With 10-plus years in a bull market, the U.S. economy is enjoying an extended, historic period of growth. In fact, many in financial services—including bank executives—may not have faced the seismic challenges that foreshadowed the Great Recession. But as banks, credit unions and other financial services organizations continue to prosper, let’s not forget: Economies are cyclical. The next downturn is not a question of if but when.
While it may seem counterintuitive to prep for the next recession amidst a growing economy, organizations must implement readiness programs for all facets of their business models. That includes portfolio diversification and perhaps most importantly, collections strategies. As no one can foresee the exact timing of any financial downturn, many banks could find themselves unprepared and lacking adequate tools and solutions.
Even time-tested tools may not work. Monetary policymakers such as the Federal Reserve usually reduce interest rates to counteract a downturn and spur growth. But because interest rates already sit at historic lows, that remedy has its limits. That makes it more critical than ever for banks and other lenders to prepare: Those with preemptive strategy will feel the least impact.
The underlying foundation for any recession-readiness program centers on how a bank prevents and handles bad debt. The primary principle is: “Every dollar of losses prevented is a dollar of profit.” That said, collections strategies used in the previous financial downturn are more than a decade old—and likely lean on outdated technology. (In 2007, Apple introduced the first iPhone. Have you seen one in use lately?)
At the most basic level, lenders must monitor their portfolios and minimize the flow of accounts into collections. Closely observe changes in risk metrics across key segments that may point to rises in delinquency—and take preemptive action where necessary. At a more sophisticated level, banks can use advanced data and technology—such as non-traditional data and machine learning—to stress test portfolios under varying scenarios, including economic downturn. The insights can illuminate how certain accounts within bank portfolios will likely perform and lead to specific action plans to engage those accounts: pre-delinquency, during the collections process and after charge-off.
Where relationships meet analytics
Collections strategies demand diverse approaches, which is where analytics-based strategy comes into play. As each customer and situation differs, machine learning techniques and constraint-based optimization can open doors for banks. They can rethink collections outreach beyond static classifications (such as the stage of account delinquency) and instead prioritize accounts most likely to respond to each collections treatment; this creates an improved collections experience.
For example, the bank can better understand whether a customer merely forgot to make a payment or is weathering financial hardship. This helps banks to create a more relevant message, contact the customer during appropriate times and connect through the most preferred channel. A more personalized approach can reduce immediate losses and sustain a customer relationship to last a lifetime.
Customer engagement, carefully considered, perhaps comprises most critical aspect of a recession-readiness program—especially given historical perceptions of the collections process. Experian recently analyzed the impact of traditional collections methods and found that 3 percent of card portfolios closed their accounts after paying their balances in full. And 75 percent of those closures occurred shortly after the account became current. Under traditional methods, a bank may collect the outstanding debt but probably miss out on long-term customer loyalty and future revenue opportunities.
Effective collections, empowered customers
Only effective technology can move us from a linear collections approach towards more customer-focused treatment, while controlling costs and meeting other business objectives. Advanced analytics and machine learning represent the most important advances in collections. Further, powerful digital innovations such as better criteria for customer segmentation and more effective contact strategies can transform collections operations, even as they improve performance and raise customer service standards at a lower cost. Empowering consumers in a digital, safe and consumer-centric environment affects the complete collections agenda—beginning with prevention and management of bad debt and extending through internal and external account resolution.
Beyond the customer experience, advanced analytics and active monitoring can help banks detect fraud exposure—specifically with uncollectible, past-due accounts that reflect illicit activity. Here, banks shouldn’t expect the occasional payment or a negotiated payment plan. The faster that lenders can recognize a fraudulent account within their delinquency queue, the less time and money they’ll spend to recover a debt that will never be paid. Active portfolio monitoring can more easily identify suspicious behavior and optimize action plans accordingly. Additionally, an analytics-based approach can reduce overhead, minimize the need to hire staff and improve compliance during the collections process.
Putting it all together: Tech, collections and weathering recessions
It’s never too early to assess and modernize technology within collections—as well as customer engagement strategies—to produce an efficient, innovative game plan. Smarter decisions lead to higher recovery rates; automation and self-service tools reduce costs; and a more comprehensive customer view enhances relationships. An investment today can minimize the negative impact of the new delinquency challenges a potential recession may present. Collections transformation has in fact already begun, with organizations assembling data and developing algorithms to improve their existing collections processes. In advance of the next recession, two options present themselves: to scramble in a reactive manner or approach collections proactively—and collect out best ideas and strategies now.
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Angela Granger is vice president of analytics, Experian.