Connect the data you already use
Once you move forward, PayRank works from the file or database fields already in your operations. Simply generate a few exports and we will handle all of the mapping and onboarding on our end.
Account prioritization built for collections
Work the accounts most likely to produce revenue.
PayRank is built on actuarial principles. Our predictive scoring engine ranks every account by expected recovery value, combining payment propensity with balance size to estimate realistic liquidation value. Rather than relying on raw balance, placement date, or generic bureau scores, PayRank delivers a prioritized action queue informed by the operational factors in your own portfolio that credit bureaus miss.
Built on your own portfolio data
Integrates directly into existing workflows
Go live in as little as 1 week
Unlimited active-book score refreshes
Score BandOutreachFees
9000–999910%41%
8000–899910%23%
7000–799910%15%
6000–699911%9%
5000–599911%6%
4000–499911%3%
3000–399911%1%
2000–299911%1%
1000–19999%1%
0–9997%1%
In one backtested portfolio, the top 10% of scored accounts generated 41% of fees with roughly the same outreach share as each other score band. The bottom 30% generated less than 3% combined.
41%of fees from the top 10% in the example backtest
<3%of fees from the bottom 30% combined
0–9,999one expected-recovery-value score for every account
Unlimitedactive-book score refreshes
How it works
A ranking layer for the collection system you already use.
PayRank does not require your agents to learn a new platform or use special software. We score your accounts and return everything to you for automated integration into your existing workflows.
PayRank scores every account
The model combines payment propensity with realistic recovery value, using the signals available in your own internal data.
Work the ranked queue
Scores flow back into your system for immediate implementation. Re-score as often as needed either on a scheduled cadence or as ad-hoc SFTP drops.
Why PayRank
Built for a different question than a credit score.
A collection operation does not need another opinion on whether an account is generally creditworthy. It needs to know where the next hour of collection effort has the highest expected value.
Ranks expected recovery, not just likelihood to pay
A high-propensity $200 balance and a low-propensity $4,000 balance are not economically equivalent. PayRank is designed to rank the expected collection dollars behind every account.
Built by an actuary. Fit to your portfolio.
PayRank was built by an actuary with over two decades of financial modeling and analytics experience. Your model is trained only on your own internal data which creates a highly customized score that other approaches cannot capture.
Useful output, not another dashboard to babysit
Each run returns account-level scores and drivers plus a portfolio summary. Our analytics portal is available for management visibility, while agents only see the score plugged into your existing system where they already work every day.
Integration
Start with an export file and automate whenever it makes sense.
Our model is designed to be plug-and-play with very little integration work.
SFTP / cloud file exchange
Send a placement file and receive the scored file plus batch summary back through a familiar scheduled-file workflow.
API
Submit scoring jobs programmatically for placement-time scoring or automated queue refreshes.
Direct database connection
Use scoped, read-only access for inputs and write scores to a landing area you control.
Built primarily for third-party collection agencies, with the same ranking approach applicable to other high-volume recovery portfolios.
Let us show you how it works
See how PayRank would fit into your collection operation.
Request a short demo and we’ll walk through the scoring approach, the ranked output, and how PayRank fits into the systems your team already uses. No portfolio file is required to get started.
Email us and we’ll respond promptly, answer any initial questions, and coordinate a demo.