DMS & Enova partner with eye toward non-prime underwriting
Digital Matrix Systems (DMS) and Enova Decisions announced a partnership tailored to support the risk-management needs of non-prime finance companies.
To help finance companies make decisions quickly with high accuracy and minimal exposure to fraud, DMS and Enova Decisions pointed out there are a variety of factors at play behind the scenes. They explained that leveraging credit bureau data in conjunction with alternative data sources not only can improve accuracy and mitigates fraud risks, but also can provide finance companies with the ability to reach underserved consumers.
Using carefully selected alternative data can provide a competitive advantage by providing a clearer picture of creditworthiness when paired with machine learning models, according to the companies, which added it’s even more critical for all underwriting decisions when meeting the financial needs of subprime and near-prime consumers.
Enter the collaboration of DMS and Enova Decisions, which is part of Enova International, a leading machine learning (ML) and artificial intelligence (AI) powered financial services company.
This data and analytics partnership supports the two companies’ common goal of helping lenders get the most value from data and minimize risk in support of effective lending decisions.
Enova Decisions’ flagship decision management platform Enova Decisions Cloud can allow finance companies to operationalize AI and make decisions from the cloud via a simple API call.
Enova Decisions will leverage Data Access Point, a connectivity hub from DMS that can link clients to all three credit bureaus and more than 20 alternative data source providers with a single inquiry and delivers the data within a standard XML format.
The company also said credit reports are delivered via the easy-to-read DMS credit report format, which can reduce errors and improve readability of critical credit information.
As business needs evolve, Enova Decisions stressed that it will be able to quickly and cost-effectively add additional data sources for its clients.
In addition to data access, Enova Decisions said it will leverage the tri-bureau DMS Summary Attributes in its machine learning models.
This set of standardized and normalized attributes can consolidate credit information for easier analysis by application and decisioning platforms. This process can provide consistency over multiple bureaus and bureau versions without compromising processing speed.
“We’re excited to work with the Digital Matrix Systems team,” said Jim Granat, senior vice president of Enova Small Business and Enova Decisions.
“We are continually looking for ways we can improve the solutions we deliver to our clients, and this partnership enables us to enhance our core ML and advanced analytics capabilities and make even more data available to our clients in real-time,” Granat continued in a news release.
Digital Matrix Systems senior vice president Carson York added this perspective on the partnership.
“We are thrilled to be working with Enova Decisions in the delivery of analytic services that improve outcomes for lenders,” York said. “DMS seeks partners that are committed to exceeding client expectations, and Enova consistently does this for their client base through the development of models that support lenders and mitigate risk through the entire customer journey.”