Artificial intelligence is a transformative technology that has a major impact on the credit sector. By unlocking insights from real-time and historical customer data, AI can make meaningful predictions about future behavior and detect signs of financial stress to drive down defaults and increase profitability.

AI can optimize every stage of the credit lifecycle to deliver tangible benefits for both the applicant and the institution.

Leaders of all sizes have recognized the potential of AI and are now prioritizing investments in this space. Almost two-thirds (60%) of leaders have allocated capital to Generative AI (GenAI) in the last year and 75% plan to increase spending over the next 12 months, EY reports^[1]. A Gartner forecast predicts that 80% of customer service and support organizations will have deployed generative AI technology by 2025^[2].

How is AI changing the credit industry?

We know that lenders have many unanswered questions about AI. To help our clients and prospective customers answer them to understand more about the material benefits of using AI to transform risk assessment and management processes, we’ve produced a free whitepaper called Beyond the Algorithm: Making better credit decisions with AI.

Here are some of the questions credit institutions should consider as they enact AI transformation.

How are AI regulations evolving? Globally, regulatory frameworks are being developed to address the unique challenges posed by AI , aiming to balance innovation with consumer protection and financial system stability. From the EU AI Act to the US Executive Order or the African Union’s continent-wide AI policy, understanding regulation is a crucial first step to unlocking the benefits of AI.

How can AI improve credit risk assessment? Although AI can be of benefit throughout the lifecycle, we focus our report in three areas: credit scoring, early warning systems, and collections. Traditionally, these processes have relied heavily on manual assessments and predefined rules. ML-powered credit decision-making extends beyond scoring models to encompass the entire credit approval process. By automating repetitive tasks and leveraging predictive analytics, ML algorithms can expedite credit evaluations, reduce manual errors, and increase operational efficiency.

How are banks using AI? Institutions are deploying AI from the back office to the boardroom, unlocking efficiencies and creating opportunities to improve services. By implementing AI across these various functions, banks are not only enhancing their operational capabilities but also providing better services to their customers, ensuring compliance, and staying sharp in an increasingly competitive digital financial landscape. From JP Morgan’s LLMs to Morgan Stanley’s AI-powered robo-advisor, understanding competitors' use of this game-changing technology will help institutions get ready to seize the opportunity.

Get ready for transformation

^[1] https://www.ey.com/en_nn/newsroom/2023/12/majority-of-european-financial-services-leaders-expect-generative-ai-to-significantly-affect-productivity-and-change-roles-but-many-firms-still-lack-plans-to-upskill-their-workforce

^[2] https://www.gartner.com/en/newsroom/press-releases/2023-08-30-gartner-reveals-three-technologies-that-will-transform-customer-service-and-support-by-2028