Reported adoption often starts too late in the funnel and misses the customers who never become digitally reachable.
Most regulated enterprises are measuring digitization wrong. Not because the numbers are false, but because the denominator is off.
Adoption dashboards typically start with customers who already made it into digital channels at least once. That sounds reasonable until you realize how many people it excludes: customers who exist on file, pay for products, interact with the business, but never activated an online login. In US banking, about one in three banked households did not use online banking in 2023. In healthcare, 38.7% of US adults never accessed a patient portal in the last 12 months.
If your dashboard starts at "active digital users," those people vanish from the metric entirely.
Why this is not just a UX problem
The tempting diagnosis is friction. Make the app easier and people will come. But the gap runs deeper than that.
Every customer who cannot sign up or log in digitally becomes more expensive to serve over time. They sit outside the reach of agentic AI, embedded finance, self-service support, and digital cross-sell. In regulated environments this compounds fast because onboarding and authentication are already more complex than in consumer apps. Extra verification steps, recovery flows, and step-up requirements create more places to fail.
The harder problem is that non-adoption is not one thing. Someone who abandons sign-up halfway through is a funnel problem. Someone who uses SMS OTP but never upgrades is a conversion problem. Someone with no digital profile at all is an identity problem. Treating all three as one adoption number leads to the wrong roadmap.
Why backend logs miss the real failure rate
Here is where most teams get surprised: over 80% of sign-up and login failures happen client-side and never reach the backend IdP at all.
That means backend success rates can look healthy while real users are dropping off on specific browsers, device types, or operating systems. The IdP sees a clean log because it only receives the requests that made it through. The failures stay invisible.
This is why authentication telemetry across client and server matters. Without it, teams redesign aggregate flows while the actual failures stay concentrated in one browser family, one device segment, or one acquisition channel nobody was watching.
What to measure instead
The metrics that connect authentication performance to business outcomes:
- Sign-up completion rate by cohort segmented by device and browser
- Login Success Rate (LSR) across the full authenticated surface
- Authentication Error Rate (AER) broken down by reason code
- Reach rate calculated against the full customer base, not just active users
- Time-to-first-authenticated-action as an onboarding health signal
These are not vanity metrics. Failed logins correlate directly with churn, support volume, and abandoned-session revenue loss.
One credential type will not fix this
Mobile-first customers may respond well to passkeys. Field workers often need options that do not depend on a personal smartphone. Privacy-averse users tend to prefer hardware keys or PIN-unlocked credentials over biometric binding. Some customers will still need supervised onboarding through channels they already trust, like a branch or call center.
The goal is not to pick the best authentication method. It is to maximize successful logins across the full customer base.
The key takeaway
The biggest blocker in regulated digitization is often not low engagement inside digital channels. It is the unseen population that never becomes digitally reachable in the first place.
Honest adoption numbers and a realistic path to closing the gap both start with the same thing: telemetry that captures the full authentication journey, not just the backend slice that already succeeded.
Find out more at corbado.com/blog/digital-identity-gap
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