Banks traditionally use data such as credit history and financial information to make credit decisions. With the advent of Big Data, financial institutions can now leverage a much wider range of data to assess the creditworthiness of potential borrowers.
Today, major financial decisions such as investments and loans are based on unbiased machine learning tools. Decisions made based on predictive analysis take into account various aspects, including economic conditions, customer segmentation, company capital, credit data, financial history, repayment behavior, and other factors. This enables the identification and anticipation of potential risks such as bad investments or defaulters, and allows for informed decisions regarding loan approvals.
• In a dynamic Banking Landscape, harnessing Big Data represents a significant competitive advantage. Banks that intelligently utilize available data will be able to optimize their services, improve claims management, and enhance customer satisfaction.