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How to identify fraud risks early in the origination process

First American Data & Analytics detects fraud risks in real-time

Jun 22, 2021 2:52 pm  By
First AmericanMortgage Fraud
Fraud word concept on cubes

Now, more than ever, lenders need a solution that creates more efficiencies so they can better manage high volumes. HousingWire recently spoke with Robert Karraa, President of First American Data & Analytics, on how lenders can better identify fraud risks and errors in mortgage applications.

HW: Fraud has been a hot topic as of late, how does First American Data & Analytics help lenders identify risks of fraud? 

ROBERT-KARRAA-10TU-1

Robert Karraa: Our company has been an established leader in fraud detection for more than 15 years. Our FraudGuard alert-based solution uses natural intelligence gained from millions of loan applications and eventual outcomes to assist underwriters to note abnormalities in application data. While still extremely effective, larger volume lenders expressed a need to create even more efficiencies in workflow and to help them focus efforts on the highest risk applications. This is why we introduced the AppIntelligence Score (AI Score) fraud solution earlier this year. AI Score is a powerful new fraud pattern-recognition score that enables high-volume lenders and investors to more precisely identify the risk of fraud and early payment default on both new mortgage applications or a portfolio. 

This highly accurate score significantly reduces review volume and false positives and uses proprietary predictive modeling to paint a truer picture of where fraud and early payment default risk are likely to occur. For example, loans with the highest AI Score, usually about 10% of total application volume, account for 50% or more of total fraud risk. This targeting enables lenders to focus their reviews on the most at-risk loans, while streamlining loan approvals and reducing operational costs.

AI Score uses our proprietary predictive fraud indices, employing both natural and artificial intelligence as well as machine learning technologies. It simultaneously runs proprietary sub-models for risk, including synthetic identity, income, employment, early payment default (EPD), undisclosed debt and loan participant risk review.  

The ability to analyze millions of alerts that underwriters have cleared and then feed that information back into the model, is what makes AI Score one of the most sophisticated models on the market.

HousingWire: You recently announced First American’s Data & Analytics Division. What does this rebrand mean for lenders? 

RK: At the end of last year, we rebranded our data division as First American Data & Analytics. The rebrand was the culmination of a multi-year effort to build a world-class, property-centric data operation that could deliver critical risk management, analytics, valuation and marketing solutions. First American Data & Analytics’ solutions enable lenders to make better, and increasingly automated, decisions to manage their workflow.

To give you a sense of our scale, we curate and maintain the nation’s largest dataset of property ownership information. That’s more than 7 billion recorded documents. And we’re adding more than 5 million new document images—more than 20 billion data elements—each month to the dataset. 

In 2020, more than half of all mortgage origination transactions relied on either our data or one of our analytic solutions. While mortgage is a big market for us, our division also serves other verticals: title, appraisal, government, FinTech, PropTech, retail, marketing, real estate, property services and education.

HW: What other products and services fall under the First American Data & Analytics division?

RK: Our flagship data platform, DataTree, would be at the top of the list. It is the industry’s most comprehensive source of property ownership and housing data as well as offering solutions for customer acquisition and market share reporting. We also have an extensive suite of APIs and other custom solutions that allow our customers to access any and all of our market-leading data sets in the format that best suits their needs. 

In addition to our data assets, we’ve assembled a number of industry-leading solutions that enable lenders and title companies to make better, and increasingly automated, decisions to manage their workflow, auditing and compliance operations and property research. Our other solutions include the RegsData loan compliance platform; TaxSource, one of the industry’s most comprehensive nationwide tax status reporting solutions; and a host of other analytics that provide solutions for valuation, appraisal management and more.

On the title side, we provide title search and examination automation solutions for title and settlement services providers as well as a nationwide offering of title production managed services. All of our title solutions are supported by the industry’s largest geographic collection of title plants. 

Finally, we have a broad—and expanding range—of valuation offerings, including AVMs and the ACI workflow solutions used by appraisers, lenders and AMCs.

HW: What’s new and what’s on the horizon at First American Data & Analytics?

RK: In addition to new solutions, like AI Score, we’ve also been focused on new ways to let users access data. FinTech and PropTech companies, for example, tend to be heavy users of our data. Increasingly, these clients are aggregating, enriching and consuming their data via the cloud on innovative platforms, like the Snowflake Data marketplace. 

Now a broader set of data consumers including FinTech and PropTech clients, can easily leverage the industry’s largest property and ownership dataset to drive advanced insights, reduce risk, build new analytics, test new concepts and power innovation in a cloud hosted environment. By moving access to the cloud, we are meeting our clients where they want to work with our data, so they always have the latest, most up-to-date data at their disposal.

First American Data & Analytics‘ tailored fraud solutions detect fraud risks and mortgage errors early on, so lenders can manage high volumes more effectively.

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