Article illustration

Essential Skills for the Modern Fraud Fighter.

The modern fraud fighter needs domain knowledge, data skills, critical thinking and communication, supported by continuous learning that keeps pace with changing threats.

5 min read

Staying ahead in fraud prevention is a constant challenge. Fraudsters are always innovating, finding new ways to exploit vulnerabilities and bypass security measures. While individual fraudsters often specialize in particular techniques or specific types of scams, fraud fighters must cover a much wider range of areas. This means fraud fighters need to adapt and evolve continually.

Key Qualities of an Effective Fraud Fighter:

  1. Subject Matter Expertise
  2. Familiar with all types of scams, past, present, and emerging
  3. Able to monitor and resolve alerts across various fraud types
  4. Knowledgeable about regulatory and compliance requirements (GDPR, PCI DSS, etc.)
  5. Technological Proficiency
  6. Experienced with multiple market solutions
  7. Understands data flows and details within the organization
  8. Skilled in ETL/ELT processes
  9. Analytical and Critical Thinking
  10. Inspects and analyzes fraud, uncovers methods, and formulates preventive measures
  11. Customer-Centric Approach
  12. Designs and implements fraud prevention measures with minimal customer friction
  13. Versatility and Adaptability
  14. Covers various roles (analyst, rule writer, operations manager)
  15. Ensures quality for customers and audits
  16. Effective Communication and Collaboration
  17. Translates operational KPIs into meaningful reports for C-level management
  18. Continuous Improvement
  19. Stays informed through training and self-education

And I'm sure you could add a few more traits and skills to the list above. Long story short, fraud fighters' qualities and required skills are diverse to encompass a wide range of areas, reflecting the complexity and demands of their role.

Pace of Change

Fraud techniques evolve rapidly. While some techniques, such as phishing or the "Nigerian prince" scam, have been ever-present since the early days of the internet, new ones are constantly introduced. Countermeasures that worked yesterday may not be effective today.

Consider the rise of tech-support scams, where fraudsters impersonate tech support staff from well-known global brands like Microsoft. Using social engineering, they manipulate customers into sending money or giving them access to their bank accounts. This scam has only gained prominence in recent years, but is already causing significant losses. Over the last decade, FBI IC3 reports have documented a rampant increase in victims of tech-support scams, which were once a niche threat.

Historical fraud-victim and loss trends across selected categories.
Figure 1: Historical fraud-victim and loss trends across selected categories. 1

Similarly, Business Email Compromise (BEC) has become a major concern. In a BEC scam, attackers gain access to an organization's network via targeted phishing emails. Once inside, they use the victim's email to submit altered invoices with account numbers the attacker controls. Like the tech-support scam, BEC was rare a decade ago but has quickly grown to cause over $1 billion in losses and continues to grow further.

The list of skills for a successful fraud fighter is comprehensive, but the most crucial skill is keeping pace with these changes and continually learning. This foundational ability supports all other skills and ensures that fraud fighters can effectively combat emerging threats.

Information Overload and Areas of Focus

The sheer volume of information can be overwhelming. New reports, studies, podcasts, and webinars are released daily, covering a wide range of topics—from the latest threats and vulnerabilities to cutting-edge techniques and technologies for tackling current and future fraud. Filtering through this information to focus on what truly matters is challenging.

Staying current is a common struggle, especially when you need to understand the business context of existing and emerging fraud schemes. To thoroughly examine proposed mitigation techniques, you must be able to break down these frauds into fundamental components and derive practical solutions that can be effectively implemented using available technology.

To maintain an edge, fraud fighters should prioritize the following areas:

  1. In-house Solutions Knowledge and Workflows - A foundational skill is knowing which technologies the organization uses and how they interact. For example, understanding customer-facing channels and how transactions flow from these channels to back-end systems like core banking. The focus should be on fraud-related components, but awareness of surrounding systems (CRM, SMS gateway, call center, SIEM, etc.) is also beneficial.
  2. Data Analysis and Awareness - Anti-fraud solutions rely heavily on the data collected during relevant interactions (e.g., customer purchases, branch staff servicing customers). It is crucial to align individual skills with the ability to work with this data, including:
  3. Understanding Technologies and Formats: Know the technologies (SQL, relational databases) and formats (XML, JSON, CSV) used within the organization.
  4. Data Location and Access: Know where relevant data resides (data warehouse, data lake, data marts) and how to access it.
  5. Data Manipulation Skills: Develop skills to manipulate, transform, and combine data to validate hypotheses.
  6. Reporting: Learn to create tables, reports, and dashboards to communicate findings clearly.
  7. Machine Learning - Machine learning algorithms are increasingly deployed in anti-fraud solutions to improve detection accuracy, aiming for higher True Positives and/or lower False Positives, thus reducing alert fatigue among operational staff. Machine learning algorithms can be integrated into fraud-prevention solutions in various deployment models, and the best fit usually depends on several factors (maturity of the customer's staff, data quality and availability, expertise and availability of technologies to build and retrain the model, purpose of the model, etc.).
  8. Detection Techniques - It is important to be familiar with various fraud detection techniques, as no single technique can efficiently mitigate all types of fraud. The most commonly used techniques are: Blacklist/Whitelist, High-Risk lists, Entity behavioral profiles, Anomaly detection, Network visualization and network analytics, Data mining and Machine learning, Text mining, Geolocation analysis, and Device fingerprinting.

Human Element

While technology is vital, the human element remains irreplaceable. Fraud fighters need to cultivate a mindset of curiosity and skepticism, always questioning and probing deeper into anomalies.

One interesting example of exposing fraud is the story of Harry Markopolos, who uncovered the Bernard Madoff Ponzi scheme in an extraordinary way. Markopolos, a financial analyst, suspected that Madoff's consistently high returns were too good to be true. Using advanced mathematical models and statistical analysis, he proved that the returns were impossible under legitimate trading strategies. Despite submitting detailed reports to the SEC multiple times over several years, his warnings were initially ignored. Markopolos's relentless pursuit and eventual public exposure of the scheme drove significant changes in the financial regulatory environment and underscored the critical importance of diligence, analytical rigor, and persistence in fraud detection.

Becoming a successful fraud fighter is both challenging and immensely rewarding. By focusing on continuous improvement in the most impactful areas, fraud fighters can significantly enhance their organization's defenses.

Remember, combating fraud is a marathon, not a sprint. Continuous learning and adaptability are our crucial allies in this ongoing battle.

References & Further Reading

  • [1] Internet Crime Complaint Center annual reports

    Official report archive for the historical fraud-trend chart. Annual reporting categories and coverage can change.

    by Federal Bureau of Investigation, Internet Crime Complaint Center

Continue reading

All articles →

Responses (0)

Join the conversation

Responses are available to read. Reader sign-in is temporarily disabled.

Responses

Loading responses…

Article image

Loading image…