AI in Lending: Prospects, Probabilities and Platitudes

For our eleventh episode, we’re delighted to be joined by Giovanni Oppenheim, Director of Banking Solution, at Earnix. Earnix has a highly esteemed reputation in Insurance, and across the last seven years has made great strides in Banking,with a focus on pricing and personalization software.  Our conversation covers key challenges for incumbent lenders, what role different types of AI technology can play in addressing financial inclusion, decisioning,personalized pricing, competition from Buy Now, Pay Later (BNPL) and delivering key tenets within Consumer Duty in the UK. We also cover key forward lookingtrends around financial inclusion and fairness in lending.     Time stamps as follows: 0:00-05:00 – Introductions and Set Up05:00 – Where is AI most effective in reshaping lending activities?07:00 – What examples have we seen in Co-pilots Vs Gen AI for synthetic data?08:30 – Examples of live Earnix case studies in Banking 09:30 – Metrics used to quantify AI improvements in lending 11:30 – How can AI assist financial inclusion 14:30 – How does incumbent bank credit approvals compare to BNPL providers16:50 – Best examples of inclusive finance using Gen AI 20:00 – Best examples of Gen AI within Consumer Duty 23:30 – AI to manage credit risk amid increased uncertainty 27:00 – AI to increase agility and flexibility 28:00 – Conclusion and Wrap-Up