In the current economic climate, assessing today’s credit risk is one of the most pressing issues facing financial institutions.

Delinquency is expected to rise dramatically in the coming months, and it’s critical to have a comprehensive understanding of each customer’s needs and the ability to take action at the right time.

On May 20, we participated in a Mastercard InConversation Series webinar themed Assessing today’s credit risk and mitigating tomorrow’s delinquency with AI. Brian Riley, Director, Credit Advisory Services, Mercator Advisory Group, and Amyn Dhala, Vice President, Global Product Management, Mastercard, discussed how AI can help with assessing credit risk, mitigate delinquency and improve customer experience so financial institutions can provide more effective services to people when they need them most.

Before we give you a highlight of the webinar, we want to let you know about the next online event. Culminating Mastercard’s InConversation webinar series is a June 17 live Virtual Cyber and Risk Summit where industry experts will be discussing the current and future state of cybersecurity in today’s hyper-digital environment. Topics include securing the ecosystem, connected intelligence and CARTA, the role of transparency and the digital customer experience, bridging authorization and authentication, and using AI to stay a step ahead of fraud. To register, go here.

A tumultuous economy is motivating lenders to seek better tactics for assessing today’s credit risk

Economic indicators were steady throughout Q4 of 2019, which allowed lending organizations to take on more risk; however, debt levels have since been trending up, posing both increased opportunity and risk for lenders. As Brian explained to webinar attendees, the total U.S. household debt level is currently at $14 trillion and, while aggregate delinquency rates remain consistent, student, auto and credit card levels are on the rise. In fact, rising delinquency rates in student and auto loans for young borrowers could have systemic impact down the road.

Recognizing the downstream effects of these trends, lenders are looking for better ways to manage credit risk and improve the lives of their customers. As Amyn shared during the webinar, lending organizations have a timely opportunity to more proactively manage risk with AI, and at the same time improve customer experiences, predict losses early to reduce costs, manage risk throughout the entire customer lifecycle, and better leverage data across their organization.

AI is vital for proactively assessing managing credit risk and decreasing costs

The traditional approach to managing credit risk is largely reactive – wait until delinquency occurs, which is too late for lenders. AI, however, can accurately predict delinquencies as early as 12 months in advance. The technology can also help decrease collection charges and the cost of acquiring new customers, Amyn explained.

By learning from data from multiple sources (such as credit bureau information, credit policies, payment information, account events and/or transaction behavior), AI can be leveraged to gain greater insight and real-time profiling to determine credit risk for any given account. Examples of practical ways lenders can leverage AI include:

  • Predicting customers who will become delinquent
  • Identifying credit abuse activity
  • Improving transaction approvals across cards, ATM withdrawals, ACH, wire, etc.
  • Helping borrowers with their finances when they need it most

Mastercard and Brighterion offer scalable custom models for predicting delinquency

Toward the end of the webinar, Amyn discussed how Mastercard delivers industry-leading AI via Brighterion technology, which processes and analyzes more than 100 billion transactions every year and reduces false positives by 10-20x. Amyn also walked webinar attendees through a case study of one global bank that wanted to proactively identify delinquent accounts so it could take action to collaboratively work with customers to manage payments. Mastercard and Brighterion developed a custom AI model for the bank that predicted which accounts would become delinquent 180 days in advance.

For any financial institution looking to get started using AI for credit risk, Brian and Amyn recommended following these 3 steps:

  1. Discuss the current challenges facing your organization that might benefit from AI
  2. Determine any potential stakeholders to include in the process to maximize performance potential
  3. Map out how AI can be part of your overall credit risk management strategy

For more on how Brighterion’s AI solution can help you predict credit risk and prevent delinquency, check out a variety of resources here.