The importance of credit decisioning in the success of a credit business cannot be overemphasized. Credit businesses are heavily dependent on their business rules, mathematical models, and data to make profitable decisions. Customer behavior and expectations have been irrevocably transformed as a result of the pandemic, and the use of alternative credit products such as BNPL, peer-to-peer lending, point-of-sale financing, and embedded credit has proliferated. At the same time, financial institutions now have access to unprecedented amounts of data owing to a digital footprint across all transactions. These factors combined with developments in AI/ML and analytics, are shaping a new battleground for financial institutions. They not only have to grapple with financial, structural, and regulatory changes but also compete with nimble new-age start-ups with next-gen decision models o ering lower customer acquisition costs, faster turnaround times, and frequent feature releases. All of which makes it imperative for financial institutions to upgrade their systems and capabilities across the credit suite to make robust credit decisions. These challenges also present an opportunity to leverage new-age decisioning models based on AI and ML, tap into alternative data, and harness the power of cloud to create lasting competitive advantage.
In this white paper, we take a look at new developments in the credit decisioning world, major concerns and challenges facing banks today with respect to credit decisioning, and the building blocks of credit decisioning platforms created for the future.
