A 7-Step Enterprise Fraud Framework to Redefine Scam Prevention

Scams (or authorized push payments) are the scourge of the day.

While no formal figures exist, it is estimated that the global scam losses exceed $1 trillion per annum. Organized crime is at the heart of this increase, with some estimates putting 1.5 million employed as professional scamsters.

The rising professionalism of the scamsters, the availability of “off the shelf” scam tools (e.g., phish kits), the very high “gross margin”, the increasing digitization of customer experiences, and inadequate law enforcement are all contributing to a continued increase in scams across the world.

The regulatory expectations, and the associated cost of compliance, vary by market. The most extreme position exists in the UK, where financial institutions are liable for up to £85k in almost all cases. Most regulators are examining the “Shared Responsibility Framework” framework, and it is reasonable to assume that FIs will have to bear an increasing share of this cost.

Customer expectations prize fraud defenses when selecting a FI. In a global survey of 1,600 customers, some 60% ranked “Good Fraud Protection” as either their top or the second priority. This was followed by “Ease of Use” (43%). While seemingly at odds, these two are the opposite sides of the same coin. Effective scam detection, measured by a high value detection rate at an acceptable level of false positives, becomes a key business growth imperative.

7 Steps to Scam Prevention

There is no one silver bullet defense against scams.  The ideal scenario – a fully alert customer – remains unrealistic.

Instead, effective defense requires a multi-layered strategy. The following 7-step framework offers a practical, intelligence-driven approach toward scam defense.

1. Understand Customer Susceptibility
   The framework begins with proactive assessment of customer vulnerability through sophisticated susceptibility scoring. This involves harvesting both monetary transactions and non-monetary events across all customer touchpoints to create always-on customer profiles. This requires an applied intelligence platform that enables real-time assessment that evolves with each customer interaction. (Note: This approach needs to be vetted against local privacy and permissibility requirements.)
2. Create Robust Customer Personas
   By developing personas that reflect psychographic and behavioral characteristics, institutions can assess specific scam vulnerabilities. For example, customers with high investible income who engage in cryptocurrency trading may be particularly susceptible to investment scams. Knowing customers helps to protect them.
3. Deploy Targeted, Personalized, Proactive Communication and Education 
   Generic scam warnings prove largely ineffective. The framework emphasizes hyper-personalized, contextual messaging aligned to individual risk profiles and scam types, creating more informed and alert customers. Breaking the scammer's spell is critical.
4. Alert and Amplify with the Susceptibility Score
   At the heart of scam detection lies sophisticated monitoring of customer behavior and activity. The framework recommends multi-layered decisioning that first identifies anomalies, then determines whether they're associated with scams or traditional fraud. Enterprise fraud capabilities can "amplify" transaction scores based on customer susceptibility and personas.
5. Build Dynamic In-Journey Engagement
   Understanding that customers in "hot states" often ignore generic warnings, the framework emphasizes dynamic, personalized dialogue that creates appropriate friction and reflection opportunities. This may include cooling-off periods or post-transaction follow-up when customers are more receptive.
6. Close the Back Door 
   Since stolen funds must flow through mule accounts, the framework emphasizes real-time intervention capabilities beyond traditional anti-money laundering controls. This requires transitioning from monthly batch assessments to instantaneous monitoring and account freezing.
7. Collaborate across the Ecosystem 
   Build a formal ecosystem across the regulator, law enforcement, telcos, social media platforms, and industry bodies to facilitate data sharing and best practice. This is probably the hardest task.

Download the complete 7-step framework whitepaper as a roadmap for transforming scam prevention from compliance obligation into strategic advantage.

How to Operationalize the Enterprise Fraud Framework

Scam prevention demands more than traditional fraud controls — it requires a sophisticated, data-driven platform capable of analyzing vast volumes of signals in real time, while maintaining the right balance between customer protection and experience. FICO operationalizes this framework by integrating advanced analytics, orchestration, and engagement capabilities across the customer lifecycle.

Dynamic Profiles

FICO® Platform continuously ingests non-monetary and transactional data, integrating third-party APIs and behavioral data to maintain evolving customer profiles. This dynamic view enables institutions to measure scam susceptibility in context and detect emerging risk patterns early.

Speed and Throughput Capacity

With the ability to process tens of thousands of transactions per second, the system ensures risk assessments and customer interventions occur instantaneously — essential when scam funds can move within seconds.

FICO^® Marketplace Integration

FICO Marketplace is a digital data hub created to give FICO Platform users easy access to third-party data providers via API connections. Specialist risk-signal providers — such as behavioral analytics, device intelligence, and telecom data — can be seamlessly integrated into existing decision flows. This open approach ensures access to best-in-class capability and agility in adapting to new threat vectors without extensive redevelopment.

Transactional Composition

Transaction compositions represent a state-of-the-art orchestration capability, allowing institutions to “compose” complex workflows that link signals, models, policies, and actions across the enterprise. This enables a consistent, explainable, and adaptive approach to scam detection and prevention across all channels.

AI and Machine Learning

Gain access to FICO consortium models, along with FICO’s award-winning detection model with a dedicated scam score. Regionally available insights like Scam Signal can also provide valuable intelligence for scam management.

Omni-Channel Engagement

Use built-in customer communication capabilities that leverage the customer’s channel of choice. Effective scam prevention requires seamless communication across preferred customer channels — mobile apps, SMS, email, or voice. Built-in customer communication capabilities enable real-time channel transitions, ensuring scam warnings reach customers in context while minimizing friction and maximizing impact.

The Path Forward

The scam epidemic represents an existential threat to customer trust and institutional stability. Financial institutions that wait for regulatory mandates or perfect solutions will find themselves at a significant disadvantage.

Success requires ruthless measurement and tagging of both structured and unstructured data to create virtuous feedback loops. Equally critical is constant engagement with operations teams and active monitoring to assess new vectors and anticipate emerging attack patterns.

As the threat landscape continues evolving, financial institutions must embrace proactive, intelligence-driven strategies that protect customers while maintaining operational efficiency. Use the seven-step framework whitepaper as a roadmap to transform scam prevention from compliance obligation into strategic advantage and position for success in an increasingly complex risk environment.

Learn More about How FICO Can Help You Stop Scams

• Download the 7-step framework as a roadmap to transform scam prevention from compliance obligation into strategic advantage
• Learn more about scams:  What is Push Payment Fraud?
• Read How Scam Prevention and Scam Detection Help Banks and Customers