Kevin King Kevin King has nearly a decade of experience in credit risk and fraud analytics, having served in a variety of roles at ID Analytics since joining the company in 2007 including analytics, business analysis, product strategy and professional services. In each of these roles, King has focused on applying ground breaking analytic tools to the unique financial services challenges, and has directly supported projects at top 10 banks, several “Big 4” wireless carriers, the two leading U.S. satellite television companies, and multiple leading cable and internet providers. A driving force behind ID Analytics’ thought leadership program, he has authored several thought leadership whitepapers on a range of topics spanning fraud, credit and identity risk. King holds a B.A. from the University of Colorado.

The walking dead: A study on the use of SSNs belonging to the deceased

From 2018 – 2019 ID Analytics identified a notable increase in the use of Social Security numbers (SSNs) belonging to deceased individuals on new applications within our ID Network®, a unique cross-industry repository of consumer information. ID Analytics executed a …

Identity fraud detection: Untangling first-party fraud and synthetics

Brandon opens a new credit card account. He begins making purchases, racking up significant debt, never pays his bill and can’t be located by the credit issuer when they attempt to collect on the account. Is this first-party fraud—a standard …

Is identity fraud becoming a leading economic indicator?

Economists continue to debate whether the next recession is around the corner or several years off. In recent months, ID Analytics has observed an interesting trend – fraudsters appear to be behaving as if the economy is already in a …

The value of alternative credit data in separating risk on the margin

In my last blog, I discussed how the use of alternative credit data has become a mainstream answer to the challenge of identifying creditworthy consumers who are credit invisible. While that is perhaps the most familiar use case for risk …

Alternative credit data case study: Top-ten card issuer uncovers credit invisibles

Almost one-fifth of adults in the United States face obstacles to obtaining credit because they are considered “credit invisible”—meaning they either don’t have a credit history with, or are treated as unscorable by the nationwide consumer reporting agencies. Leveraging alternative …

Combatting synthetic identities: Finding the ghosts haunting your enterprise

There’s a ghost in the room—synthetic identity fraud—and unlike the elephant, everybody’s talking about it and not sure what to do about it. Our recent blog series provided an overview of the different types, complexity and magnitude of the evolving …

Synthetic Identities: Part Three, A Fraud vs. Credit Risk Perspective

Our previous posts examined the different types of synthetic identity fraud, including manipulated and manufactured, which vary in construction, intent and degree of financial harm. Part three of our series examines how the diversity in synthetic identity behavior impacts …

Is Your Fraud Strategy Ready for Black Friday?

Black Friday is quickly approaching and the weekend shopping forecast is bright. Consumer spending is expected to increase by 47% from the same period in 2016.1 This time period includes Cyber Monday, which holds the record for the largest …

Finding the Right Fit: A Fraud Strategy without Compromise

Businesses today are seeing a greater volume of fraud attacks at account opening than ever before,1 and with valid personally identifiable information readily available from data breaches, application fraud techniques are becoming more sophisticated and widespread.2 This puts …

Growing P2P Marketplace Through Evolved Fraud Management

When most organizations think about deploying origination fraud strategies, the focus is often on reducing losses and trimming operational expenses. The marketplace or peer-to-peer lending industry is not like most industries. The pain this industry feels by each successful fraud