Fraud EDge: A forum for fraud-fighting faculty in higher ed
Social Network Analysis (SNA) has its roots in academics, beginning as an analytical concept in the field of sociology more than 80 years ago. (See Analyzing Social Media Networks with NodeXL: Insights from a Connected World by Derek Hansen, Ben Schneiderman and Marc A. Smith, page 32.) Academic research still dominates this discipline, though more recently, businesses in general and marketing operations, in particular, have been very successful in using SNA in targeting customers, focusing advertising and motivating buyers. Beyond marketing, businesses use SNA to focus product development, reduce customer service costs and to improve public opinion of a firm or its products. We can use the business insights achieved in these traditional business uses of SNA just as effectively in fraud examinations. — Les E. Heitger, Ph.D., Educator Associate
The previous two columns in this series explored the power of unstructured data in fraud examinations and their enhancement by using unstructured and structured data together. In this column, we discuss the use of structured and unstructured data together in SNA to discover the interrelationships between actors in more complex schemes. Fraud fighters have used SNA in cases involving the Foreign Corrupt Practice Act (FCPA), anti-bribery and corruption (ABC), public corruption, financial statement fraud and systemic frauds involving collusive or conspiratorial acts.
NETWORKS AND THEIR ORIGINS
Networks consist of groupings of related people, animals, things or ideas — from the complex structure of anthills and beehives to the inhabitants of rainforest ecosystems. At the human level, the structure of networks becomes increasingly complex because our relationships involve social and communicative elements, i.e., social networks. These networks form because of our choices of whom we interact — based on ideology, religion, social status, personality types or our surrounding environment.
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