The following post is part of a series of blogs written by MeridianLink Partners who will be attending the MeridianLink LIVE! User Forum in May 2023. To learn more about the event, visit https://www.meridianlink.com/userforum.
There has long been a dependence on credit data for identity validation. Verification services often perform checks against the stores of credit information, then return a match/no-match. Clearly, there’s a wealth of that data available, but this sheer quantity itself presents its own challenges.
Also, criminals using combinations of fake and stolen PII result in the creation of new CRA records with every fraudulent application, making the fraudulent identity appear to be adequately legitimate to pass future identity checks. This further complicates matters for victims whose identities have been compromised.
Even more costly is synthetic fraud, wherein completely manufactured identities are associated with stolen elements of real identities. With no real person to get an alert from a bank or credit issuer, these avatars can exist in various companies’ databases for months or even years, building up history and credit limits and then maxing out the loans or credit cards and disappearing.
How do we eliminate these vulnerabilities?
The Socure Solution: Not Just Data, but Intelligence
At Socure, we curate a considerable amount of data, but even more importantly, we believe in precision over volume. So, what does that mean?
We regularly source feedback data from our 1,700+ customers across the financial ecosystem and a multitude of other industries, along with the outcomes of hundreds of millions of applications, to continually learn and refine “good” and “bad” applicants. We then apply advanced machine learning against this data to build validation models that recognize the good from the bad. It’s not just about catching criminals—it’s about the most accurate possible classification. Good applicants get in, bad ones are kept out.
Another advantage of our approach is resolving multiple dimensions of an identity, using many sources for each element. Each consumer is evaluated as a whole, not simply as disconnected pieces of PII. This significantly cuts down on false positives and defends against the cleverest of crooks who combine stolen and fake data.
In this way, Socure isn’t dependent solely on commonly available data, but rather the intelligence gleaned from the curated information from across the digital economy.
Validating good applicants means they enter the system with little friction so that they can receive the best offer available and transact immediately. Recognizing bad applications at the outset means getting them out of that same system with equal speed to reduce fraud losses and downstream operations expenses. By quickly placing applicants into one bucket or the other, we automatically and drastically reduce the number of people who are subjected to additional friction, such as KBA or costly manual review.
Helping Smaller Organizations Grow
Socure’s solutions are purpose-built for the most accurate identity classification on the market. We are not data brokers—we are an AI-based, low-code, holistic platform designed specifically to help financial organizations grow their business by auto-accepting the greatest number of worthy applicants while improving fraud capture rates and vastly reducing the friction that adds to costs and can drive away business.