Creating a Recession-Resilient Loan Portfolio Through Diversification

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Credit defaults are on track to rise in 2023 as the economy heads towards a possible recession, and bankers are taking notice. In fact, some of the nation’s largest banks recently announced that they plan to set aside up to $4.5 billion in loan loss reserves in anticipation of a recessionary event. While an increase in loan loss reserves is an effective hedge against potential defaults within an existing loan portfolio, how can bankers better ensure that the loans they are originating now are less likely to fall into default in the future?

Some bankers are actively exploring ways to responsibly diversify and expand their loan portfolios, recognizing that risk diversification is fundamental to portfolio management and helps control concentration risk by increasing the borrower base. History has shown that it also considerably reduces the threat of defaults and helps stabilize loan portfolios during times of recession.

For some banks, loan diversification can mean expanding the number of loan products available. For others, it can mean bringing more borrowers into the fold. The challenge for the latter is that the true effects of the pandemic are still reverberating within the credit scores of a large percentage of borrowers. In some cases, this is reflected as artificially higher scores for borrowers with marginal repayment capacity who may experience financial hardship as interest on loans increase, making loan re-payment much more difficult.

So how can bankers diversify their loan portfolios and expand their borrower pools without expanding their level of risk? Increasingly, banks are leveraging access to new alternative data sets and borrower-permissioned access to bank statements, mobile phone bills and rent rolls, in addition to the FICO score, to help gain a more accurate view of a borrower’s true ability and propensity to pay. Speed to market is key, and bankers should focus on solutions that create decision pathways to guide potential borrowers through the required next steps to qualify for loans, but that do not require banks to redirect significant internal resources to implement.

What alternative data does is help bankers better see the patterns that uncover ways to provide solutions to a larger group. By incorporating this level of insight into rules-based decisioning workflows, bankers can provide loan products and solutions to a larger group of consumers through a more efficient, user-friendly consumer experience.

The market opportunity is there for banks that wish to pursue it. Currently, there are about 17.9 percent of households classified as “underbanked” and 5.4 percent classified as “unbanked” in the United States, while the number of people needing loans has increased by 24 percent. Consider the Hispanic and Latino market in the U.S. alone, which accounts for more than 18 percent of the U.S. population but remains one of the most underserved markets by the financial industry. A recent study conducted by the Government Accountability Office, stated that 14 percent of Hispanics are unbanked, and 30 percent are underbanked (compared to 3 percent of whites who are unbanked and 14 percent who are underbanked). There are a number of reasons for this discrepancy, from many consumers falling outside of the traditional credit scoring system to a large percentage of consumers living in so-called “banking deserts.”

The reality is that many “thin file” consumers represent a safe credit risk for bankers who commit to identifying and serving them and the need for greater levels of loan diversity and resilience in the face of recession may provide the catalyst to finally do so. Those banks that do will be in a better position to grow and diversify their loan portfolios which, in time, may prove to a key step in weathering the next economic downturn.

About Author:
Steve Bireley, Chief Technology Officer of Lokyata, has decades of enterprise and B2B SaaS product engineer experience, and is enthusiastic about helping banks build and scale their credit decisioning capabilities.


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