Banks to use artificial intelligence to determine credit ratings

The new report shows how technologies such as machine learning, predictive analytics, and natural language processing (NLP) could transform the banking industry in both front-office and back-office operations.

Artificial intelligence could have the biggest impact on behind-the-scenes operations. Banks are experimenting with machine learning for determining scoring techniques that would reduce the risks of lending. AI can also offer the necessary analytics for assessing lending risks for customers, who especially in developing markets, lack conventional credit records. For example, AI can be used to analyze non-traditional types of data, such as mobile phone usage and social media profiles, to predict the creditworthiness of borrowers

AI will also transform behind-the-scenes operations. One area that is already experiencing significant change is lending. Traditional credit scoring techniques are ill-equipped to deal with consumers who lack conventional credit records, which is a common occurrence in developing markets. However, some lenders are now using AI to analyze non-traditional types of data, such as mobile phone usage and social media profiles, to predict the creditworthiness of borrowers.

NLP technologies also allow banks to create more customer-orientated products. Chatbots are evolving and allow better interactions with banks. Chatbots can also work as financial advisors, as they employ advanced analytics to offer financial insights to consumers, such as warning them when they are likely to go overdrawn or recommending changes in behavior that will allow them to save money.