Video: Agile Analytics for Regulatory Compliance: Stop the High Jump in the Dark

 

Ahhhh…, “CCAR Season”.  For the banks lucky enough to make the Fed’s list of institutions required to submit annual capital plans, it means armies of employees and contractors going heads-down for months to produce thousands of pages of documentation. That documentation is submitted to the regulator, and then the new scenarios for next year are released, starting the entire process over again. And that is just CCAR! The same is true for any number of the dozens of regulations to which financial institutions and financial services firms are subject in today’s post-crisis regulatory environment. As one industry consultant quoted in a MoneyBeat article called, Why Did U.S. Units of Deutsche Bank, Banco Santander Fail the Stress Test?:

“The message to all banks is that the bar is going to keep rising, and they won’t be able to stand still to keep up. Banks have privately chafed at this. ‘It’s like doing a high jump in the dark. You clear the bar and then it gets raised a little bit for the next jump,’ but the banks can’t see exactly how high the bar has been reset, Mark Levonian, a managing director with consulting firm Promontory Financial Group, said in an interview… ‘So you jump as high as you can.” At the same time, Fed officials are explicit about the fact they expect improvement every year, telling the banks not assume what was okay last year will suffice this year, he said.'” 

This got me thinking…

  • What if it didn’t matter how high the regulators set the bar?
  • What if it were possible to create an agile analytic environment for all of the data compilation and analysis that goes into regulatory compliance efforts?
  • What if there were a way to reduce the burden on compliance teams and at the same time produce analytic results that are accurate, transparent, and, most importantly, can add value in other areas of the business?

The process of preparing regulatory reports and submissions is an exceedingly complex exercise often involving bringing together data from dozens or sometimes hundreds of disparate systems and performing sometimes complex, advanced analytics on those data. It’s not a very rewarding effort, either. Many firms see regulatory compliance as a mandatory, one-off, periodic exercise not unlike preparing your personal income tax returns, albeit on a much grander scale. Once the submission is complete, the results are often mostly discarded and the entire Sisyphean effort starts over again to prepare for next year’s submission.

Why is it such hard work? Because the vast majority of firms are just not set up with the right tools and methodology to make it any less so. Multitudes of individual analysts logging into antiquated business intelligence platforms, dumping as much data as they can into spreadsheets or desktop databases (the analytic software equivalent of duct tape and bailing wire), and crunching the numbers in isolation is far from an efficiency-conducive environment. Not to mention the nightmare this causes for anyone who wants to trace or audit all of that analytic work.

There must be a better way.

As it turns out, there is. Some of the most successful financial services companies that I work with as my clients have enabled, or are enabling, a much more pervasive, agile analytic environment. By employing modern software platforms that enable analysts to do the same work in a fraction of the time and to do so in a repeatable, yet flexible way that allows for course adjustments and new analytics along the way, these firms are realizing the goals of reduced effort and increased value simultaneously.

Sometimes, especially in larger firms, this agile analytic environment is provided by a centralized function such as an analytics Center of Excellence (CoE) or a “Data Lab” under the guidance of a Chief Data Officer or a Chief Analytics Officer. It can also start smaller, as a departmental kind of environment that can grow over time.

However it is implemented, an agile analytic environment as it relates to regulatory compliance has several key components that need to be in place to ensure success:

  • A cooperative relationship between stakeholders in IT and in the business with the common goal of enabling a governed self-service environment for data analysis
  • Acceptance that existing data infrastructure (ETL platforms, enterprise data warehouses, business intelligence suites, etc…) simply cannot be agile enough to respond quickly to the changing regulatory environment
  • A software platform that enables analysts and others with a wide variety of skill sets (from business analysts to data scientists, and everyone in between) to contribute to the building of analytic applications in an agile way.

When properly implemented, this environment provides analysts with the tools they need to pull data from many disparate sources, perform advanced analytics on those data and, importantly, capture the results of their efforts as reusable analytic assets. This not only shortens the next analytic cycle for regulatory compliance and reporting, but can also add value in other areas such as financial analyses, operational efficiency, and customer experience analytics. The complex regulatory environment is here to stay, but with some forethought and imagination, along with the right tools for the job, the resulting burden on compliance and analytics teams can be lessened and the results of their efforts can contribute substantial, long-term value to the business.

*Quote cited from the Wall Street Journal, Ryan Tracey