Here’s a problem every collections team knows too well: by the time you realize an account is in trouble, you’re already playing catch-up.
It’s like trying to grab an umbrella after you’re already soaked.
AKUVO, which builds collections technology for banks, credit unions, and fintechs, just rolled out two new predictive models designed to flip that script. The goal? Help financial institutions see payment trouble coming from a mile away and actually reach people when they make contact.
Two New Tools, One Clear Goal
The company launched two data models that work together to make collections smarter and less reactive:
Propensity to Pay scans your portfolio to flag accounts showing early signs of repayment risk. Think of it as an early warning system that gives you time to step in before a missed payment becomes a chronic problem. With these signals, collections teams can make better decisions about servicing and outreach while there’s still time to course-correct.
Channel Engagement takes the guesswork out of how to reach people. Not everyone wants a phone call, and not everyone checks their email. This model identifies which communication channels are most likely to actually get a response from specific account holders. The result? Better engagement rates and a smoother experience for everyone involved.
From Spray-and-Pray to Surgical Precision
Together, these models help institutions ditch the old-school approach of treating every delinquent account the same way. Instead of casting a wide net and hoping for the best, collections teams can now segment accounts based on actual data, automate the routine stuff with confidence, and deploy their human collectors where they’ll make the biggest impact.
The best part? Both models plug directly into the AKUVO Platform, so teams can weave these insights into their existing workflows (what AKUVO calls “Playbooks”) and track performance through AKUVO iQ.
“Collections teams need enough warning to change an account’s direction and enough engagement intelligence to make every outreach attempt count,” said Mike Orsomarso, SVP of Data and Analytics at AKUVO. “Propensity to Pay and Channel Engagement models give teams practical signals they can build directly into their strategy, helping them decide where to focus and how to connect.”
Building a Smarter Collections Toolkit
These new models are part of AKUVO’s ongoing push to give financial institutions decision-ready insights rather than just raw data dumps. Combined with their existing Severity of Delinquency model, the platform now offers behavioral signals that cover the full collections lifecycle—from the first hint of trouble to resolution.
The takeaway? Collections doesn’t have to feel like crisis management. With the right intelligence at the right time, institutions can actually get ahead of payment problems and connect with people in ways that work.