Posted by at 21:04h

bank-regulation-1According to the RAND Corporation, nearly 40 percent of US households experienced financial distress during the 2008 financial meltdown. Eight years on, the financial sector is now under more scrutiny than ever. The financial crisis of 2008 increased the importance of having intelligent regulatory frameworks.

Government regulators have reacted through increased regulations, introducing numerous bills including Dodd-Frank, CCAR and BCBS 239 that require banks to greatly increase their transparency, among many other requirements. The recent case of Wells Fargo opening up roughly 1.5 million savings/checking accounts and 565,000 credit card accounts without their customers’ permission only adds to the distrust of the regulators.

The global corporations will likely face an ever- growing burden in maintaining compliance with increasingly complex regulatory and reporting regimes. According to Dick Bove, banking analyst at Rafferty Capital Markets, ‘The Wells Fargo scandal would most likely scuttle a campaign by House Republicans to blunt the regulatory impact of Dodd-Frank.’


Increased regulations aren’t just a temporary challenge for global financial institutions – it’s the living reality. The Dodd-Frank Wall Street Reform and Consumer Protection Act, passed by President Obama in July 2010, already has a major impact on the financial sector. For example, the Federal Reserve and the Federal Deposit Insurance Corporation initially deemed five out of the nation’s eight largest banks – JPMorgan Chase, Bank of America, Wells Fargo, State Street and Bank of New York Mellon to not have “credible” crisis plans under Dodd-Frank, and were told to fix and resubmit their plans.

Another important regulation, Comprehensive Capital Analysis and Review (CCAR), emerged to assess, regulate and supervise 33 bank holding companies with $50 billion or more in total consolidated assets. Recently, Bank of America has been fined $7.65 million by the Securities and Exchange Commission (SEC) for miscalculating capital ratios. CCAR policy requires unprecedented transparency and capital management. The Fed can take enforcement actions against any financial industry which fails to comply with CCAR.



Fed stress tests and regulatory data collections are not only here to stay, but will likely continue to expand further in scope. Regulators want to fully understand how banks arrive at their risk assessments. To accomplish this, financial institutions must be able to explain to regulators in a timely fashion how they arrived at their numbers, including all of the source data used to calculate the number. At a technical level, this requires banks to delve into their enterprise databases to identify data elements and trace data relationships within and between databases. The banks have to respond to their auditor’s requests on how the numbers were derived and their source data in a timely fashion, for example explaining how a capital reserve or liquidity number was calculated. The difficulty is that this is often a highly manual, tedious, time consuming process. This is where a technology firm like ROKITT can play a vital role in automating this data discovery process.



Fortunately, there are several ways for the business to address this. A common solution is an expensive manual approach, whereby the business assigns specific project teams comprised of the company’s software developers, data architects and subject matter experts (often supported by teams from outside technology consulting firms) to manually review its entire data environment to discover and document the hidden data elements and its data relationships. Alternatively, the business can partner with a technology firm like ROKITT that specializes in automated data discovery.

If you are embarking on a data discovery project, consider ROKITT as your strategic partner of choice. ROKITT’s team has worked in some of the most demanding IT environments in the world, and our people bring the agility, skill and experience required to build the best-in-class, automated data discovery product. ROKITT ASTRA uses machine learning, heuristics and deep domain knowledge to automatically discover and self-learn hidden data relationships with up to 90%+ accuracy to help organizations to quickly and accurately baseline and understand their enterprise data landscape.