Client Results
“We have recently utilized RDS to identify asset information on batches of dormant post judgement accounts. The results from our original placement have been impressive, resulting in a 300+% return on our gross spend. Equally as important, the folks at RDS are professional, compliant, analytically driven, and a pleasure to work with.”
“The hit rate was higher than any employment vendor we used previously.”
“Finally, a product that provides the most important element-peace of mind.”
Using Data Science for Distressed Debt Recovery
From locating and analyzing assets to predicting the likelihood and amount an account will pay, data can transform debt recovery. But few organizations have the requisite datasets or technical capacity to realize those possibilities.
Our suite of data analytics tools equip you with everything you need to pursue the most profitable accounts in the right order – and produce the highest yield. Using proprietary account analytic models, uniquely large datasets and cutting-edge AI, we improve data accuracy across multiple sources, create suit-decisioning scores and produce actionable insights to save you time and money.
Asset Identification
Deciding whether legal action will be worthwhile is difficult when you don’t have an accurate view of an account’s assets. But our industry-leading asset location process takes the guesswork out of identifying payers to verify consumer assets, including real estate ownership, bank accounts and employment – ultimately producing higher yields.
Paymetrix AI utilizes a sophisticated asset waterfall in conjunction with recursive searching, multi-step verification and unique data sources to find previously undiscovered assets from pre-suit and post-judgment accounts.
Paymetrix AI:
- Accesses exclusive partnerships and proprietary databases
- Guarantees accuracy of data across many sources
- Balances maximum recovery with timing of cash flows
Account Decisioning
Our account decisioning model provides actionable insights to help creditors prioritize accounts for servicing efforts. Using Paymetrix AD, creditors and account servicers are able to create a ranking of accounts, enabling efforts to be focused on the most profitable accounts and an efficient litigation strategy. Our proven cost/benefit model continually demonstrates the value we add to the account servicing process.
Paymetrix AD understands and prioritizes accounts by:
- Using linear and logistic regression and machine learning on historical data to predict future results
- Determining the probability of payments and then calculating the Net Present Value of those payments
- Creating a profitability index based on these metrics
Profitability Index
Most organizations work manually to predict each account’s value and propensity to pay. But even those that use predictive analytics have to invest large amounts of capital and time to see results.
Paymetrix PI is a cost-effective suit-decisioning tool that leverages 35 years of historical data to help you pinpoint the right accounts to litigate. We use AI to approximate the likelihood of assets, implement a second sophisticated model to score the account, then provide a weighted score based on the original probability of assets.
As a result, you can:
- Understand the value of a portfolio and the optimal mix of collection strategies
- Litigate the most profitable accounts in the right order
- Save time and money on your suit-decisioning scores
Real Estate Valuation Software
Where a consumer lives tells us a lot about their financial situation and whether they can afford to repay their debt. Our real estate valuation software leverages this fact to produce better asset insights for quicker profits.
Paymetrix RE employs deep machine learning techniques to identify up-to-date images of both the property of interest and surrounding properties. It then compares the images to data from more than 155 million U.S. properties, producing an overall real estate score that evaluates the quality and value of a property. Paymetrix LUX takes the same model and adds images of home interiors from a mix of different sources to provide even more granular data.
This technology can also be used to:
- Make decisions on credit worthiness
- Determine optimal locations for new businesses
- Target properties to rehab in high scoring neighborhoods
- Automate property decisioning fo foreclosures or the REO market
