Recovering the lost art of consumer credit risk assessment


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As the country recovers from the physical and mental health implications of the COVID-19 pandemic, the economic consequences could affect consumers’ financial health and credit underwriting for years to come. The Federal Reserve recently questioned the effectiveness of traditional scores over the next several years. Their general point is this: The industry could face systemic risk if and when data on commercial lines of credit changes in value as a direct result of COVID-19 programs and effects. When consumers’ underwriting decisions are based on tools limited to the history of credit reports, credit decisions can become less efficient and credit products less accessible or more expensive. Fortunately, financial institutions can access much more information than what is found in a traditional credit score. This is where alternative data comes in.

The new COVID normal

Consumers and businesses have had to adapt to work in the home economy resulting from the pandemic. There has been a clear division in how the pandemic has impacted the financial health of consumers. For those who maintained their sources of income, the reduction in expenses related to travel, entertainment and meals served as something like a raise in wages that they could use to pay off debts or increase their savings. For people negatively affected by the pandemic, such as those in service industries – restaurants, hotels and retail – the results have been much less favorable. Those who have been negatively affected have relied on federal, state and regional stimulus packages and may have relied heavily on banking products to weather the storm.

Historically speaking, access to affordable banking products has depended greatly on credit history. A single major financial disruption, such as a job loss or the death of the breadwinner, could lead to bankruptcy, impacting the financial health of consumers for seven to ten years.

During the pandemic, one program that was particularly helpful in weathering the financial storm was forbearance, which gave consumers the ability to skip payments to financial institutions without spending or negative reporting. Forbearance has also helped consumers prioritize spending by deferring payments without incurring fees or damaging their credit history in the long run.

These two factors, financial stress and forbearance, each impacted the value of line-based solutions in determining a consumer’s overall ability to pay. As a result, overall default rates may increase over time as lenders rely solely on these products and services.

Tradeline data may not create a reliable image

COVID-19 has also led commercial lines of credit data to be less reflective of financial health, an issue that has led the Federal Reserve to question the value of commercial lines of credit data, than credit bureaus. credit use to describe the balance, arrears, and account information for each credit account listed. on credit reports. For those who did not opt ​​out, situational credit defaults could underestimate a consumer’s creditworthiness due to events beyond their control. For these consumers, traditional credit scores based on data from business lines could go down.

For those who opted out, credit information about financial stress will not appear on credit reports, even as overall consumer debt increases. In these cases, scores based on line of credit information alone could underestimate a person’s financial health.

This is the systemic risk that the Federal Reserve referred to. While line-of-credit data does not fully reflect the health of consumer credit, scores based on this data are less effective. Consumers may then have less access to credit or experience increases in the cost of credit. These trends could threaten customers’ access to affordable credit and the ability of lenders to issue affordable credit, as unreported credit risk drives up credit default rates.

It’s the perfect storm of systemic risk. The pandemic has heightened financial stress in which the industry’s reliance on data from traditional commercial lines of credit hampered the ability of consumers to provide the tools necessary to weather the storm.

Bringing alternative data to the fore

It is at times like these that responsible credit underwriting is best served by expanding the information available to the underwriter. This provides a better view of a consumer’s long-term creditworthiness rather than relying on a single point in time when business line data is affected by a variety of ‘noisy’ credit events that can obscure the real risk to the consumer. This increase in systemic risk is destabilizing.

Many consumers who did not have a credit footprint before the pandemic suddenly need access to financial products. These consumers have sought out banking products in large numbers. In these cases, invisible credit consumers or thin file consumers have likely been denied affordable credit products or pushed into much more expensive risky products.

The solution to these risks is for lenders to invite other sources of solid data into the decision-making process. Alternative data such as public records and property records can provide additional information about a person’s overall creditworthiness beyond their specific business behaviors. This data also adds depth to the data-driven decisions of traditional commercial lines of credit by indicating high and low risk behaviors outside the consumer’s wallet. Lenders could then make more refined decisions based on the combination of the larger data elements in which traditional business data is part of the decision rather than the sole driver of the decision.

By opening up the process to other predictors such as FCRA-compliant alternative and non-commercial credit event data (such as ownership, address stability, and economic health), lenders could make responsible loan offers to consumers currently disenfranchised by the existing credit system. or impacted by the pandemic.

Given the current data landscape, it makes sense to expand the data used in credit decisions. By diversifying the information in a decision, the impact and effectiveness of a particular score becomes less impacting on that decision. The overall systemic risk of single-source decision-making can decrease dramatically.

Alternative data helps banks lend to more consumers

This is where alternative data comes in handy. Alternative data can also replace traditional data on lines of credit when such data is not available. It can also help some consumers – especially invisible credit groups – to break out of their less desirable credit status. Many of these consumers could then open affordable credit accounts, purchase cars and homes, or use a credit card on reasonable terms. For example, an internal LexisNexis Risk Solutions review of applicants for banking products found that using alternative data attracted 35% more consumers than a traditional strategy based on credit reports.

Using alternative data can also reduce the systemic risk of fundraising campaigns across the industry. It is one of the best defenses against the systemic risk presented by single-source decision making, based on data from lines of credit. This is especially true as the Federal Reserve and industry question the effectiveness of data in supporting the post-COVID economy.

Alternative data must more than ever be a key component of underwriting decision-making strategies. This data can provide increased predictive value when used with a traditional credit score based on a commercial line and enable the scoring of many consumers who cannot achieve credit scores using only traditional credit data. This fosters an environment of inclusion, which all financial institutions and governments should aim for.

Jeffrey Feinstein Jeffrey Feinstein

Jeffrey Feinstein is vice president of global analytics strategy for LexisNexis Risk Solutions based in Alpharetta, Georgia.


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