Identity Verification's Missed iPhone Moment

Published Date : 7/31/2025 

Explore why the identity verification sector is overlooking a groundbreaking opportunity, much like Intel did with the iPhone. Discover the untapped potential of behavioral biometrics and the barriers hindering their adoption. 

Almost 20 years ago, Intel famously passed on the offer to produce microprocessors for a new product of an up-and-coming startup with a fruit-inspired logo. Although the iMac and iPod had made Apple a household name, Intel’s rejection was, at least on its face, a good business decision. The PC market was stable and profitable; so-called “smartphones” appeared a passing fad.

Asian Samsung ended up supplying the microprocessors installed in the first iPhone models, and Intel’s choice—one of the worst good business decisions of the century thus far—became enshrined as a textbook example of the innovator’s dilemma, in which a company rejects disruptive innovation because it doesn’t fit their current business model.

The identity verification industry, I fear, finds itself in a comparable position to Intel’s in 2006.

Right now, most ID verification platforms activate in the middle of the onboarding funnel, typically in the form of phone verification, selfie uploads, or document scans. Only a subset of users ever get to the stage of eKYC such as uploading an ID, taking a selfie, etc. This means these companies are monetizing a fraction of user traffic and overlooking the opportunity present before any of those checks take place. That’s where untapped behavioral signals live: metadata, device patterns, usage cues. These signals can monetize users earlier in the funnel and provide their clients with more intelligence. Such “non-traditional” data consistently outperform baseline scores and can trigger alerts way before the actual ID verification starts.

This isn’t a novel insight. As early as 2020, even the traditionally conservative World Economic Forum acknowledged that digital footprints and behavioral signals could enhance identity frameworks by offering continuous, passive authentication and risk assessment. Around the same time, Gartner emphasized the importance of device, location, and behavioral data as core components of modern identity proofing. Behavioral biometrics were seen as a rare combination of low user friction and strong privacy safeguards, capable of detecting anomalies well before traditional ID checks begin.

And yet the industry continues to ignore them. Why?

How rational fears beget irrational consequences

As always, compliance is king, and compliance-related concerns create hesitation. The EU’s GDPR legislation has made companies wary of even anonymized and ostensibly privacy-compliant behavior biometrics. The U.S.’s Fair Credit Reporting Act (FCRA) compliance and explainability has the same effect on companies in the American market. If an algorithm can’t give a human-readable reason for a rejection, it’s not compliant.

Caution becomes paralysis. That’s a problem, since the fear of regulatory missteps often outweighs the reality. We’ve seen risk teams ignore statistically validated models—models that could save them millions of dollars—because they can’t trace the logic back to a traditional data source. In one case, a financial institution in Africa chose not to implement a fully compliant predictive scorecard. So far, they’ve suffered $1.2 million in losses that the scorecard predicted. Unnecessary risk-aversion doesn’t come cheap.

The hidden cost of saying No

It’s easy to scold business leaders on being too risk-averse, but that’s not a full view of the problem. Accountability also figures into these half-business, half-psychological calculations. In many institutions, no one gets fired for buying data from FICO, TransUnion or Equifax, even if it underperforms. Using alternative data sources on the other hand constitutes a personal risk. If it fails, the decision-maker is exposed.

This culture of defensiveness helps explain why so many businesses continue to rely on suboptimal tools, even when better options are available. No one wants to be wrong, especially if they feel it could jeopardize their otherwise good performance. Compounding the problem is how behavioral data is generally met with skepticism, as though typing speed or app usage patterns couldn’t possibly indicate financial reliability—despite the numbers saying otherwise.

At an industry event not long ago, I sat near the head of lending at a major neobank in southeast Asia. He was skeptical of behavioral biometrics’ relevance to risk assessment, so I asked him, “If we improve your model by even one Gini point, would you at least test it?” He said yes. Then again, his CEO was sitting nearby, and I still wonder if his answer would have been the same without that pressure.

It’s not just about the technology

As with Intel and Apple in 2006, this isn’t a technical problem. It’s a leadership one. It represents not only a failure of vision, but a comfort with existing, profitable trends and compliance measures.

Disruptive innovation rarely slots neatly into existing processes. That’s why it typically comes from the outside, made by people with no attachment to a given company’s current business model. What’s needed now is a shift in mindset toward a more honest cost-benefit analysis. Hesitation isn’t saving companies compliance headaches but costing them untold millions. Saying no is a financial choice.

The specter of the angry regulator, however unfounded, and the skepticism of the neobank C-suite is driving an industry-wide innovator’s dilemma. The technology is ready. It’s compliant and it’s backed by provable data. Companies ought to move forward with it. The ones that don’t might just live to regret it.

About the author

Michele Tucci is the Chief Strategy Officer and co-founder at Credolab, a global leader in device behavioral data and analytics. By delivering predictive insights and scores for credit risk, fraud prevention, and marketing, Credolab gives financial institutions a holistic view into every stage of the customer journey so they can make smarter decisions about onboarding, underwriting and communication. The company serves nearly 100 clients, including leading neobanks, credit bureaus, BNPL providers and identity verification companies across the U.S., Latin America, Asia, and EMEA. 

Frequently Asked Questions (FAQS): 

Q: What is the innovator’s dilemma?

A: The innovator’s dilemma is a situation where a company rejects disruptive innovation because it doesn’t fit their current business model, often leading to missed opportunities and potential long-term failure.

Q: Why are companies hesitant to adopt behavioral biometrics?

A: Companies are hesitant due to compliance concerns, such as GDPR and FCRA, and the fear of regulatory missteps. Additionally, there is a culture of defensiveness and skepticism towards non-traditional data sources.

Q: What are the benefits of using behavioral biometrics in identity verification?

A: Behavioral biometrics offer continuous, passive authentication and risk assessment, detect anomalies early, and provide low user friction and strong privacy safeguards.

Q: How can behavioral biometrics improve financial institutions' performance?

A: Behavioral biometrics can improve model accuracy, reduce fraud, and enhance user experience by providing more comprehensive and real-time data.

Q: What is the role of leadership in adopting new technology?

A: Leadership plays a crucial role in adopting new technology by shifting the mindset towards a more honest cost-benefit analysis and embracing disruptive innovation, even if it doesn’t fit existing processes. 

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