According to the Consumer Financial Protection Bureau, Americans filed more grievances about debt collections than about any other financial incident. Of the 316,810 complaints received by the CFPB about debt collection in 2017, the most common was, “Continued attempts to collect debt not owed,” which was cited by 39 percent of grievance filers.
Debt collection in finance is starting to be disrupted by artificial intelligence due to the availability of massive amounts of historical records of customers for banks and other financial institutions. Most AI applications that have real-world business significance for debt collection today seem to be in personalizing communications to customers and identifying clusters of similar debtor profiles.
From our research we have segmented the AI applications for debt collection into the following broad segments:
- Driving Additional Messaging Campaigns
- Customer Service (Debtor) Personalization
- Debt Management Service
We delve further into each of these applications and aim to coax out the need-to-know factors for business leaders regarding AI usage for debt collection.
Driving Additional Messaging Campaigns
Tailoring interactions to debtor habits could be possible with AI today. Virtual assistants are starting to be deployed through channels in which collections agencies can reach out to debtors through email SMS, and outbound dialing, allowing organizations to increase the number of individuals that they’re able to contact on a daily basis.
TrueAccord was founded in 2013 in San Francisco and claims to be offering an AI-driven debt collection solution. The 97-employee company claims to be offering debt collection solutions to banks, eCommerce and telecom companies.
TrueAccord claims that their decision engine uses machine learning to create digital interaction experiences that are customized for each debtor. The company claims its platform can create an interaction model for each debtor.
TrueAccord claims this model provides banks with the best possible channel and time to reach out to existing and new debtors which might eventually result in better debt revenue collections.
The company says more than 1.5 million debtors have already been modeled using their platform. Based on these existing debtor profiles, their software claims to predict an individual’s response time, schedule, best communication channel, and type of content that they’ll respond to.
TrueAccord adds that its decision engine can automatically select the appropriate pre-approved messages from banks to deliver to debtors. The software also tracks, in real time, the action events from the debtor, such as interaction with call centers, or email opens, link clicks and browsing patterns on TrueAccord assets. The software then sends this data to employees at debt collecting agencies so they can plan the ideal style and time of their next message.
What channel the next message should likely https://goo.gl/gGHvYg