3 ways AI will revolutionise the BFSI industry

Summary

Nearly half of the adult population in the Philippines remains unbanked, according to Bangko Sentral ng Pilipinas, a gap that has long limited access to credit and, by extension, the ability to start or grow a business. Artificial intelligence is starting to close that gap by using alternative data sources to assess creditworthiness for customers who lack the traditional financial history lenders typically require.

Gender bias in credit lending is one of the clearest examples of where AI can make a measurable difference, since men have historically secured loans more easily than women under assumptions embedded, often invisibly, in non-gender data fields used by conventional scoring models. Combining responsible use of gender data with machine learning techniques offers a path to approving creditworthy customers who are currently screened out by traditional models or overly rigid regulatory guidelines.

Beyond lending, the same technologies are reshaping how banks in the BFSI industry compete on customer experience, moving well past basic chatbot deployment into deeper personalisation and process automation that differentiate banks offering largely similar products and services.

• How expanding women's access to credit intersects with broader poverty-reduction outcomes, per World Bank research
• Where AI is moving beyond chatbots into end-to-end banking process transformation

Banking innovation leaders and financial inclusion advocates will find a grounded look at how artificial intelligence is being applied to real credit and customer experience challenges in Southeast Asia.