Partner Spotlight: ID Analytics

by | Published: Apr 17, 2018 | Last Updated: Apr 17, 2018

In this Partner Spotlight, we’re focusing on ID Analytics, a leading provider of credit and fraud risk solutions. Kevin King, Director of Product Marketing sat down to talk with us about fraud trends and insights, as well as share some product details with us.

Partner Spotlight - ID Analytics

How long have you been a partner of Zoot?

ID Analytics has been in partnership with Zoot for over a decade.

What specific issues does ID Analytics address?

ID Analytics focuses on providing fraud, credit and identity insights that help enterprises grow safely. Most of our solutions are designed for account opening – helping clients answer critical questions like: “Is this identity real?”, “Is the person who they say they are?” and “Will this person be able to pay me?”

What is the main benefit that Zoot clients will see when they integrate with an ID Analytics solution?

On the fraud side, the main benefits are going to be reduced fraud losses, decreased customer friction and lower operational expenses. The priorities of the enterprise and the strategy they apply to our tools will determine which of these benefits stand out the most.

On the identity side, benefits include better managing compliance challenges like KYC with our Comply360 tool to reduce external data costs, and often allow enterprises to approve a higher percentage of applicants.

On the credit risk side benefits include new account growth and improved pricing strategies.

What trends do you see, that Zoot clients should be thinking about?

I’ll stick to application fraud. We should be planning for an increased volume of attacks stemming from large-scale data breaches – the raw materials to steal an identity are simply more available, and more effectively packaged by hackers to identity thieves than ever before.

We should expect a continued rise in the sophistication of attacks from fraudsters entering the application fraud space, pushed out of credit card transaction fraud by the EMV migration. Finally, I think we must expect consumer’s tolerance for the fraud and authentication screens historically used by lenders to continue to decline.

That sounds scary – more threats and reduced consumer tolerance for defenses. But what I typically tell enterprises is that they should be transferring a large portion of that responsibility and stress onto companies like ID Analytics. The right partners will build the right tools and provide experts who can assist with the right strategies for those tools, to protect your business and your customer experience.

What’s the most impactful type of fraud you’re seeing? What do you think it will evolve into?

At the point of application, I think synthetic fraud is the most impactful simply because current defenses are the most vulnerable to it. For those who haven’t come across the term, Synthetic fraud refers to a form of application fraud where a criminal makes up an identity for an application rather than stealing one.

Done carefully, fraudsters can create plausible credit histories for these fake identities, allowing them to access a good amount of credit and services before ultimately busting out for large losses. I’m not sure if it’s driving higher losses than traditional identity theft – synthetic fraud is difficult to measure – but it’s the top-of-mind trend.

Looking forward, the evolution of fraud methodologies is almost entirely driven by the evolution of fraud defenses. In other words – fraudsters don’t change their approach until it stops working. On synthetics, the national credit reporting agencies have already taken some basic steps to close loop-holes which made it too easy for fake identities to quickly amass prime credit histories.

Additionally, we may see some regulatory updates on how SSN can be verified, which addresses a major weakness in our collective defense strategy for synthetics. These aren’t innovations as much as they are closed loop-holes, but they’ll make the crime harder to commit.

I can’t say for sure how fraudsters will react – it could be tweaking the methodology for creating synthetic identities, or it could be shifting their priorities and doubling down on identity theft.

Let’s talk solutions. How does your ID Network, and solutions like ID Score, work?

ID Analytics maintains a real-time, cross-industry repository of identity data known as the ID Network. The ID Network has nearly 3 billion applications for credit and services from U.S. consumers, along with performance on those applications (ex. Was the application approved, did it result in a fraud loss?).

This coverage stands apart from what the national credit reporting agencies provide through its breadth – in addition to covering key financial services markets, the ID Network sees nearly every wireless application submitted in the U.S. ID Analytics also has strong insight into subprime and online lending behaviors.

The ID Network is driving force behind all of our solutions, including our flagship application fraud solution, ID Score 9.5. ID Score 9.5 is a three-digit score that communicates the risk of an application being fraudulent.

