Secure Onboarding: A 3-pillar Blueprint for the AI Age

Imagine you live in a house where changing the front door lock requires jackhammering the foundation, rewiring the electrical system, and rebuilding the entire porch. It sounds ridiculous, right? If a burglar manages to pick your lock, you’ll want to swap it out in hours, not months.

Yet, this is precisely how most financial institutions (FIs) are forced to handle consumer onboarding. Synthetic identities can look convincing on paper, and deepfake-driven scams can be generated and iterated quickly. The bigger issue for most banks is not effort or intent. It’s speed.

In this article, we’ll explore how financial institutions must prioritize agility for secure onboarding in the age of AI.  

Key Takeaways

• According to Datos Insights, 69% of fraud executives say outdated technology is their biggest challenge in preventing onboarding fraud.¹ 
• When new fraud threats emerge, many financial institutions often struggle to test new data sources or build orchestration sources.
• To ensure secure onboarding, FIs should implement a 3-point blueprint that delivers signal agility, dynamic resilience, and supports architectural coexistence. 
• Following this framework enables continuous improvement, resulting in better customer experiences, greater operational efficiency, and improved fraud performance.

How Banks Can Keep Pace with Emerging Fraud Trends 

Many organizations are trapped in a cycle of integration debt. When a new threat emerges, teams either scramble to test new data sources or try to build orchestration solutions in-house. Both paths can turn small changes into long projects that deliver too late. 

Data orchestration shouldn’t be a one-time integration project; it must be a continuous loop that lets you plug in, normalize, and deploy new data sources instantly. The answer is a new operating model for secure onboarding, one that moves beyond static identity to real-time data agility.

According to Datos Insights, 69% of fraud executives say outdated technology is their biggest challenge in preventing onboarding fraud.¹ They are fighting nimble, AI-powered criminal networks with rigid, hard-coded defenses.

The answer isn’t to buy new locks or engineer them yourself. It’s about putting a smart lock that continuously adapts to new threats.

To outpace AI-driven fraud without alienating legitimate customers, a secure onboarding program requires an orchestration layer that delivers three critical capabilities:

• Signal Agility. Use a universal API to access, orchestrate, and normalize any data source or risk signal, from legacy credit bureaus to real-time behavioral biometrics, without a code release. Integrate once, then plug in new sources quickly without engineering overheads. 
• Dynamic Resilience. Implement real-time, adaptive orchestration that sends the right signal at the right time, rather than every signal, every time. Swap, skip, or step-up verification checks in real time based on live risk signals, ensuring frictionless flows for low-risk users.
• Architectural Coexistence. Use a “wrap-and-modernize” approach that plugs into existing core banking systems, delivering next-gen orchestration without the risk of a “rip-and-replace” migration. Feed normalized decisioning intelligence into your existing risk engine today, or switch on Feedzai’s AI-native decisioning tomorrow. You choose how to consume the intelligence and unlock value at your pace.

1. Signal Agility: Move Faster Than Fraud

Traditional onboarding was built around static identity data. However, this same data is often widely available to criminals. Datos Insights reports that synthetic identity fraud is now the top concern for 56% of FIs, largely because these fake identities are convincing on paper.²

You must move from verifying data to verifying reality. This requires a universal API to connect to the entire data economy to access, orchestrate, and normalize any data source or risk signal. 

In practice, this orchestration layer should let you:

• Integrate once, and iterate fast. You should not spend months integrating a new data source only to discover it adds noise. Modern teams test suitability quickly, validate data quality early, and move on if it does not help.
• Keep vendor flexibility. Fraud, pricing, and performance all change. Abstracting decision logic from the underlying service lets you switch providers without rewriting your workflows.
• Expand signals beyond the static identity data. Signals like behavioral biometrics, device intelligence, and network intelligence patterns matter because valid credentials and clean personally identifiable information (PII) are no longer definitive proof of a genuine applicant. You need signals that help distinguish a human from automation and machine, and genuine intent from engineered deception.

