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Using Big Data to Prevent Student Loan Defaults

Using Big Data to Prevent Student Loan Defaults


By George Covino, USA Funds Vice President, Default Prevention

College administrators already mine “big data” to gain insights into the performance of their institutions in relation to their missions. Big data – large data sets that can be analyzed to reveal patterns, trends, and associations – already helps schools address issues such as enhancing student success rates, improving teaching effectiveness and reducing administrative burdens. Big data also can be applied to more effectively and cost-efficiently address a critical and growing challenge facing colleges and universities: helping their graduates and other former students successfully repay the loans that helped pay for their studies, and managing institutional cohort default rates (CDRs).

As critical as CDRs are to an institution’s reputation and ability to help students with financial aid, the challenge of maintaining a low CDR is growing more difficult. The Federal Reserve Board of New York estimates the amount of outstanding student loan debt has reached nearly $1.2 trillion (Quarterly Report on Household Debt and Credit, August 2015). According to the Institute for College Access and Success Project on Student Debt, average student loan debt levels for graduates rose 56 percent – to $28,950 from $18,550 – between 2004 and 2014 (Student Debt and the Class of 2014, October 2015).
The solution to addressing this CDR challenge is a more targeted approach to default. Although many colleges and universities have traditionally provided counseling, outreach and other support to all of their student loan borrowers, this blanket approach is more costly, requires greater institutional staff resources, and many institutions simply lack the resources to use a blanket approach effectively.

By identifying students who are likely to be at higher risk for loan default and by concentrating interventions on this population, colleges can more effectively prevent loan defaults and do it with a smaller investment of staff and financial resources.

So what is the “big data” that institutions can use to profile their students who are likely to default on their loans? Each time the Education Department publishes cohort default rates, it issues to each college a Loan Record Detail Report or LRDR. These reports identify all borrowers in a cohort used to calculate the default rate and the status of their loans. By identifying borrowers who defaulted on their loans, and combining data from other sources about these borrowers, an institution can draw a “picture” of a typical student at high risk for default.

Although the exact profile of a defaulted borrower is unique to each school, there are some common factors among all institutions.

Research has consistently shown that students who complete their academic programs are at much lower risk for student loan default than students who borrow for college but withdraw prior to graduation.

As a result, student retention and completion efforts have the additional benefit of combating student loan default (See, for example, Woo, 2002).

A corollary of this first factor is that defaulters also tend to owe less on average than other students who borrow to pay college expenses. This seemingly counterintuitive factor reflects the value of a postsecondary education credential: Graduates are likely to leave campus with higher overall debt levels than noncompleters, but graduates have the academic credentials needed to obtain quality employment to earn the income necessary to manage their higher debt levels.

Another often-cited characteristic of borrowers at risk for default is that they fail to take action on their loan accounts. For example, defaulters fail to take advantage of the opportunities to temporarily postpone payments by requesting deferment or forbearance of their loan payments. In fact, many defaulted borrowers never make a single payment on their loans (Campbell & Hillman, 2015).

Other factors that may be relevant to an institution’s profile of at-risk student loan borrowers may include:

  • Program of study, course requirements or certain enrollment structures such as distance education or remedial classes
  • Demographicss
  • GPA rangess
  • First-generation statuss
  • Students who registered lates
  • Students who did not meet satisfactory academic performance standards

Sources for the data to develop this borrower-risk profile include institutional data, loan servicer files, and reports from the Department of Education’s National Student Loan Data System. The following are some data points that may be relevant:

  • Standardized test scores
  • Student application details
  • Contact or interaction history
  • GPA
  • Full- or part-time or online enrollment status
  • Major
  • Employment status
  • Involvement in on-campus activities
  • Student loan and grant information
  • Alumni engagement

Using this borrower profile, a college can then develop proactive intervention and outreach strategies that target borrowers according to their level of default risk, with greater attention and emphasis paid to higher-risk students. The details of these student loan borrower interventions should be part of a default prevention plan. The Department of Education requires institutions with excessive CDRs to develop such a plan, but it is best practice for an institution to develop, update and follow such a plan, regardless of whether it is required to or not (Default Prevention and Management, 2005).

In addition to providing a plan for action for default prevention at your institution, a default management plan can serve two other vital purposes. First, it offers a forum for establishing overall default management goals for the institution. How much reduction does the institution seek to achieve in its CDR and over what time frame? The plan also should be the focal point for taking an institution-wide approach to default prevention. Managing CDRs is not the sole responsibility of the financial aid office. As noted earlier, student retention and persistence rates are significantly tied to default rates. So enrollment management staff should be involved in default prevention. Student support and academic offices that have important touchpoints with students also should be included. Student records and the business office are also key players in the default prevention effort. And, of course, to be successful, a default management plan needs support from the institution’s chief executive.

In considering default management strategies to incorporate in such a plan, I recommend that colleges and universities follow a “lifecycle of the student approach” that delivers support to at-risk student loan borrowers during four key periods.

Application and first 90 days of enrollment
Default prevention and debt management really begin before students first enter the classroom. Loan counseling and orientation activities should include information about borrowing, as well as advice for minimizing debt and managing finances.

