Unfortunately, while the federal government is slowly beginning to incorporate some advanced analytical capabilities, it lags far behind in its deployment of commercially available and viable technologies. Compared with the high levels associated with human resource staffing, technology does not cost that much. So for Step 6 in my series of steps of what is necessary to meet the the challenges of financial crimes, I believe we must start moving aggressively to incorporate advanced analytics at the federal, state, and local law enforcement levels.
Over the last few years, there have been tremendous advances in the amount of data collected and available for analysis.
Just a few examples include financial, trade, transport, and travel data. Communications and social networking are growing exponentially. Industry calls these record sets of information, "big data." I will not discuss the collection of classified data. Concurrently, there have been major advances in data mining and advanced analytical capabilities that can help organizations derive the “intelligence” from vast data sets. Data warehousing and retrieval are enhanced by cutting edge technologies that search, mine, analyze, link, and detect anomalies, suspicious behaviors, and related or interconnected activities and people. Fraud frameworks can be deployed to help concerned government agencies and departments detect suspicious activity using scoring engines that can both rate, with high degrees of statistical accuracy, behaviors that warrant further investigation while generating alerts when something of importance changes. Predictive analytics use elements involved in a successful case or investigation and overlays these elements on other data sets to detect previously unknown behaviors or activities, enhancing and expanding an investigator’s knowledge and efforts while more effectively deploying resources. Social network analytics helps investigators detect and prevent criminal activity by going beyond individual transactions to analyze all related activities in various mediums and networks uncovering previously unknown relationships. Visual analytics is a high-performance, in-memory solution for exploring massive amounts of data very quickly. It enables users to spot patterns, identify opportunities for further analysis and convey visual results via Web reports or the iPad. Moreover, it is now possible to engineer "red flag indicators" in financial reports - both within the government and in commercial enterprises that file the information - that will identify likely suspect methodologies such a hawala or trade-based money laundering.
I’m not a technical person. But I do know that the above examples are great tools that are available NOW.