Using Advanced Data Analytics to Combat Financial Crime

November 1, 2017

To keep up with regulations and adaptive criminals, money services businesses (MSBs) must continually evolve their anti-fraud and anti-money laundering (AML) processes.

A successful anti-fraud and AML compliance program is dependent on identifying the objectives of the program, implementing key components, knowing what scenarios to monitor for and understanding the vital role that technology plays within it.

In our webinar ‘Using Advanced Data Analytics and Technology to Combat Financial Crime’ we examined financial crimes common to the industry and how MSBs can incorporate technology into their compliance programs to protect themselves.

Narcotics trafficking, terrorist financing and elder abuse are just a few of the crimes that appear in this industry. Adding to the challenge of detecting these crimes is the often anonymous nature of the business that can lead to inaccurate information.

Clients may not actually exist, information can be incomplete, or the same ID could be incorrectly assigned to multiple customers. The need to ensure there are designated and qualified employees to report suspicious activity and file regulatory reports properly—with the limitations of manual processing—further complicates efforts to mitigate risk.

Fortunately, technology can be leveraged to automate AML compliance processes. This ensures procedures are properly followed, engaging the organization in a culture of compliance. Advanced analytic capabilities within a technology solution lets the business take a deeper look into their data to ensure client data is complete, help employees identify reportable transactions, aggregate data, pre-populate and validate reports, and submit and confirm submission of reports.

With anomaly detection and predictive analytics, businesses can identify many of the money laundering schemes quickly and easily, while also reducing the burden on employees. End-to-end automation of regulatory reporting helps businesses complete 70%–80% of their reports, and without involving any staff.

The risks and rewards of operating a money services business are big. The best way to maintain compliance, manage work volume at a reasonable cost, and mitigate risks is to have the right culture and an analytics-driven compliance program. The right data analytics program that combines anomaly detection and predictive analytics will help businesses identify money laundering scenarios quickly and easily.

About Anu Sood 

Anu Sood (LinkedIn | Twitter) is the Director Marketing at CaseWare RCM and is responsible for the company’s global marketing strategy. She has over 20 years of experience in product development, product management, product marketing, corporate communications, demand generation, content marketing and strategic marketing in high-tech industries.

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