Instead of a rigid, one-time setup that degrades as fraud evolves, secure onboarding creates a self-optimizing risk loop that instantly ingests new signals, refines them through standardized data archetypes, and bolsters your defenses in real time. You aren’t just building a workflow. You are building an immune system for your digital front door.

2. Dynamic Resilience & Intelligent Precision

Modern secure onboarding is about smart friction. Challenge fewer good customers, and apply stronger controls only when risk signals warrant it.

Two shifts matter most.

I. Pay for insights, not volume

A hardened enrollment flow routes applicants based on risk and confidence:

• Approve. Low-risk applicants move quickly with minimal friction.
• Risk-review. Uncertain cases get step-up verification or targeted checks.
• Decline. High-confidence fraud is stopped early.

This reduces unnecessary checks and protects conversion. In practice, banks can reduce waste by orchestrating expensive signals only when needed. Feedzai has seen some financial institutions reduce unnecessary data consumption by up to 20% by applying this strategy.

II. Build resilience into the flow

AI-era attacks evolve quickly, but so do operational realities: vendors fail, performance drifts, and conditions change.

A resilient onboarding program:

• Uses caching and chained workflows to mitigate single-source dependency, keeping onboarding smooth during third-party outages;
• monitors data drift and performance declines;
• maintains continuity so you do not have to choose between “open the gates” and “shut down onboarding.”

This matters because banks expect more fraud pressure in real time. Datos Insights reported that 90% of financial institutions expect real-time payment fraud to increase.

3. Architectural Coexistence: Flexible Deployment That Maintains The Core

“Modernization” often sounds like a multi-year rip-and-replace. But it doesn’t have to be. Keeping the core means you preserve the engines and systems you trust, while adding a layer that makes change faster and safer:

• Deploy anywhere. Feed decisioning intelligence into your existing risk engine today, then evolve at your pace.
• Give risk teams controlled agility. Reduce dependence on IT for every change with a self-serve, no-code UI while maintaining governance, approval flows, and auditability.
• Improve safely. Test data sources and strategies before rollout, then promote changes with clear versioning and rollback paths.

This is the difference between a program that updates quarterly and one that can respond to new fraud patterns quickly without breaking customer experience.

What Outcomes Look Like When The Operating Model Changes

When onboarding becomes a continuously improving system, the outcomes show up in three critical stages.

• Improved customer experiences. Faster application completions and fewer unnecessary interruptions for genuine applicants.
• Greater operational efficiency. Fewer manual reviews and lower cost-to-serve.
• Strengthened fraud performance. Better detection and fewer successful synthetic or impersonation attacks.

Datos Insights custom research and industry analysis references outcomes such as an 83% rapid completion rate, a 70% reduction in enrollment steps, $250,000 in operational savings, and a 23% decrease in fraud rates.

The key takeaway is not the specific metric for each bank, but the principle that agility drives cumulative progress: every step forward simplifies the next.

A Quick Maturity Check For AI-Era Onboarding

In the age of AI, secure onboarding is not about building the tallest wall. It’s about building the fastest reflexes, with strong governance.

To assess this question, ask your team the following questions:

• Can we add and validate any new signal quickly, without a long engineering cycle?
• Can we reduce friction for low-risk applicants while stepping up only when risk increases?
• Can we stay resilient during vendor failures and data drift?
• Can we deploy improvements without disrupting the core systems that run the bank?

If multiple answers are “no,” the opportunity is clear. The next step is to fix the operating model first, then scale better decisions on top of it.

In an era of synthetic identities and AI-orchestrated bot attacks, a static defense is insufficient. By turning onboarding into a proactive immune system, Feedzai enables banks to neutralize threats in milliseconds while providing legitimate customers with the frictionless experience they expect. 

Remember, it’s not about fixing your lock. It’s about upgrading your architecture.

Additional Resources

• Blog: What is Data Orchestration? Key Benefits and Concepts
• Webinar: Collaborative Data Exchange: The Next Frontier in Fraud Prevention
• Analyst Report: How Data Orchestration Unlocks Safer, Faster Account Opening
• Solution: Bank Account Opening Without the Friction