Risk-Based Authentication: Smarter IDV

Identity verification (IDV) is a critical component of modern businesses, protecting against fraud and ensuring compliance. However, a blanket approach to IDV – requiring the same stringent checks for every user – is both costly and detrimental to user experience. The solution? Risk-based authentication (RBA). This strategy, fueled by user segmentation and granular risk scoring, allows businesses to dynamically adjust the level of IDV based on the perceived risk associated with each individual user and transaction. This post explores how to implement a sophisticated RBA strategy for a more efficient and effective IDV process.

Key Takeaway 1: Traditional IDV is inefficient and expensive. Risk-based authentication focuses verification efforts where they are needed most, reducing friction for low-risk users and increasing security for high-risk ones.

Key Takeaway 2: Effective user segmentation is the foundation of RBA. Grouping users based on behavior, demographics, and transaction history allows for tailored security protocols.

Key Takeaway 3: Risk scoring provides a dynamic assessment of risk, enabling real-time adjustments to the IDV process. This ensures optimal security without sacrificing user experience.

Key Takeaway 4: Implementing layered security, incorporating multiple verification methods, strengthens defenses against increasingly sophisticated fraud attempts.

The Problem with One-Size-Fits-All IDV

For years, businesses relied on a standardized IDV process. Every user, regardless of their risk profile, faced the same hurdles – submitting ID documents, completing liveness checks, and undergoing potentially intrusive scrutiny. This approach presents several drawbacks:

• High Costs: Each IDV step incurs a cost. Applying these costs universally is wasteful for low-risk users.
• Friction & Abandonment: Complex IDV processes frustrate legitimate users, leading to cart abandonment and reduced conversion rates. Studies show a 15-20% drop in conversion for every additional verification step.
• Poor User Experience: Treating all users the same ignores the fact that some pose minimal risk.
• Ineffective Against Sophisticated Fraud: Fraudsters are adept at circumventing standard IDV checks.

User Segmentation: Knowing Your Customers

The first step towards RBA is dividing your user base into meaningful segments. Segmentation should be based on factors that correlate with risk. Here are some key segmentation criteria:

• Geographic Location: Users from high-risk jurisdictions may require more stringent verification.
• Transaction Value: Higher-value transactions warrant increased scrutiny.
• User Behavior: New users, users accessing from different devices, or those exhibiting suspicious activity should be flagged.
• Account History: Long-term, trusted customers should experience less friction than new registrants.
• Industry/Use Case: High-risk industries (e.g., online gambling, cryptocurrency) require stricter IDV.

For example, a user making a $10 purchase from a familiar device in a low-risk country might only require email verification. Conversely, a new user attempting a $10,000 transaction from a VPN in a high-risk region would necessitate full identity verification with liveness detection and potentially AML screening.

Risk Scoring: Quantifying the Threat

Once users are segmented, a risk scoring system assigns a numerical value representing the likelihood of fraudulent activity. This score is calculated based on a combination of factors, including those used for segmentation, as well as real-time data points like IP address, device fingerprint, and behavioral biometrics.

A robust risk scoring engine should:

• Be Dynamic: The score should update in real-time as new information becomes available.
• Be Customizable: Businesses should be able to adjust the weighting of different factors based on their specific risk tolerance.
• Integrate Multiple Data Sources: Combine internal data with external fraud intelligence feeds.

Implementing Layered Security with RBA

Layered security is essential for mitigating evolving fraud threats. RBA acts as the orchestration layer, determining which security measures to apply based on the user’s risk score. Here’s a potential tiered approach:

• Low Risk (Score 0-30): Email or SMS verification.
• Medium Risk (Score 31-60): ID document verification with basic data extraction.
• High Risk (Score 61-80): ID document verification, liveness detection, and face match.
• Very High Risk (Score 81-100): Manual review by a fraud analyst, potentially combined with additional data points.

This approach ensures that high-risk users face thorough scrutiny while low-risk users experience a seamless onboarding process. The result is increased security, reduced costs, and improved customer satisfaction.

How Didit Helps

Didit's all-in-one identity platform is specifically designed for implementing risk-based authentication. Our platform provides:

• Modular Architecture: Choose from 18+ composable modules (IDV, Liveness, AML, etc.) to build custom verification flows.
• Workflow Builder: Visually design and automate verification paths based on risk scores and user segments.
• Real-time Risk Scoring: Integrate with Didit’s risk engine or connect your own.
• Comprehensive Data: Access detailed risk insights and analytics to optimize your RBA strategy.
• Scalability: Easily adapt to changing fraud patterns and business needs.

By leveraging Didit’s platform, businesses can significantly reduce fraud losses, improve conversion rates, and enhance the overall user experience.

Ready to Get Started?

Don’t let a one-size-fits-all IDV strategy hold your business back. Embrace the power of risk-based authentication and unlock a more secure, efficient, and customer-friendly verification process.

Request a Demo to see how Didit can help you implement a robust RBA strategy.

Explore Didit’s pricing and start optimizing your identity verification today.