Honed to detect applications submitted by identity thieves, ID Score interrogates each element of an identity on an application (ex. SSN, Name, Address…etc.) to evaluate the potential risk to an enterprise. Today, ID Score is the application fraud assessment trusted by 7/10 top U.S. financial institutions and 4/4 top U.S. wireless carriers.

What makes your solutions unique?

At the end of the day, enterprises buy our solutions because of performance – which we believe is best in class. Few, if any, of our solutions are adopted without a historical test comparing performance to that of our competitors’ offerings. That performance is driven by several factors, but I’ll focus on the two most critical ones.

We often say our solutions are powered by innovative analytics, but differentiated by data. The data aspect is obviously the ID Network – leveraging a data source which has a more complete and current view of how identities are behaving in the U.S. marketplace is a major advantage for all our solutions.

While many risk solution providers are beginning to embrace machine learning to assess identity and credit risk, ID Analytics has been utilizing sophisticated data science techniques since our foundation in 2002. The barrier for most vendors in this space hasn’t necessarily been mastering machine learning techniques themselves, but rather figuring out how to harness them in a way that provides clear transparency to enterprises, consumers and regulators.

Innovations early in ID Analytics’ history allowed us to overcome this hurdle, and in doing so, enabled us to leverage the cutting-edge techniques needed to extract maximum insight and value out of our data.

What problems can solutions like ID Score solve for Zoot clients?

ID Score falls into the category of an application fraud score, which naturally makes most people think of fraud loss avoidance. And that’s not incorrect – most of ID Score implementations are inspired partially by reducing losses. However, when we think about how application identity fraud impacts enterprises, you also must consider the cost and pain of inefficient existing fraud strategies.

How much operational expense does an enterprise spend on stopping fraud? It’s not uncommon for us to sit down with a lender or service provider and find that their operational expenses are higher than their fraud losses.

Organizations also must think about the degree of friction they put new applicants through to stop fraud. We often find existing fraud strategies take applicants through verification and authentication steps which degrade the customer experience. Application rates, particularly in digital channels, have reached astronomical levels – and even miniscule amounts of friction have an outsized impact on the likelihood of abandoning an application.

So, when we’re working with enterprises to develop application fraud strategies, these are the three pain points we’re focusing on – reducing fraud losses, minimizing operational expense and removing friction for legitimate customers. And while there are a range of best practices that help meet those goals, the foundation is always an improved ability to pinpoint risk and allow the clear majority of applications to proceed frictionless past fraud checks.

I’m unquestionably biased, but I’ve been running competitive tests of application fraud scores for over a decade, and most of the time ID Score is going to deliver the best available foundation for solving those problems.

Who is a good fit for your solutions?

Any enterprise that receives applications from consumers they have no previous history with and has to decide whether they want to do business with that individual, is a great fit. We’ve focused most of this blog on identity fraud – but there are a range of identity issues like KYC, and of course credit risk issues, which are challenging to address for consumers you’ve never dealt with before. ID Analytics is here to partner with those organizations; arming them with solutions that help them say “yes” more often.

Anything else you’d like to share?

Obviously, many best practices exist in the risk management world, but these days most of the challenges we’ve covered will be solved by analytic tools and technologies. I can’t over-emphasize the importance of testing multiple solutions and providers before choosing what to implement.

Fraudsters are constantly improving and innovating, and consumer’s expectations are always rising. Price will always matter, but it’s becoming increasingly risky to sacrifice solution quality for convenience or cost – the margin of error is just too small.

That means you should always be sure you’ve partnered with the right company on each individual use case you manage, and you should be highly skeptical of decisioning platforms that restrict your ability to identify and implement the best tools. That mentality is a big reason we’ve always enjoyed working with Zoot – and look forward to many future years of collaboration.

Conclusion

A big thank you to Kevin King, Director of Product Marketing from ID Analytics for these details and this excellent overview. For more information about additional products and services from this partner, please visit https://www.idanalytics.com/.

Want to learn more about integrating ID Analytics services into an existing or new Zoot platform? Please contact us today.

Post Categories: Fraud | Partner Spotlight

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