Combating non-compliance with agile analytics

When the ICIJ released a searchable public database of the Panama Papers last month, businesses - particularly financial institutions - scrambled to cross-reference it with their own company’s data to uncover any connections with the 200,000 involved entities.

Almost immediately, the Obama administration announced steps that the White House is taking to fight money laundering, corruption and tax evasion, such as requiring financial institutions to verify the true identities of the people behind the companies they do business with. Days later, financial services company Raymond James was hit with a $17 million lawsuit for failure to comply with anti-money-laundering regulations.

Notice the trend? There’s an international spotlight on compliance and anti-money-laundering, but the constantly evolving regulatory landscape has made it harder than ever for businesses to comply. To make matters more complicated, businesses struggle to keep up with the growing number of data sources and communication channels to monitor for compliance risk, from social media to mobile to text messaging and beyond.

Data from all these sources, in combination with data from different business units around the globe, are spread across hundreds of disparate systems - making it nearly impossible for businesses to provide quick answers when the regulators come knocking and to stay ahead of risk before it is too late.

The Agile Solution

One approach to handling this influx of data is quickly taking shape: adopting an agile analytic environment. Companies leveraging this solution are able to stay on top of ever-evolving compliance requirements, helping them be more proactive and quickly respond to regulation change. When properly implemented, this approach enables analysts to pull data from across disparate sources, perform advanced analytics - such as predictive analytics - on the data, and create reusable analytic assets. A far cry from traditional manual approaches to compliance, agile analytics - made possible by modern software platforms and key infrastructure changes - enables analysts to do the same work in half the time and in a repeatable, yet flexible way.

For example, in light of the Panama Papers, my company worked with one of the world’s largest financial institutions to help cross-reference the public database made available by ICIJ. As quickly as possible, the firm needed to determine if any of its customers were involved, provide a report on any exposure of sensitive materials and be prepared for repercussions from regulators. It was a global feat not possible with traditional methods of approaching the abundance of data. Because the company already had an agile infrastructure in place, it was able to quickly build an analytic application to examine the data and get fast insights to any potential risks.

Now that the application is built, it will be run over the next couple of months and be prepared for deployment for the next crisis, even if regulations are altered.

How to Get Started

Where can a company begin in setting up this agile approach? In larger firms, the agile environment often begins with a centralised function, such as a Center of Excellence (CoE), under the guidance of the Chief Data Officer or Chief Analytics Officer. But the need for agile analytics starts smaller. Individual departments or business functions need analytics and look to the CoE to provide essential skill sets, such as data provisioning, data science and architectural skills, to compliment the business expertise provided by the department or business line.

Regardless of the implementation, an agile analytic environment has several imperative components, especially as it relates to compliance:

  • Cooperation between IT and lines-of-business with the common goal of enabling a governed, self-service environment for data analysis. Data is getting more accessible to anyone within a business, but getting it to be coherent and provide insightful information is another challenge.
  • Acceptance that existing data infrastructure (ETL platforms, BI suites, etc.) cannot respond quickly enough to the changing regulatory landscape.
  • A software platform that enables analysts and business users, regardless of technical acumen, to contribute to the building of analytics applications in an agile way.

At some point in time, nearly every financial institution will be at risk of being exposed. Instead of waiting for the next Panama Papers crisis, it’s time the industry gets more proactive in how it handles compliance by setting up an agile infrastructure now. When it all boils down, speed and flexibility are a key component to monitoring and investigating data related to regulatory compliance, anti-money-laundering and mitigating risk.

An agile approach to analytics can bring the kind of business-wide, global intelligence to help companies avoid the non-compliance penalties than can cost millions.

Suki Dhuphar, Managing Director, EMEA at Lavastorm

Image Credit: Shutterstock/Sergey Nivens