Toronto-based fintech Operant.AI believes a consortium for financial institutions is needed to improve the performance at third-party debt collection agencies.
Operant Founder and CEO Allan Fisch said at a meetup yesterday at Bank Innovation’s headquarters in New York that a consortium would allow the FIs to contribute anonymized data on the performance of their third-party debt collection agencies, thereby allowing for better collection performance industrywide.
Operant is a machine learning-powered platform that could use such data to help improve banks’ and agencies’ repayments rates.
The purpose of this consortium would be to help the banks turn their debt collection departments into revenue drivers, as opposed to cost centers, as they are typically viewed, Fisch said. This consortium of FIs could solve the misalignment problem that exists between banks and their collection agencies, Fisch said.
“Collection agencies are handicapped because they do not have enough data,” Fisch said. “To give these agencies the analytics, without letting them into the data room, we can better align banks with collection centers.”
Watch Fisch explain Operant’s consortium here:
Operant.AI uses machine learning on collections data to modernize the collection process. The company currently works with banks and accounts receivable groups in Canada and has an upcoming proof-of-concept initiative with a large Canadian bank. Operant integrates data associated with bank accounts, as well as gathers some of its own proprietary data, and then applies machine learning to personalize the collection agency’s approach — all at the urging of the financial institution that owns the debt. This, according to Fisch, improves the customer experience, increases repayment rates by perhaps 20%, and maximizes retention.
Operant.AI plans to launch in the U.S. soon, and is in the current startup class of INV Fintech, this publication’s sister accelerator.1 - Reader Likes This Post