Loan and credit evaluation processes rely on outdated information and misclassifications. AI-powered systems , however, can access many different data sources to make informed and accurate lending decisions. By considering more variables than credit scores and historical transactions, AI-based systems can better assess the creditworthiness of individuals and businesses. This improves the overall quality of lending decisions and expands access to financial services for underbanked populations. However, the use of AI in loan and credit decisioning has its challenges. Retail banks must be mindful of potential biases in the training of data and algorithms and address these issues to ensure fair lending practices.
