< Our podcast: Interchange

Data is the New Oil So Who Is Protecting It?

Zach Anderson Pettet
Host
Date Published
(
July 13, 2021
)
Listen Time
(
25
min
)

Our guest this week is Riddhiman Das, Chief Executive Officer @ TripleBlind. We cover the advent of Enterprise Data Privacy as a Service, Riddhiman's experience at Ant Financial uncovering the problem that TripleBlind solves today, and what the future holds for privacy in financial services.

You can find Interchange on Spotify, Apple or your favorite podcast platform.

There is truth to the new saying “data is the new oil.” That metaphorical oil, data, drives everything from our business decisions, our ad budgets, and company strategy.  But how do we protect our data, make it portable, and make our data work for us? That’s still a big question in the technology world today.

Enter: TripleBlind, the Enterprise Data Privacy as a Service company. The easiest way to describe who they are and what they do is to think of them as the HTTPS of private data sharing. Banks, brands, and companies in a multitude of industries can unlock new revenue opportunities while automatically enforcing compliance with GDPR, HIPAA and other privacy regulations.

Bond, as an example, is building into the Embedded Finance space. But, at our core, we consider ourselves a data company. As we look around at the industry, we see data being underused and even misused.

We sat down with Riddhiman Das, Chief Executive Officer at TripleBlind, to discuss his history in deep tech, the problems in data privacy, and what the future holds for data privacy in financial services. Before starting TripleBlind, Das was a key member of the team that scaled Zoloz to eventually be acquired by Ant Financial. We cover his time and learnings at both companies.

Check out our four key takeaways below from our conversation with Riddhiman.

Go Slow to Go Fast

When the Zoloz (previously EyeVerify) team started working on their retinal-based biometric ID system, they started with one of the most expensive cameras on the market and it took over two hours to verify someone’s identity with the technology.

There was no commercial scenario where that cost or time was going to be acceptable, but they started slow and kept iterating. Looking forward in time, Das explains that it was unbelievable to him how “in 2012, the technology was running 300 milliseconds on a front-facing camera of a smartphone.”

The continuous iteration and obsession with form factor led Zoloz to be the first American company acquired by Ant Financial.

Find the Experts

Zoloz had a groundbreaking piece of technology. But, they still needed to find product market fit.

The team decided to join the Wells Fargo Accelerator as they had a thesis that retinal based biometric technology could be a good fit for the banking industry. Despite this thesis, Das admitted that they learned through the accelerator that “we (Zoloz) are not banking experts.”

They joined the accelerator specifically because they weren’t banking experts. “We were biometrics experts..but we didn’t know how that would apply to a bank directly,” Das explained.

Joining the Wells Fargo Accelerator, learning “how to speak bank,” and understanding how they fit allowed Zoloz to scale to hundreds of financial institutions in short order.

Data Doesn’t Speak to Data

One of the most significant problems in modern finance is the siloed nature of the data across the thousands of financial institutions in the world. Not only is data siloed by financial institutions, but in many cases, the data is siloed by a department within one single organization.

This is an obvious problem for cross-selling, KYC, and a number of other things bankers concern themselves with. “Around 96% of enterprise data goes under-utilized,” Das explains.

On a societal level, this is a money launderer's dream. As Das points out, “no one just uses one bank. I may have a credit card from one financial institution, a checking account at another, and a mortgage at yet another.”

If Bank A’s data set can’t communicate with Bank B’s data set, how could we ever catch money laundering at scale?

This is where point #4 comes in.

Use Third Party Data Safely

“Historically, we’ve only used first party data,” Das explains. TripleBlind allows organizations to add third party data to these algorithms safely. And, of course, he concludes that “the more variables you’re able to use and the more data you’re able to use, the better your models are.”

Companies like Bond and TripleBlind are laser-focused on building technology to empower new entrants in the financial ecosystem. Data use and security is one of the core tenants on this mission.

If you’re interested in building technology that levels the playing field in finance, let’s chat.

Reach out to zach@bond.tech or check out our careers page and let’s chat!

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