Consumer debt in the United States grew in 2020 at its sharpest rate in more than a decade, reaching close to $15 trillion. The reason is not difficult to surmise: the pandemic led to millions of lost jobs and other adverse impacts. Yet, this has not been the whole story of the economy. Many consumers have remained gainfully employed and hiring — along with vaccinations — has picked up pace in recent months. Government stimulus programs meanwhile have helped keep consumers and businesses afloat — while also potentially masking the underlying economic fundamentals of borrowers.
These complex and dynamic conditions have brought a long-running challenge for banks to the fore: managing credit risk in a world rocked by unpredictable events. PYMNTS’ latest research reveals that this has become a pressing priority for banks. Thirty-four percent of financial institutions (FIs) consider uncertain economic conditions impacting lending and credit their most important challenge, and 88 percent of them believe the pandemic has exacerbated it.
AI In Focus: The Navigating Bank Credit Risk Playbook, a PYMNTS and Brighterion collaboration, examines how banks are using advanced technology to improve credit risk management, as well as other essential operations like fraud detection. The study, which is based on a survey of 100 FI executives, specifically focuses on how banks are using artificial intelligence (AI) in these key areas and how they view its potential. It also builds on research we have been conducting since 2018, tracking the use of AI and other advanced computational systems in banking, healthcare and other sectors.
Our research shows AI is gaining traction rapidly in the banking sector. The use of AI systems has increased threefold, from approximately 5 percent of FIs overall that reported using them in 2018 to 16 percent in 2021. Large banks have so far spearheaded adoption, with 79 percent of banks with more than $100 billion in assets employing it.
Banks also appear to be getting a remarkably wide range of benefits from AI in the relatively short period of time it has been commercially available. Banks that use AI consider it beneficial for six distinct purposes, which ties it with data mining — a system banks have been using since the 1990s — as the computational technology with the greatest number of benefits, according to our research.
Fraud detection remains a key use case for AI in banking, however, FIs are also increasingly putting AI to work in credit risk management. Three-quarters of banks that employ AI
report using it to identify potentially bad accounts. Other applications include aiding in credit decisions (63 percent), credit/risk underwriting (56 percent) and identifying solutions to potential credit problems (56 percent).
The playbook goes beyond data in assessing how banks are tackling credit and lending issues in a complex economic environment. In this edition, Mike Kinane, the head of credit cards and lending at TD Bank, offers an on-the-ground perspective on the challenges the bank has faced and why the past year has underscored the importance of expecting the unexpected.
For these and many more insights, download the playbook.
About The Playbook
AI In Focus: Navigating Bank Credit Risk Playbook, a collaboration with Brighterion, examines how FIs are using AI and other advanced computational systems to improve credit and lending, as well as other vital operations.
Selected by EFXA