The lending and collecting processes are crucial to a bank’s operations and involve many customer touchpoints. Due to the ever-growing number of options that customers have at their disposal, institutions that can provide a superior customer experience in these domains are at a distinct advantage in developing customer loyalty.
Research has shown that a credit lead has the highest chance of being converted in the first three minutes of contact. The chances significantly diminish after 30 minutes and become miniscule after just one day.Research also shows that on average only 20% of leads are converted. So, how do financial institutions sift through all of their incoming leads to identify those that are most likely to be converted and not lose potential business?
For this report, Efma spoke with five leading bankers who work in the lending space to better understand how they are implementing artificial intelligence and machine learning to eliminate processes, source leads, and reduce fraud. Across the board, banks listed effective lead prioritization as their number one priority when it comes to the lending process. Yet, in their responses, the bankers admitted to limited machine learning implementation in their lead prioritization processes. While there is considerable push to be more sophisticated from top leadership, the speed of change is often slow.
Read more on the insights shared by leading experts in this space.