People Data Labs: Professional Data – The Virtually Fraud Free Identity Layer Fintech Needs

With the rise of cybercrime, the ways in which the industry deals with identity are clearly not working. The culture around identity verification is less advanced in fintech than in other industries, and has recently moved to areas where they are responsible for their own due diligence. As such, fintech needs another layer of identity.

Stephen Labenbusch

In this another guest of the financial technology timesAnd Steven Labenbush, the principal product manager of the company People data Labs, argues that cybersecurity measures and the current identity of fintech lag behind the ability of contemporary fraudsters. Here, he presents a new approach to knowing your consumer and outlines a fraud-free solution that fintech companies should urgently seek to enforce.

Labenbush is the lead product manager for People Data Labs that manage PDL risk, fraud, and identity solutions. Prior to joining People Data Labs, he held senior positions at several Fortune 500 companies where he used identity analysis to create solutions that prevented millions from tax fraud, debt evasion, Medicaid fraud, and welfare fraud. Labenbusch holds a Ph.D. in human-centered design and engineering from University of Washington, College of Engineering. He has also participated in user research in IBM And Microsoft Conducted independent research funded by National Science Foundation.

As we head into 2022, two things couldn’t be more clear. First, fintech is poised to grow even faster around the world. Consumers are embracing an ever-widening range of financial services offered through digital platforms. Driven by a combination of convenience, a growing baseline for digital intelligence, and the demands of the Covid-19 pandemic, nearly 90 percent of all Americans now use at least some financial technology in their daily lives.

Second, fintech faces a major identity challenge that could hinder this growth. Fortunately, this solution already exists. New forms of data, particularly professional data, could form the basis for the new layer of verified identity needed to continue providing more sensitive financial services via fintech solutions. But first, a little context.

Why is the identity challenge increasing?

There is an old axiom that says, “If you are looking for fraud, follow the money.” As value continues to flow through fintech tools, fraudsters were sure to follow, and today’s fintech industry is awash with synthetic identities that complicate the delivery of critical services. Fintech providers need to be able to authenticate real users and weed out scammers. This necessity becomes more central as the fintech ecosystem expands.

Early financial technologies were built primarily to mediate the services provided by brick-and-mortar financial institutions such as banks. As a result, they have relied on the traditional physical identity verification that these institutions perform, such as reviewing driver’s licenses and other government documents via an in-person interview.

As fintech has moved beyond its reliance on traditional financial institutions, it has incorporated other traditional digital identity tools into its toolkit, but a lot of the data under those digital identities complicates identity risks as much as they solve them. The 20th century structures we used to define identity, such as credit head data or public records, do not meet the needs of 21st century identity.

As consumers continue to demand more sophisticated services from fintech, the industry has accessed other sources of identity data. Many providers rely on credit file data to verify and verify identities. However, credit files are already riddled with rampant fraud. For decades, synthetic identities have been used by bad actors to fraudulently establish credit relationships, and these synthetic identities are persistent, and continue to proliferate in any data source that relies on credit files. As a result, this data in isolation is inappropriate for the task.

How can professional data help?

While credit fraud is common, and its ramifications are throughout the financial ecosystem, professional data from resumes and other public and proprietary B2B sources is virtually fraud-free.

When was the last time you heard of someone trying to secure a job using an artificial identity? There is very little chance or incentive to use a completely false identity to get a job that the criminal wouldn’t come to do.

As a result, identities generated from this professional data containing details such as work history, educational background and even professional qualifications, can provide the necessary layer of context needed to verify real identities and eliminate synthetic identities from contention.

Along with the increasing consumer demand for fintech services, comes a commensurate increase in the use of fintech tools by businesses. As a result, it is increasingly important for fintech providers to understand not only individual consumer identities, as represented in things like credit scores, tracking cookie data, and device identifiers, but also their professional identity.

A professional identity that is formed around employment history can reveal the differences between a real client and a deceptive character; Help reduce risks and speed up all types of transactions.

In the past, when companies took a long time to consider identity at all, personal business identity and business identity were usually considered separate entities. The rise of entrepreneurship, mega-business, and property-driven online businesses is making it increasingly imperative to understand the person and the professional as a single business identity.

Including high-quality, professional data from a qualified provider can help bridge this artificial gap and create a more holistic view of the customer, or prospect that will not only help speed up transactions and reduce risk, but also open new markets that are unencumbered by old assumptions.

How to identify a data partner

If fintech plans to continue building the future of digital transactions, the industry will need to widen the aperture on the kinds of data sources it uses to understand and act upon identity. While credit profiles and other traditional consumer data sources will remain critical, fintech will need to find sources of accurate professional data to fully prepare their users for new services. Selecting data partners from the next generation of fintech providers will require evaluating data sources with new criteria:

  • QualityThe easiest way to find out if a third-party supplier is providing high-quality data is to find out where that data came from. The quality data partner must be willing and able to tell you how and where their data is sourced. and to demonstrate that the data is in full compliance with all relevant rules and regulations governing data collection, storage and use. The growth in fintech has led regulators to take a closer look at the industry and ensuring that data sources are above the board and fully compatible will help many of the major fintech players get through it.
  • freshnessWhile credit profile data tends to be permanent, professional data can change quickly. Every day millions of people change jobs, take on new roles, acquire new skills, and move on to new opportunities. The Quality Data Partner shall commit to reflect this data in a timely manner through regular updates of relevant records based on public and private sources.
  • Accessibility Even for seasoned companies with large product teams and highly skilled data engineers, integrating and building with data can be costly in terms of time, resources, and staffing. A quality data partner can help mitigate these costs by making data more accessible. Find a partner that prioritizes empowering engineers with APIs that detail important attributes of your business, such as those related to customer risk to provide more value without overburdening your team.


A new generation of fintech providers is poised to change the way people and businesses interact with one another. Fintech has moved beyond just brokering the services provided by legacy financial institutions and enabling a wide range of services completely unfettered by traditional banking and finance.

As a result, the demand for an understanding of identity and the exclusion of synthetic identities is much higher. To make this a reality, fintech will need to look beyond consumer credit and other forms of identity in the 20th century and embrace the next wave of data partners who can help them better understand their customers in a professional context, guiding them as they emerge. To tap into new relevant markets and audiences.

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