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Attacking Money Laundering with Advanced Data Wrangling

August 23, 2016

Globally, money laundering accounts for losses of up to $2 trillion annually. Financial services institutions are firing back by investing in money laundering detection systems. According to PriceWaterhouseCoopers, the annual growth rate for anti money-laundering (AML) spend is expected to grow by $8B in 2017—mostly for AML detection systems, as well as for managing compliance with new AML laws and statutes. Historically, the detection of money laundering has been seen as the domain of government. But things have changed.

In Financial Services, AML Is Now Your Business

Between increased regulation (e.g. The Bank Secrecy Act, the Know Your Customer provision of the Patriot Act, and The Foreign Account Tax Compliance Act), along with some big fines levied against financial services firms, the industry now knows they must implement better money laundering detection systems, and according to a recent survey by Ovum, the bulk of that investment is targeted specifically for anti money laundering data, systems, and tools.

The New Needle in a Haystack – By Tomorrow

Financial services institutions already knew that AML detection was critical to averting fines and that predictive detection can save billions—if they could catch the bad guys in time. However, money laundering is harder to detect than other fraud because it requires large amounts of aggregated data, over long periods of time and from diverse sources to see AML outliers. That’s hard to do in spreadsheets alone. By the time the experts have found the money launderers, they may have already moved on.

Trifacta partner Cloudera reports: “Today, the introduction of an enterprise data hub built on Apache Hadoop at the core of your information architecture promotes the centralization of all data, in all formats, available to all business users, with full fidelity and security at up to 99% lower capital expenditure per terabyte compared to traditional data management technologies.” At a lower lost per terabyte for data hubs provided by Hadoop, top financial institutions can now create data wrangling applications that meld with existing information and data sources (in a centralized, compliant, accessible, and fast way) to detect money laundering faster and more accurately than ever.

Quite simply, because data is is now cheaper to store, there’s more of it, enough to build ever more accurate algorithms and predictive models to analyze and forecast nefarious transactions before they happen. Banks, insurance companies and other financial service firms can now store, analyze and report on many millions of data points in multiple countries, using data from third party providers as well as their own sources, They can now look across years and in some cases decades for patterns of money laundering that they have never been able to been before. Forensics, discovery and further investigation can all be performed faster, by fewer team members, allowing analysts to do what they love: find the bad guys.

Trifacta Gets You Insights, Faster

As money-laundering methods continue to evolve to evade discovery, time becomes a financial services company’s most precious resource. Data wrangling with Trifacta saves time and money not only now, but also in the future, by enabling sophisticated but standardized predictive modeling, where false positives are automatically eliminated and staff time is reduced, as are costs.

A standardized data wrangling approach will not only reduce costs by limiting time spent importing, formatting and manipulating by individuals, it will do so by also improving the accuracy, speed and quality of reporting enterprise-wide. This is especially critical for financial services providers, who must understand who has touched data throughout the firm and provide in-depth data lineage to prove compliance with BCBS 239, among other new requirements.

Built from the ground up by financial services professionals, Trifacta’s unique wrangling solutions, enable analysts throughout the company to monitor, analyze and report on data, working alongside with their colleagues at all technical levels, while preserving source data and data lineage. Trifacta also offers analysts better up front assessment of data sources, leading to smart extraction that learns preferences over time. Trifacta’s easy to use, intelligent, interactive, visual data analysis tools improve data understanding for your entire organization regardless of technical skill. You can learn more about how Trifacta is aiding fraud detection within the financial services industry here.

Finding the bad guys has never been easy. But Trifacta can help you shine a light into the dark corners of your data warehouse where their fingerprints are so you can find them faster than ever before.