With charge-offs and delinquencies hitting recent highs, the stability of your credit portfolio may be at risk.

At first glance, issuers have lost some of the tools in their tool belts to help delinquent customers get back on track with their payments. Delinquencies and charge-offs were less of an issue during the pandemic.

The New York Fed in February said delinquencies surged in 2023 as did total consumer debt, with credit card delinquencies leading the way with a 50%+ increase during the year. This signals a normalization of credit after pandemic-related stimulus aids wane and a reflection of the impact of higher inflation and interest rates, leading consumers to rely more on credit products for purchases, which can contribute to rising delinquencies and charge-offs.

With a total of $1.13 trillion in debt, credit card debt that moved into serious delinquency amounted to 6.4% in the fourth quarter, a 59% jump from just over 4% at the end of 2022, the New York Fed reported. The quarterly increase at an annualized pace was around 8.5%, New York Fed researchers said.

Delinquencies also rose in mortgages, auto loans and the “other” category. Student loan delinquencies moved lower as did home equity lines of credit. Overall, 1.42% of debt was 90 days or more past due, up from just over 1% at the end of 2022.

Financial institutions can implement several strategies based on recent data when trying to address the challenge of rising delinquencies and charge-offs, including monitoring and stabilizing delinquency rates, managing net loss rates, improving portfolio yields, and adapting to economic changes.

In addition, we’re seeing clients and prospects use data analytics to understand customer behavior, analyze purchase patterns, calculate Customer Lifetime Value, and deliver personalized offerings in real time.

The Consumer Financial Protection Bureau (CFPB) has made it more difficult for issuers to collect since its enhancement of Regulation F at the end of November 2021 – in particular the 7-in-7 rule limiting the number of contacts collectors can have in a seven-day period — and with its recent effort to reduce the maximum card late fee to $8 – undermining a critical part of reinforcing the importance of paying on time.

Implementation of the 7-in-7 rule under Regulation F has had significant implications for debt collection practices and necessitates adherence to the prescribed limits to ensure compliance with consumer protection regulations.

Regarding late fees, data analytics play a crucial role in understanding consumer behavior and the financial impact of late fees on accounts. The analysis of average late fees, revenue generated from late fees, and the proportion of late fees to total consumer charges provides insights into the financial dynamics of issuers.

By examining data related to late fees, such as trends in late fee volume, revenue generated, and the correlation between reliance on late fees and subprime accounts, financial institutions can optimize their strategies for fee structures and consumer interactions.

As a result, we’re seeing increased interest from issuers in turning to data analytics to address these challenges. Here at Predictive Analytics Group, we’re talking to them about:

1. Proactive Risk Management includes strategies to build loss reserves ahead of potential defaults.
2. Predictive Modeling forecasts the likelihood of delinquencies or charge-offs based on various factors such as payment history, credit utilization, and economic indicators. These models help prioritize accounts for intervention and tailor strategies to mitigate losses.
3. Segmentation and Targeted Interventions can result in offers of financial education programs or personalized assistance to high-risk groups, thereby reducing delinquencies and improving repayment rates.
4. Behavioral Analysis is about understanding consumer behavior through data analytics, allowing clients to offer tailored solutions like setting up alerts for overspending or providing budgeting tools to help customers manage their finances effectively.
5. Regulatory Compliance: Recent efforts by regulatory bodies, such as the CFPB’s effort to cap credit card late fees at $8, are encouraging issuers to use services like ours to ensure compliance with new regulations while optimizing their revenue strategies.
6. Fraud Detection: Data analytics can also be instrumental in detecting fraudulent activities that may contribute to delinquencies or charge-offs. By monitoring transaction data for anomalies and implementing fraud detection algorithms, issuers can prevent losses due to unauthorized transactions or identity theft.
7. AI Integration: Leveraging AI technologies can enhance risk assessment capabilities, enabling banks to safeguard against rising delinquencies by predicting customer behavior and identifying potential defaults early on.

Our advanced data analytics solutions offer a lifeline, turning overwhelming data into actionable insights that can stabilize and even improve your collections outcomes.

By leveraging data analytics effectively, lenders can navigate the challenges posed by rising delinquencies and charge-offs. Understanding consumer behavior, implementing predictive models, and adopting targeted interventions are key strategies that can help banks proactively manage risks and optimize their approaches to loan product management.

By collecting, integrating, and analyzing data from multiple internal and external sources, financial institutions can gain a holistic view of customers. This allows them to match customer behavioral patterns with their spending habits to identify individuals likely to default, reducing manual errors and saving time through automated technologies.

Let us know if you’d like to talk about how predictive analytics might help your collections operations.