Navigating the Evolving Fraud Landscape with Explainable AI-Based Detection

In an era where fraudsters continually refine their tactics, businesses face an uphill battle in distinguishing between legitimate and fraudulent user requests. To fill the gaps in detection, companies often employ a variety of fraud detection solutions. However, managing multiple solutions from disparate vendors can be costly, unwieldy and hard to scale. 

And while AI-based fraud detection enables better protection against emerging threats, not all AI-based anti-fraud solutions are built alike. This blog post will explain the benefits and challenges of AI-based anti-fraud detection and how it works on the Transmit Security Platform.

Evolving Fraud Tactics and the Limitations of Traditional Solutions

Amid the increased use of automated frameworks to scale attacks, organized crime, and a lower barrier to entry thanks to organized fraud rings and the rise of generative AI, fraud is becoming more sophisticated, with tactics that change by the day. 

But traditional anti-fraud solutions, which rely on predefined static rules and algorithms that require significant expertise to create, only work well on common and current fraud types that fit within known fraud patterns, making it difficult to detect new and emerging MOs.

To adapt to these threats, today’s solutions need to discern intricate usage patterns by integrating risk signals from diverse, ever-evolving sources — a task that requires the use of sophisticated AI-based solutions. 

The Double-Edged Sword of AI-Based Solutions

Unlike traditional systems, AI-driven solutions harness machine learning algorithms to detect unusual patterns and anomalies that signify both known and unknown threats, unifying various detection methods into a single risk engine for more comprehensive protection.

But while AI offers agility and comprehensive detection capabilities, it is not without its challenges. The ‘black-box’ nature of some AI systems, which often deliver a risk score or recommendation without context on the reasons for the decision, can hinder transparency and explainability in fraud investigations. Moreover, integrating AI-based detections with other data sources and standardizing risk scores across different solutions can be complex — making tuning decisioning and customization for unique business logic a difficult task. 

Benefits of AI-based detection:

• Protection against attacks designed to evade specific detection methods
• Vendor consolidation that reduces costs & complexities 
• Anomaly detection to detect novel attack patterns 

Challenges of AI-based detection:

• Difficulty explaining decisioning 
• Tuning false positives and negatives
• Customization for unique business logic
• Integrating and standardizing existing solutions & data sources

How Transmit Security improves AI-based detection

Transmit Security’s explainable AI-based detection is complemented by a powerful fraud orchestration engine that harmonizes its own risk scores with existing data sources to return unified, actionable recommendations. In addition, each recommendation is accompanied by the top reasons for each recommendation, simplifying fraud investigations and reporting. 

This allows businesses to expedite their ability to build, test and optimize complex journeys that automatically reduce friction or trigger challenges and step-ups based on the level of risk in each request. And through industry-leading orchestration, enterprises can shorten development cycles by testing and deploying controls using low-code tools.

With it, enterprises can: 

1. Improve detection using a centralized decisioning engine that leverages the full context of up-to-date threat intelligence, application usage patterns and individual user behavior to pinpoint anomalies. 
2. Tune and customize decisioning by providing self-service feedback on false positives and negatives with our Labels API, customize how algorithms respond to different threat types with detection sensitivity tuning and implement unique business logic with our Rules API.
3. Identify gaps in detection using our attack simulator to understand what different threats targeting their systems look like and leveraging generative AI to explore risk scores, users, devices, applications and attack types through natural language queries. 
4. Orchestrate real-time controls against emerging threats with natively integrated identity proofing, adaptive authorization and risk-based authentication capabilities that can be called with a single decision based on the level of risk and the application’s unique needs. 

Enhancing security and trust with robust fraud reduction

Transmit Security’s AI-driven detection enhances fraud detection with transparent decisioning, comprehensive analytics and seamlessly integrated customer identity security services, underpinned by industry-leading orchestration that connects effortlessly with any external data service or source.

This enables businesses to effectively tackle sophisticated and emerging threats,  shifting from temporary, reactive measures against known threats to a continuously updated, cohesive solution that can either complement or replace existing systems.To find out how Transmit Security can help your company, contact Sales for a personalized demo or read our case study on how a leading US Bank achieved a 1300% ROI by reducing fraud-related expenses.