Onboarding Gen Z and thin-file customers: Improve pass rates

Sharmistha Das

Sharmistha Das

Head of Product – Data Solution

Gen Z is widely considered the most difficult adult demographic to verify in the United States: they expect the experience to be fast and mobile-friendly, and they often have a limited credit history.

As such, traditional IDV methods using credit bureau data alone lead to many onboarding declines.

We’ve written this article to help. In it, we’ll cover:

  • How to onboard Gen-Z and other thin-file customers
    • Avoid relying solely on credit bureau data
    • Use dynamic waterfalling between data sources to fill verification gaps
    • Prioritize digital footprint as a primary identity signal
    • Make onboarding mobile-friendly and as frictionless as possible
  • How GBG helps businesses optimize onboarding for hard-to-verify customer segments 

Ready to start onboarding more Gen Z and other thin-file customers? Discover how our Multi-Source solution and GBG Go, our all-in-one KYC orchestration platform we built based on 30+ years of identity verification experience, can help. Book a demo.

How to onboard Gen Z and other thin-file customers

1. Avoid relying solely on credit bureau data

Traditional credit data alone often falls short for Gen Z, individuals who are new to the country, and other thin-file customers with limited borrowing history. It creates unnecessary barriers for these genuine users, increasing false declines.

A stronger approach is to supplement credit data with alternative, authoritative signals, such as: 

  • Phone and email ownership
  • Rent and utility payments
  • Social Security validation
  • Educational credentials
  • Digital financial behavior

Together, these data points create a fuller picture of identity. For example, a Gen Z customer may lack a credit card but have a long-standing mobile number and consistent digital activity, which are both strong indicators of legitimacy.

2. Use dynamic waterfalling between data sources to fill verification gaps

Thin-file customers often fail verification not because they’re risky but because one data source alone doesn’t provide enough information. Without a waterfall approach, they may be declined too early or pushed into manual document review, which then adds friction.

With dynamic waterfalling, the system checks one source first, then automatically moves to others if necessary. This goes on until identity is verified or sources are exhausted. As a result, match rates increase without any additional user input needed. 

Even better, dynamic orchestration, using automated rules and real-time decisioning to coordinate how different verification steps are triggered, can route users to the most relevant KYC check based on their profile and adapt in real time based on partial matches or risk signals. 

For instance, a Gen Z user can be verified using alternate data sources like mobile & email intelligence instead of credit bureau header data for quicker verification.

3. Prioritize digital footprint as a primary identity signal

Gen Z customers often have stronger digital footprints than traditional credit footprints because they’re more likely to build their identities through mobile usage, social platforms and online transactions.

Signals that can provide current, reliable evidence of identity include:

  • Mobile numbers
  • Email accounts
  • Device behavior
  • Transaction history

Mobile numbers can be particularly valuable. Even if a customer changes addresses frequently, they often keep the same phone number, making it a reliable option for verification.

4. Make onboarding mobile-friendly and as frictionless as possible

Gen Z expect onboarding to be fast, intuitive and mobile-first. Every extra field or document request increases the risk of abandonment.

This means that effective onboarding flows should minimize manual inputs, use passive verification wherever possible, and deliver near-instant decisions. For instance, you can reduce reliance on document uploads by accepting Digital IDs where possible. You can also choose a KYC provider with a clean user interface for a better customer experience.

However, reducing friction doesn’t mean lower assurance. With multi-source data solutions and smart orchestration, you can maintain strong compliance controls while meeting Gen Z’s expectations for speed and simplicity.

How GBG helps businesses optimize onboarding for hard-to-verify customer segments 

We’re a global identity technology company with more than 30 years of experience in the identity verification space. 

Our end-to-end identity orchestration platform, GBG Go, allows you to verify legitimate customers in 195+ countries with more than 80 KYC modules delivered through a single API. Within the platform, you can enable Multi-Source data verification instantly, no new API integrations required, to unlock deeper data checks against thousands of alternative sources. 

Here are three reasons why businesses like Betway, Nike and Santander choose to work with us:

Access broader identity signals to verify more legitimate customers

 

 

Successfully onboarding Gen Z and thin-file customers starts with moving beyond credit data alone. By using alternative identity signals, such as phone and email intelligence or rent, utility, alternate financing or deposits data, we enable you to verify customers who may be underrepresented in traditional bureau records.

