Koyal Group Training Services, Big risks and big data
CONSIDER, if you will, an analogy. Oceans are vast bodies of water that offer an abundance of marine life and resources. Yet at the same time, that immensity of size and scope means that any kind of meaningful fishing is daunting without proper skills and equipment.
Imagine now, that ocean as the vast body of data and information that flows through the average company in a given year. Sales, collections, purchases, payments, transactions, communications, e-mails, invoices, reports, spreadsheets, and more -- and you’re trying to fish for information to protect your company from significant risks such as fraud and misconduct. One of the skills and equipment in this case will be forensic data analytics (FDA) to net you the right results -- to catch those big and small fishes among corporate fraudsters.
Ernst & Young released in February this year a report titled, “Big risks require big data thinking: Global forensic data analytics survey 2014.” The survey revealed interesting information and insights on the benefits, challenges and lessons learned by companies across different countries and industries in their use of FDA. It reported that companies -- especially those looking to grow in markets where the perceived incidences of fraud, bribery and corruption are high -- consider the increasing regulatory compliance requirements and aggressive enforcement trends by regulators as major factors in the design and use of FDA to mine their “big data.”
Big data is defined as high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision-making. FDA allows companies to collect and use information culled from their data to identify and investigate aberrations, such as improper payments, anomalous patterns of behavior and trends, or suspicious transactions, to better prevent fraud, corruption and bribery.
The interesting thing to note, however, is that while 72% of the 450 executives interviewed for the survey believe that emerging big data technologies can play a key role in fraud prevention and detection, only 7% know of specific big data technologies available, such as model-based mining and visual analytic tools. Worse, only 2% of respondents actually use big data processing capabilities in their internal FDA systems. This implies that most business leaders know they need to better manage their big data, but don’t really know how to go about it.
FDA enhances the risk assessment process because it allows for better comparison of data to improve fraud-risk decision-making, while also improving audit planning or investigative fieldwork. By sifting through data thoroughly, FDA can help identify potential misconduct that a less sophisticated system might have missed.
Of those surveyed, 82% also believe that FDA allows for earlier detection of misconduct -- a significant benefit considering that, in over 1,300 incidents of fraud, it took a median of 18 months to detect them (from the latest Association of Certified Fraud Examiners Report to the Nations on Occupational Fraud and Abuse).
Modern FDA systems also allow the analysis of non-traditional or unstructured data formats in addition to structured data formats. Text mining, for example, uses new data sources such as social media, free-text fields of accounts journals, and others.