In-school period
This period offers a college the opportunity to develop a relationship with individual students and take steps to promote their future success in managing their student loans, by ensuring students persist to graduation, by including in their education personal finance management training, and by providing accurate reporting of a student’s enrollment status.

As noted earlier, there’s a direct correlation between failure to graduate and student loan default. Colleges should consider having dedicated default prevention and retention staff members that can establish working relationships with student loan borrowers from early in the process through repayment.

A highly effective way to support student success is to surround the student with service. Rather than providing an independent array of services, create a true integration of these services, for example, through “one-stop shops” where a student can go to one building and take care of business with admissions, registrar, financial aid, and the bursar…all in one spot.

Colleges can promote their student success by developing comprehensive early-alert systems to promote timely contact with students at risk of withdrawing and by developing programs to assist students who are not meeting academic progress standards.

Another critical initiative during the in-school period is helping students become financially literate.

If students understand how a late student loan payment affects their credit scores, they may be less likely to miss a payment. A financial literacy program can be a huge benefit to students and a critical component of a default management plan. I find the most effective ways to deliver personal finance information to students is to integrate them into existing programs that students are required to use, such as orientation, counseling and even academic courses.

Accurate reporting of enrollment information is another key to preventing loan defaults. In addition to being a regulatory requirement, timely and accurate reporting helps ensure that student loan borrowers receive their full grace period before loan repayment begins, and further ensures that correspondence and phone calls to borrowers from their loan servicers occur in the appropriate timing and sequence to increase the likelihood of successful loan repayment.

Final year and program completion

The final year in school is an opportune time for preparing students for loan repayment success. Students need support in preparing for life after college, by obtaining employment and understanding the options for repaying their student loans.


Outreach to student loan borrowers after they leave school, whether through graduation or withdrawal, is a proven effective default prevention practice. Three periods are especially appropriate for this outreach.

  • Contacting students during their grace periods – the six months after they leave school before they must begin repaying their loans – offers the opportunity to reinforce that the school staff is a trusted adviser to former students and to ensure they are prepared to make that all-important first student loan payment.
  • Contacting former students whose student loan payments are past due and counseling them on the options for resolving their loan payment problems is a vital step in preventing loan default.
  • Reaching out to former students who are completing periods of deferment or forbearance — when their loan payments were temporarily suspended — can ensure they get back in the habit of making their monthly loan payments.

Using the profile of at-risk borrowers, an institution can customize its outreach based on borrower risk category and the resources available to support the outreach. Borrowers in different risk categories may receive more frequent telephone calls or different messages and calls to action.

Once an institution is committed to a targeted approach to student loan default prevention, it must determine who is going to do the work.

Some schools perform all of the necessary default prevention activities through institutional resources. Others farm out the entire portfolio of work to third-party default prevention experts. Other institutions take a blended approach – performing some default prevention task using campus resources and contracting out others.

In assessing these options, schools should consider both the level of expertise and the depth of resources they have to apply to student loan default prevention. To effectively tap “big data” for default prevention requires access to the data, an aggregator to serve as a repository for the various information sources, and an analytics tool to “make sense” of the data. In addition, a targeted default prevention approach requires resources to carry out the outreach to student loan borrowers and track the results.

Whatever approach is used, mining big data to refine institutional default prevention efforts can have a big payoff in enhancing a school’s reputation, ensuring satisfied alumni and preserving student access to financial aid resources to pay college costs.

George Covino

George Covino has 35 years of experience in financial aid and student loan debt management services. In his current role with USA Funds, he consults with colleges and universities nationwide on the application of financial literacy, borrower outreach, student success strategies and default prevention planning to improve student loan repayment rates and reduce loan defaults. Covino’s previous experience includes service as director of financial aid at Babson College and assistant director of financial assistance at Boston University. He earned a master’ degree in Higher Education administration from Boston University and hold an undergraduate degree from the University of Massachusetts Boston.

Contact Information:George Covino // USA Funds // 866-329-7673, Ext. 0177 // george.covino@usafunds.org // Twitter: @GeorgeRCovino


Campbell, C. and Hillman, N. (2015). A Closer Look at the Trillion: Borrowing, Repayment, and Default at Iowa’s Community Colleges. The Association of Community College Trustees. Retrieved from http://www.acct.org/files/Publications/2015/ACCT_Borrowing-Repayment-Iowa_CCs_09-28-2015.pdf.

Default Prevention and Management: A Plan for Student and School Success. (2005). U.S. Department of Education. Retrieved from http://www.ifap.ed.gov/dpcletters/attachments/GEN0514Attach.pdf.

Quarterly Report on Household Debt and Credit. Federal Reserve Bank of New York. (2015). Retrieved from http://www.newyorkfed.org/householdcredit/2015-q2/data/pdf/HHDC_2015Q2.pdf.

Student Debt and the Class of 2014. (2015). The Institute for College Access and Success Project on Student Debt. Retrieved from http://ticas.org/sites/default/files/pub_files/classof2014.pdf.

Woo, J. (2002). Factors Affecting the Probability of Default: Student Loans in California. Journal of Student Financial Aid. Retrieved from http://publications.nasfaa.org/cgi/viewcontent.cgi?article=1179&context=jsfa.


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