DECEMBER 2021CIOAPPLICATIONS.COM8IN MY Viewith the recent advances in computer power and storage capabilities the Banking Industry has become even better at something that has traditionally mastered since it started to use computers: gathering data.Data is the blood that flows and feeds any company, major or small. We use it to measure our efficiency, losses and gaps. In the narrower context of Financial Crime Risk Management, data is used to prevent, detect, monitor and mitigate the risk of criminals using the a financial institution's products and services, either by detecting anomalies hidden within thousands of transactions or screening across large datasets looking for matching names, keywords or even news.Data collection: let's get everythingIt does not take long for a big financial institution to collect vast amounts of data related to their customers and how they behave (payments, purchases, transactions), the numbers are simply staggering: 90 percent of all data in existence today was created in the past two years, 80 percent of data will be unstructured by 2025.While storing these volumes of data might not be a problem for the analyst community, it is retrieving what constitutes the problem. Typical of any catch up dynamics, financial crime analyst are always trying to identify patterns where illegal transactions hide. To make things worse, requirements can also be very vague or broad i.e. "What can we find on human trafficking in these markets?" This sometimes ends in huge data collection efforts, where time and resources being wasted, trying to develop data insights that will likely not answer to the question. Technology can help processing data but it's humans who need to decide first what to look for.Financial Crime Analytics can learn from Intelligence practices in order to help solving this problem.Intelligence RequirementsA series of primary intelligence requirements (PIRs) should be developed, agreed and shared across the Risk function and Business Units in order to help defining those requirements and narrow both response and delivery times. Narrowing the initial question to a series of known and tested typologies is the first step to optimize time-dependant processes, resources and reasonably maximize chances for success in delivery and answering the question "so what?"PIRs should be aligned to an existing Financial Crimes Typology Library and Data sources inventory so it's easier to decompose a potentially ambiguous question into elements that can be easily mapped to existing areas of knowledge.Example: - Primary Intelligence Requirement: Provide analytics support to prevent, detect and manage finance of slavery and trafficking.- Typologies:o Human Traffickingo Money Mules - Related Typologies:o Terrorism Financingo Drug Trafficking- Data & Systems:o Customero Transactionalo Transaction Monitoringo Negative News ScreeningThe above steps can be further expanded to include specific data fields or filters. In this way, a question as broad as "what do we have on human trafficking in this market for the last 6 months?" could be quickly put against a TOO MUCH DATA? APPLYING INTELLIGENCE TECHNIQUES TO FINANCIAL CRIME RISK DATA ANALYTICS.WFRANCISCO MAINEZ, HEAD OF DATA AND ANALYTICS, BUSINESS FINANCIAL CRIME RISK, HSBC
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