Fighting Fraud and Cyber Threats with the power of Network Analytics

February 6, 2015

Best practices, Methods, Tech Insight

Both fraudsters and cyber attackers take advantage of an increasingly interconnected world to infiltrate and assault financial and virtual infrastructures. Especially sophisticated electronic interactions bind people together in complex, global networks. While such networks have created new opportunities for interaction and commerce, they have also increased the scope and scale of risks. To stay a step ahead, risk managers need to be proactive. Social Network Analysis (SNA) is a powerful tool in the fight to detect, track, and mitigate the power of both online and real-world criminal networks.

network visualization

network visualization

Driven by increasing powerful computers and software, SNA can be applied to a broad range of business domains to discover hidden patterns in social interactions. Policing and intelligence services already apply this technique to detect and mitigate criminal and terrorist rings. Businesses frequently use SNA to develop targeted marketing strategies and to focus online ads. SNA is also increasingly being applied to a range of risk management challenges such as fraud mitigation, forensic investigation, discovery, regulatory compliance monitoring, and cyber risk assessment.

How does SNA uncover hidden patterns?

SNA works by aggregating and mapping the interconnections between people. Connections implied by emails, phone calls, property ownership, investments, company structures, organizational relationships, etc., all can be used to understand hidden networks, bearing regulatory guidelines in mind. By tracing connections, a network ‘graph’ is generated which both visualizes and quantifies patterns in focused communities. From this, suspicious patterns can be uncovered and examined in detail. As well, known patterns can be quantified and used to detect similar cases in larger sets of data. For instance, by encoding the communication and transactional patterns associated with a known fraud technique, a similar pattern can be detected in a broader domain.


Example of application of network anlaytics to tax fraud detection

Who is applying SNA for Risk Management?

SNA should be on the radar of risk aware professionals across all industries as a powerful tool in the flight to detect and track risks in complex networks:

  • Enterprise Risk Manager:  SNA is applied to a range of ERM concerns, such as succession planning, streamlining employee communications, and mitigating insider trading.
  • Compliance Officer:  SNA is used to unlock hidden patterns in internal communication channels such as phone, email, and messaging. Hidden rings and isolated groups can be a danger from a compliance perspective – better to be informed and aware!
  • Reputation and Social Media Managers: SNA is a powerful tool for monitoring and analyzing social media communities, for instance to mitigate and control attacks on reputation.
  • Fraud Investigator:  SNA is used to uncover hidden patterns associated with fraud rings and organized crime. Network analysis brings new light to the effort to detect bribery, corruption, money laundering, and financial fraud

What’s next? How to Apply SNA in your organization

  • Undertake a maturity scan:  Not sure how SNA fits into the big picture? Assess your current landscape and clarify opportunities to test SNA to address specific unaddressed challenges.
  • Conduct a proof-of-concept:  Curious, but not convinced?  Seeing is believing! Frame a discrete, well defined challenge to demonstrate core SNA techniques and benefits.

Strengthen existing risk efforts:  Complement your existing toolset! Perhaps you have an existing fraud detection and mitigation or compliance monitoring program, but wish to investigate ways to strengthen your toolset?  SNA can be a powerful complementary add-on approach to strengthen an existing solution.

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About SARK7

Scott Allen Mongeau (@SARK7), an INFORMS Certified Analytics Professional (CAP), is a researcher, lecturer, and consulting Data Scientist. Scott has over 30 years of project-focused experience in data analytics across a range of industries, including IT, biotech, pharma, materials, insurance, law enforcement, financial services, and start-ups. Scott is a part-time lecturer and PhD (abd) researcher at Nyenrode Business University on the topic of data science. He holds a Global Executive MBA (OneMBA) and Masters in Financial Management from Erasmus Rotterdam School of Management (RSM). He has a Certificate in Finance from University of California at Berkeley Extension, a MA in Communication from the University of Texas at Austin, and a Graduate Degree (GD) in Applied Information Systems Management from the Royal Melbourne Institute of Technology (RMIT). He holds a BPhil from Miami University of Ohio. Having lived and worked in a number of countries, Scott is a dual American and Dutch citizen. He may be contacted at: LinkedIn: Twitter: @sark7 Blog: Web: All posts are copyright © 2020 SARK7 All external materials utilized imply no ownership rights and are presented purely for educational purposes.

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