Forcepoint Case Studies Arizona Financial Crimes Task Force
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Arizona Financial Crimes Task Force

Forcepoint
Analytics & Modeling - Big Data Analytics
Analytics & Modeling - Real Time Analytics
Finance & Insurance
Business Operation
Fraud Detection
Regulatory Compliance Monitoring
Data Science Services
Transnational criminals launder billions of dollars in illegal proceeds every year. In the Southwest Border affected areas, over half a million humans are smuggled and prescription drugs, illegal drugs and intellectual property are stolen. Law enforcement agencies have been challenged to process and analyze an overwhelming amount of data that pertains to these operations. Parsing and finding the incriminating data in a vast sea of constantly expanding data sources became extremely difficult, as the sheer volume of transaction data far exceeded the capability and volume capacity of typical database software. Due to the limitations and restrictions of the technology, transaction volume became the enemy, and it became harder and harder to detect money laundering patterns across the financial industry. A simple query involving multiple names, addresses or telephone numbers, for example, took hours or days to complete. Enforcement agencies were forced to invest a great deal of time searching through databases, sometimes containing millions of records each, for the suspicious activity they knew lurked among the data. In this timeframe, it was difficult to conceptualize money laundering patterns while remaining a few steps behind the criminals themselves.
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The Arizona Financial Crimes Task Force (AZFCTF) was established to investigate and interdict the money laundering activities of complex national and international organized crime and to mitigate the violence associated with the smuggling activities that fund these organizations. In January of 2014, the AZFCTF funded the creation of the Transaction Record Analysis Center (TRAC), a centralized searchable database of the financial transactions of global money services business (MSBs). TRAC now serves as the intelligence component for AZFCTF and is staffed by analyst and law enforcement professionals recognized as experts in money laundering activity. The TRAC provides data, meaningful data analysis, collaboration and training to investigators, analysts and prosecutors nationwide in their efforts to disrupt criminal organizations and dismantle their operations.
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AZFCTF needed a solution that could manage the huge volumes of data flowing into the TRAC, as well as deliver an easy-to-use analytical platform to law enforcement and regulatory users. Today Forcepoint’s SureView® Analytics is providing AZFCTF with a turnkey analytical solution that is customized for the varied user community consisting of federal agents, analysts, state and local detectives as well as money services business regulators. For each of these stakeholders, SureView Analytics delivers complete management of the environment from data ingestion to delivery of actionable analytics. The TRAC portal offers a dashboard of easy to use analysis tools, training webinars and auditing functions. Through a secure private cloud, the solution avoids overhead expenses of onsite hosting, and offers scalability as needed. Queries can be returned in a matter of seconds instead of hours which turns the increasing volume of data transactions from an enemy into an ally.
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The SureView Analytics solution has been adopted by over 2,000 users and hosts over 100 Memorandums of Understanding (MOUs), making the TRAC a unique and unprecedented financial fraud investigative tool.
Its value to the Southwest Border states and beyond is recognized daily by the number of law enforcement and regulatory agencies requesting MOUs from across the nation.
The query result speed attained by today’s experienced TRAC user enables queries to be run in a timely manner resulting in the recognition of critical activity patterns and the dismantling of criminal organizations.
Adopted by over 2,000 users
Hosts over 100 Memorandums of Understanding (MOUs)
Queries can be returned in a matter of seconds instead of hours
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