, so it seems unlikely that Secretary DeVos will change course. And although Congress historically has been hesitant to push for more data—and even actively banned a national student-level data system in 2008— there have been recent bipartisan efforts to remove that ban and improve federal data collection and publication.

Congress does not need stand-alone legislation to make a sample of NSLDS available to the public. It could add the provision to a budget bill, providing ongoing availability of the data going forward. Doing so would provide real value to Congress and alleviate some of the burden of analysis on the Department of Education, proving a valuable proposition for all of those invested in improving borrowers’ outcomes.

Colleen Campbell is an associate director of Postsecondary Education at the Center for American Progress.