EQ Engine
Most teams waste effort on accounts that are never going to pay, or miss the ones about to slip.
Experience the power of predictive analytics for debt collection.
EQ Engine applies predictive analytics for debt collection, scoring every account in a portfolio for propensity to pay and collection probability, so you know where to spend effort in advance.
From there, EQ Engine turns that score into a next-best-action recommendation, which channel, what timing, what offer, and updates it again every time you re-score. Our scores aren't a one-time label; they move with the account.
Payment projection
Predict how much you'll actually recover, so you focus effort where it counts.
Collection probability
See repayment likelihood for every account in your portfolio in every channel.
Dynamic updates
Predictions update as borrower behavior and market conditions shift.
Performing accounts
Spot which healthy accounts are at risk (before they slip).
For example, deciding which of two current borrowers gets an early-intervention offer versus a routine reminder, based on how their risk profile is trending before anything is past due.
Collections
Apply our predictive data to every text, email, or dialer campaign to retain good borrowers.
For example, choosing whether an early-stage account gets a self-service nudge or a live agent call, based on its predicted response to each channel.
Recovery
Understand your options and focus late-stage effort where the returns are real.
For example, choosing between a payment plan, a settlement offer, or legal placement, based on the account's valuation and a predicted net recovery value.
Valuation
Value portfolios down to the account level. Price with confidence.
For example, setting a floor price for a portfolio segment based on what EQ Engine projects it will actually recover, not its face value.
Credit data + payment history + real-time behavior. One view. That feeds a scoring layer that outputs a value and risk estimate plus a next-best-action recommendation: which channel, what timing, what offer. It rescores again as new payment and contact activity arrives.
Legal Selection Scoring: Real results
On one client's legal-placement decisions, EQ Engine's selection model produced a 10x lift between its best and worst-ranked accounts, versus a 2x lift from a generic credit score, adding significant precision to the client's legal strategy. That let the client redirect 36% of its high-cost legal placements and add $9 million in net collections. On another client's letter-targeting program, EQ Engine's selection criteria produced a 167% lift in average 30-day unit yield versus the whole-population baseline.
Built for how you collect
Creditors
Rank accounts by who's likely to cure before charge-off, with scores you can explain line by line.
Debt Buyers
Know what a portfolio is worth at the account level before you price it, not after.
Collection Agencies
Place effort on the accounts that will actually pay.
Auto Lenders
Rank auto accounts based on expected recovery value, so efforts and legal costs go to the paper that needs them.
Put a smarter score on every account you hold
Scored inventory in weeks, not quarters. Models customized to your assets and environment.