With cybercrimes growing, it’s clear that the ways the industry deals with identity aren’t working. The culture around identity verification is less advanced in fintech than in other industries, and it’s just recently moved into areas where they’re responsible for their own due diligence. As such, fintech needs another layer of identity.
In this guest post for The Fintech Times, Steven Lappenbusch, Principal Product Manager for People Data Labs, argues that fintech’s current cybersecurity and identity measures are falling behind the ability of modern fraudsters. Here, he puts forward a fresh approach to knowing your consumer and identifies a fraud-free solution that fintechs should urgently be seeking to impose.
Lappenbusch is Principal Product Manager for People Data Labs managing PDL’s risk, fraud, and identity solutions. Prior to joining People Data Labs, he held senior roles at several Fortune 500 companies where he used identity analysis to create solutions that prevented millions in tax fraud, debt evasion, Medicaid fraud, and welfare fraud. Lappenbusch holds a Ph.D. in Human-Centred Design and Engineering from the University of Washington, College of Engineering. He has also been involved in user research at IBM and Microsoft and conducted independent research funded by the National Science Foundation.
As we enter 2022, two things could not be more clear. First, fintech is poised to grow even faster all over the world. Consumers are embracing an ever-widening array of financial services delivered through digital platforms. Driven by a combination of convenience, a rising baseline of digital savvy, and the exigencies of the Covid-19 pandemic, nearly 90 per cent of all Americans now use at least some fintech in their daily lives.
Second, fintech is facing a major challenge around identity that could hamper this growth. Fortunately, that solution already exists. New forms of data, in particular professional data, can form the foundation of the new layer of verified identity needed to continue offering more sensitive financial services via fintech solutions. But first, a little context.
Why is the identity challenge growing?
There’s an old axiom that holds, “if you’re looking for fraud, follow the money.” As ever more value flows through fintech tools, fraudsters were sure to follow and today’s fintech industry is inundated with synthetic identities that complicate the delivery of critical services. Fintech providers need to be able to authenticate real users and weed out fraudulent ones. This imperative becomes even more central as the fintech ecosystem expands.
Early fintechs were primarily built to mediate services offered by brick-and-mortar financial institutions like banks. As a result, they relied on traditional physical ID verification performed by those institutions, such as reviewing drivers licenses and other government documents via an in-person interview.
As fintech has outgrown its reliance on traditional financial institutions it incorporated other traditional tools of digital identity into its toolkit, but much of the data underneath those digital identities complicates identity risk as much as it resolves it. The 20th-century structures that we’ve used to define an identity, like credit header 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 reached for other sources of identity data. Many providers rely on credit file data to verify and validate identities. However, credit files are already laden with endemic fraud. For decades, bad actors have used synthetic identities to fraudulently establish credit relationships, those synthetic identities are persistent, and continue to proliferate throughout any data source that relies on credit files. As a result, this data in isolation is inadequate to the task.
How can professional data help?
While credit fraud is commonplace, and its ramifications felt 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 a synthetic identity? There’s very little opportunity, or incentive, to use a completely erroneous identity to get a job the criminal won’t show up to do.
As a result, identities built from these professional data containing details like work history, educational background, and even professional qualifications, can provide the necessary layer of context needed to validate real identities and eliminate synthetic ones from contention.
Along with widening consumer demand for fintech services comes a commensurate increase in the use of fintech tools by businesses. As a result, it’s increasingly important for fintech providers to understand not just individuals’ consumer identities, as represented by things like credit scores, tracking cookie data, and device ids, but also their professional identity.
Professional identity formed around employment history can reveal the differences between an authentic customer and a fraudulent persona; helping to minimise risk and expedite all manner of transactions.
In the past, when businesses took the time to consider identity at all, the personal commercial identity and the business identity were typically considered separate entities. The rise of entrepreneurship, gig work, and proprietor-driven online businesses makes it increasingly necessary to understand the person and the professional as one commercial identity.
Including high-quality professional data from a qualified provider can help to bridge this artificial gap and create a more holistic view of the customer, or prospect that will not only help to expedite transactions and minimise risk, but also open new markets unencumbered by legacy 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 types of data sources it uses to understand and act on identity. While credit files and other traditional consumer data sources will remain critical, fintech will need to seek out sources of accurate professional data to fully contextualise its users and qualify them for new services. Choosing these next-generation data partners will require fintech providers to evaluate data sources with new criteria:
- Quality – The easiest way to know if a third-party vendor is offering quality data is to know where that data comes from. A quality data partner should be willing and able to tell you how and where they source their data. And to demonstrate that data is fully compliant with all relevant rules and regulations governing data collection, storage, and use. Growth in the fintech space has regulators taking a hard look at the industry and ensuring that data sources are above board and fully compliant will help many major fintech players pass muster.
- Freshness – While credit file data tends to be enduring, professional data can change quickly. Every day millions of people change jobs, take on new roles, acquire new skills, and relocate for new opportunities. A quality data partner should be committed to reflecting this data in a timely manner through regular updates to relevant records based on public and proprietary sources.
- Accessibility – Even for savvy businesses with large product teams staffed with 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 to mitigate these costs by making data more accessible. Look for a partner that prioritises enabling engineers through APIs that segregate attributes critical to your business, such as those pertaining to client risk to provide more value without unduly burdening your team.
A new generation of fintech providers is poised to transform the way individuals and businesses transact with one another. Fintech has moved beyond simply mediating the services provided by legacy financial institutions and into enabling a wide range of services fully untethered from brick-and-mortar banking and finance.
As a result, the demand to understand identity, and to weed out synthetic identities, is far higher. To make this a reality, fintech will need to look beyond consumer credit and other 20th-century forms of identity and embrace the next wave of data partners who can help them to better understand their consumers in a professional context, and guide them as they look to tap into relevant new markets and audiences.