MidAtlantic Finance Selects Point Predictive Auto ONE to Transform Fraud Operations
Solutions will help lenders detect more fraud and misrepresentation, streamline fraud operations, and combat emerging schemes
Point Predictive, the San Diego-based company that provides artificial intelligence (AI) solutions to lenders, announced that MidAtlantic Finance has adopted Auto ONE, its suite of one-of-a-kind, SaaS fraud risk management solutions designed specifically for automotive lenders.
Latest Aithority Insights: Detecting, Addressing and Debunking the Hidden AI Biases
Auto ONE delivers a full suite of AI-based resources delivered in one location, with a single API call, and sub-second response. Together these solutions can be easily integrated into the auto loan origination process to:
- Reduce default on auto l**** due to fraud or misrepresentation on the application by up to 50%
- Increase loan pull-through by 30% or more
- Validate income accurately to reduce risk and eliminate stipulations and manual review for most applicants
- Identify the use of fake employers
- Improve dealer risk detection
Auto ONE includes Case Manager, which provides an intelligent layer of risk controls, automation logic, a rule engine, action guidance, and key metrics across the fraud investigation process in an elegant user interface to streamline investigative workflows.
“Point Predictive is constantly innovating and providing us with new ways to automate our lending processes to lower our cost of origination and better protect ourselves from fraud losses,” said Kevin Hawkins, CEO of MidAtlantic Finance. “We are pleased to expand our partnership.”
Case Manager is designed to deliver auto lenders the most modern, configurable, and extensive control over fraud in the marketplace today. It provides valuable operational efficiencies and robust capabilities, including:
- Configurable work queues. Better allocate resources and accelerate throughput.
- Rule engine. Easily write and modify rules to respond to emerging situations.
- Rule management. Define stipulations and other LOS actions with easy, click-based logic.
- Automation logic. Most rules for fraud risk management can be executed automatically.
- Case Creation. Easily create cases with synchronized loan application data.
- Filters. Easily view and manage subsets of loan volumes.
- Fraud Reporting. Track suspicious applications and monitor disposition.
- Live analytics. Access a detailed array of real-time operational metrics.
“Auto ONE enables our team to detect, investigate, and disposition fraud cases all in one place,” said Michael Pereira, Jr., Vice President of Lending Operations for MidAtlantic Finance. “It’s a powerful, one-stop-shop for managing all of our fraud investigations, and Case Manager streamlines our fraud investigation process. Having the ability to write and customize rules allows us to catch new fraud schemes faster and target areas where risk is higher.”
AI and ML News: AI: Continuing the Chase for Brain-Level Efficiency
Auto ONE leverages data from the largest automobile lending data consortium in the United States, purpose-built for risk management with more than:
- 120 million historical auto lending applications
- 12 billion application risk attributes
- 56 million unique consumers
- 100 million historical income reports
- 17 million employer records
- 6,500 fake employers
- 200,000 social security numbers tied to default
- 102 million social security numbers of deceased individuals
- $4.5 billion in l**** with early payment defaults
- $1 billion in l**** identified as fraudulent
“We are excited to grow our partnership with MidAtlantic and we know the expansion of our partnership is already delivering significant benefits to their team,” says Tim Grace, CEO of Point Predictive. “Auto ONE is transforming the auto lending process by centralizing important data to facilitate early fraud detection. Our consortium data and AI-based scoring enable MidAtlantic to address and resolve issues before l**** are funded.”
AI ML in Marketing: AI and Big Data Analysis Used to Find Brands’ Emotional Connection
[To share your insights with us, please write to sghosh@martechseries.com]
Comments are closed.