Using waterfall logic, these sources are accessed in a prioritized sequence, starting with the most relevant checks, then automatically progressing to additional sources only if needed. For example, if one source doesn’t contain the information needed to verify a user, the system moves onto another source. 

This helps verify more users passively behind the scenes and minimizes the need for document uploads or manual review, which keeps the onboarding experience fast and smooth for customers.

Use dynamic orchestration to optimize verification paths in real time

Static verification flows can create unnecessary friction and fail legitimate users. That’s why we built GBG Go upon dynamic orchestration: the system can use real-time decisioning to determine the most effective verification path for each user, routing them to the right checks based on context, risk signals and available data.

This approach allows you to introduce step-up verification only when needed, while genuine users move through the process with minimal interruption. By adapting in real time instead of relying on a one-size-fits-all flow, you can reduce friction and accelerate approvals while maintaining strong fraud controls.

 

 

Deliver fast, low-friction onboarding experiences built for digital-first users

Our platform’s sleek, user-friendly interface can be fully white-labelled, so every touchpoint – from data entry to verification – aligns with your brand while remaining intuitive for mobile-first users.

 

 

Behind the scenes, customizable routing lets you tailor verification flows to different user segments and continuously refine them through A/B testing. Combined with GBG Trust, which assigns real-time risk scores to help identify potential fraud early, you can route applicants quickly, fast-tracking genuine users while applying the right level of scrutiny where needed.

This improved user experience means fewer abandoned applications, higher conversion rates and onboarding journeys better aligned with how younger, digital-first customers expect to engage – all without compromising fraud controls or compliance.

How GBG helped a financial services provider boost ROI from 8:1 to 30:1 through advanced risk intelligence

A leading financial services provider was looking to strengthen its fraud prevention strategy as increasingly sophisticated fraud attacks began exposing gaps in its onboarding process. While the organization already used identity verification to confirm customer identities, it lacked the broader risk intelligence needed to identify potentially fraudulent applicants hiding behind seemingly legitimate credentials.

By combining our identity verification with intelligence from mobile numbers, email addresses, physical addresses and IP data, the client was able to assess not only whether an identity was genuine, but also whether it exhibited characteristics commonly associated with fraud.

Additional insights into mobile account tenure, account status, SIM swap activity and device information helped the client introduce risk-based decisioning and step-up authentication only when needed.

As a result, the company increased their identity verification and fraud prevention ROI from 8:1 to 30:1. Non-existent email addresses alongside address risk signals also delivered an increase in ROI from 16:1 to 23:1.

Read the full case study here.

Build an efficient onboarding process for hard-to-verify customers with our Multi-Source solution

Successfully onboarding Gen Z and thin-file customers requires more than adapting traditional verification methods – it means rethinking onboarding to include broader data coverage, intelligent orchestration and low-friction digital experiences. 

With our Multi-Source solution, you can build more efficient onboarding journeys for hard-to-verify customers while balancing conversion with compliance and fraud prevention at scale.

Book a demo to discover how we can help you improve your KYC onboarding process for Gen Z and other thin-file customers.

FAQs: Onboarding Gen Z and thin-file customers

You can increase pass rates without sacrificing security by using more than one data source for verification – especially when onboarding Gen Z workers and other digital natives who may lack traditional credit histories. Combining credit data with alternative signals, such as phone, email, device and government data, helps verify more legitimate customers while reducing false declines. 

For digital onboarding, dynamic orchestration can further improve outcomes by routing users to the most relevant checks and applying step-up verification only when risk warrants it, creating a smoother experience from day one.

Alternative data can support KYC compliance by strengthening identity verification when traditional data is incomplete – particularly for Gen Z employees (and even some millennials) who may not yet have extensive financial footprints. Signals such as phone ownership and utility data provide additional evidence to verify customers while supporting a risk-based, auditable compliance approach.

For Generation Z, prioritize data sources that reflect their digital behaviours, such as phone and email intelligence, smartphone usage patterns and device signals, rather than relying primarily on credit history.

As digital natives shaped by social media and the pandemic, Gen Z often engage differently from previous generations. This means that effective onboarding strategies for tech-savvy users should prioritise speed, mobile-first design and minimal friction. A strong onboarding program should feel intuitive on a smartphone and deliver instant feedback.

By combining alternative data with intelligent orchestration, organisations can create onboarding journeys that improve verification rates while also supporting retention and long-term engagement.