Identity Verification During Customer Onboarding: 5 Failure Points & Best Practices

Identity verification is now a core part of customer onboarding. But when identity data collection and verification are poorly designed, they create friction instead of trust. Manual data entry, slow review, repeated capture attempts, limited onboarding channels, and weak fraud controls can all drag down conversion or expose the business to unnecessary risk.

This article breaks down the biggest customer onboarding challenges related to identity verification and the customer onboarding best practices that help solve them without adding unnecessary friction for legitimate users.

Manual form filling is one of the fastest ways to lose legitimate customers during onboarding. In many onboarding flows, users are being asked to re-enter information that already exists on their passport, ID card, or driver’s license. If users have to type in names, document numbers, dates of birth, and other identity data by hand, the process becomes slower, more frustrating, and more prone to input errors.

This is especially challenging in regulated industries, where businesses are required to collect specific identity data and verify it as part of onboarding. The goal is not to remove data collection, but to reduce manual input as much as possible.

The most effective fix is automated document data capture. Instead of asking users (or employees) to type in document details, the system can extract the required fields directly from the identity document and fill in the forms automatically.

You can implement automated data entry in both brick-and-mortar and online scenarios.

In-person customer onboarding strategy: Use compact devices like passport readers. The operator scans the document, and OCR technology automatically enters the relevant data into the system. This leaves customers only to put their signature on the page.

Digital customer onboarding strategy: Implement specialized SDKs that can enhance your app with identity document reading capabilities. These solutions use OCR technology to automate data extraction and entry from a submitted identity document. 

Some, like Regula Document Reader SDK, can also identify the document type upfront, removing steps such as “Choose your country” and “Choose your document type,” which helps reduce friction and improve conversion.

Poor capture in remote onboarding, where its quality depends on the user’s device, lighting, and camera behavior, can derail the process even when the user is legitimate and willing to continue. This applies to both document and biometric capture in flows that require a selfie check. 

If the image is blurry, cropped, affected by glare, or captured at the wrong angle, the system may not be able to complete the check reliably. That usually means repeated attempts, extra friction, and a higher chance of drop-off.

The best fix is to detect quality issues early and guide the user in real time. Document capture tools can flag blur, glare, poor framing, and other problems before the image enters the verification flow. Some, like Regula, can also improve the image automatically, for example by deskewing a document shot at an angle or removing glare.

Manual review is often one of the main reasons onboarding takes longer than customers expect. When submitted identity data has to be checked by an employee before a decision is made, even low-risk applications can end up waiting in a queue. 

For the user, that delay creates uncertainty. For the business, it increases the chance that a legitimate prospect will abandon the process before onboarding is complete. This issue is especially visible in digital onboarding, where customers expect fast decisions and have little patience for unclear waiting times.

The most effective way to reduce review delays is to automate the repetitive checks. That includes document data extraction, authenticity checks, data consistency checks, and biometric matching. The goal is not to remove human review altogether, but to reserve it for suspicious cases and edge scenarios that genuinely require judgment.

For example, Regula Document Reader SDK can extract identity data, cross-check it across the visual zone, MRZ, barcode, and RFID chip where available, and compare the submitted document against the expected layout and security features stored in its template database. Combined with Regula Face SDK for face matching and liveness checks, this allows businesses to verify both the document and the person presenting it in one flow.

Together, these automated checks help detect inconsistencies, formatting anomalies, signs of tampering, and impersonation attempts early in the process. As a result, straightforward cases can move forward faster, while suspicious submissions are escalated for manual review.

Some onboarding flows lose customers before verification even begins because the process is only available through one channel. If users can only onboard in a branch, only in a mobile app, or only on the web, some legitimate prospects will drop off simply because that path doesn’t work for them.

In practice, higher conversion often depends not on having more channels, but on giving customers at least one workable path and one fallback path. Depending on the business model, that may include mobile apps, web onboarding, branch workflows, or even self-service kiosks.

At the same time, supporting multiple onboarding channels can create operational complexity. Separate tools, fragmented logic, and inconsistent user flows are harder to implement and maintain. That is why many businesses prefer a provider that can support several verification touchpoints within one ecosystem.

For example, Regula offers document reader devices for in-person onboarding and web and mobile SDKs for remote verification of ID documents and biometrics. It also provides an identity verification platform that helps orchestrate verification workflows and manage multiple solutions, including third-party ones, from a single application.

Weak fraud controls create a different kind of onboarding failure. Instead of losing legitimate users through friction, businesses risk approving potential fraudsters. If the onboarding process cannot reliably detect forged documents, impersonation attempts, or biometric spoofing, fraudulent applicants may gain access to services under a false identity.

Fraudulent onboarding can lead to direct financial losses, higher operational costs, compliance issues, and reputational damage, especially in industries where trust and customer due diligence matter.

Businesses need layered identity verification controls to reduce the risk of deepfakes, forged documents, and other sophisticated fraud attempts. The key is to combine multiple checks rather than rely on any single signal.

Identity data can be cross-checked across the visual zone, MRZ, barcodes, and RFID chip where available to detect inconsistencies and signs of tampering.

In remote onboarding, a zero-trust-to-mobile approach adds another layer of protection by re-verifying RFID chip data on a server within a secure perimeter instead of trusting the mobile device alone.

Biometric verification also plays an important role. Face matching and liveness checks help confirm that the person presenting the document is real and matches the claimed identity.

In high-security in-person environments, dedicated document readers can further strengthen fraud detection.

A stronger approach is to combine document, biometric, geo, IP, device, and behavioral signals in real time and adapt verification controls based on risk. For example, unusual device patterns, repeated failed attempts, or inconsistencies across signals can trigger stronger checks or a higher-assurance flow. 

Where onboarding also includes compliance screening, the same orchestration layer can support related checks, such as KYC, AML, and PEP, alongside identity verification. Regula’s identity verification platform supports this kind of orchestration across verification workflows and tools.

Together, these controls improve fraud resilience without turning onboarding into a manual process.

Identity verification can either strengthen customer onboarding or become the reason it breaks down. In most cases, the same five problems appear again and again: too much manual input, too much waiting, poor capture quality, limited onboarding paths, and fraud controls that are too weak for the level of risk.

Regula supports this with document verification, biometric checks, and workflow orchestration across remote and in-person channels. For teams building a broader onboarding stack, the same workflow can also include related checks such as KYC, AML, and PEP screening.

Talk to our team to see how it could work in your specific onboarding flow.