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Q&A: Credit decisioning and the two-lane economy

Investments in analytics, such as AI and machine learning solutions, enable companies to utilize non-traditional data sets quickly, explain what the data is revealing, and test new credit risk models and strategies.

View of the City of London from The Shard. Image by Tim Sandle.
View of the City of London from The Shard. Image by Tim Sandle.

Many businesses rely on credit and gaining access can be a labyrinthine process, fought with complexity. To chart a route through, Experian has launched a new eBook titled Navigating a New Era of Credit Risk Decisioning, which looks at today’s complex lending and credit landscape.

Credit decisioning refers to the internal procedures followed by an organization in deciding to accept a certain credit risk as part of regular credit origination for banks and similar institutions where granting credit is part of the business model.

To gain an insight into the book’s themes, Digital Journal caught up with Donna DePasquale, Executive Vice President of Global Decisioning at Experian.

Digital Journal: Your new eBook Navigating a New Era of Credit Risk Decisioning took a look at consumer spending behaviors and how lenders are navigating today’s complex landscape. What were some of the most interesting consumer findings?

Donna DePasquale: We found that there is a two-lane economy that has emerged and exacerbated due the pandemic. Our data shows that 1 out of 3 consumers remain concerned about their finances. However, at the same time some individuals currently have more cash than they had when the pandemic started—and now they’re ready to spend. We found that these consumers are no longer reducing their discretionary spending as much as they were six months ago. Only 11 percent are cutting their spending compared to 19% a year ago. We also found that high-income houses (earning more than $100K annually) are starting to spend the most.

DJ: Why does this environment make it more difficult for lenders to be able to offer the right loans and products to the right consumers?

DePasquale: Navigating this varied landscape depends on a deep understanding of individual customer needs and the ability to serve customers across the spectrum. This period of the great deferral, the aggregate impact of payment assistance programs, coupled with changes in spending and savings behaviors, requires lenders to look beyond traditional approaches to credit decisioning. Forward-looking companies will need to go beyond traditional data sources and leverage expanded data to anticipate the credit needs of their customers while using tools to automate the decisioning process and reduce the risk.

DJ: What can lenders do to make smarter more efficient decisions?

DePasquale: We identified three things lenders need to do to navigate the complexity of the current lending and credit landscape:

  1. Leverage data and advanced analytics – to create a comprehensive understanding of the risk and opportunity of their portfolio as well as visibility into changes to customer profiles.
  2. Proactively engage customers – offer new credit and other products to support those that are recovered and ready to engage.
  3. Prepare for a potential wave of delinquency – as payment holidays come to an end, lenders should make it easy for customers that are still struggling. Lenders must offer online support and flexible terms that help customers solve their problems.

DJ: You mentioned advanced analytics, how can use AI to ensure they are offering financial access to all consumers?

DePasquale: The data inputs generated by the pandemic have impacted credit risk models and machine learning applications in unexpected way considering widespread payment holidays and government assistance programs. These factors have impacted the performance of credit models that rely on historical data and may be masking customers’ true financial circumstances. As a result, lender confidence in models has slipped. But, investments in analytics, such as AI and machine learning solutions, enable companies to utilize non-traditional data sets quickly, explain what the data is revealing, and test new credit risk models and strategies. At Experian, we believe that everyone deserves financial access and AI can help make sure lenders are reaching customers in real-time with the most relevant, contextual offer, when they need it most.

DJ: Your research found that consumers continue to prefer digital banking, will that continue to trend upwards?

DePasquale: Absolutely, we believe the pandemic pushed people to bank online and the convenience of it is keeping people banking online. 55 percent of people conducted banking online during the pandemic versus 33% before. We saw increases across age groups. In fact, 14 percent of consumers surveyed age 60-69 applied for a new loan or card online during the period. With more people banking online, expectations are on the rise. 55 percent of consumers have higher expectations of their digital experience since the pandemic began.

DJ: What about payment options such as subscription models and buy-now/pay later?

DePasquale: The convenience of digital channels is also creating the opportunity for new payment methods, such as subscription models and buy-now/pay later (BNPL.) We found that 27% of consumers reported purchasing products using buy now/pay later programs. Flexible payment options will be important for consumers going forward and businesses need to adopt. A digital strategy simply isn’t enough anymore. There needs to be a re-imagined customer journey that puts the consumer at the center.

Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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