The Impact of New Regulations on the Banks' Big Data Lake

Today’s financial services industry is flooded by the constant introduction of new regulations. Each new deadline forces companies to reevaluate their current processes and architecture.

January 2013 was the first indication of a worldwide shift in risk data management requirements, with the issue of BCBS 239 by the Basel Committee on Banking Supervision. BCBS 239 mandates that banks adhere to a set of core principles for effective Risk Data Aggregation and Risk Reporting (RDARR) practices as early as the start of 2016.

As a result, business consultants, systems integrators and big data vendors at all levels of the stack are actively helping banks prepare their processes and IT infrastructures for compliance.

While the waves of BCBS 239 will make landfall at different times – depending on the classification of your bank – the question is: will you be ready?

Bank-Reported Challenges

With the New Year fast approaching, financial institutions are scrambling to ensure that big data architectures meet risk reporting, data aggregation and data governance requirements. The self-assessment questionnaire from January 2015 showed that while Global-Systemically Important Banks (G-SIBs) were making progress on key principles, they struggled overall, leaving year-over-year progress largely unchanged. Specifically, data aggregation and the supporting infrastructure for proper governance remain the most challenging areas for financial organizations.

Not surprisingly, the principles with the lowest reported compliance were:

• Principle 2 (Data Architecture/IT infrastructure);
• Principle 6 (Adaptability); and
• Principle 3 (Accuracy/Integrity).

Perhaps most alarming, the year-over-year downgrades reveal that banks are uncovering more problems as they attempt further compliance. Specifically, banks “continue to point to the need to enhance current IT architecture and data flows to reduce complexity and manual workarounds” and report that “IT infrastructure, while adequate in normal times, was not adequate in stress or crisis situations.” Domestic – Systemically Important Banks (D-SIBs) face these same compliance challenges.

Even those that believe they will be ready for their respective deadlines will be doing so with many manual workarounds that are not optimal or adaptable.

A Big Data Platform to Enable Compliance

It is critical for financial services institutions to determine an architecture that will best enable them to meet compliance requirements – and quickly. This architecture should allow for comprehensive enterprise level governance, while also enabling analysts to complete and continually improve their risk Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy Read this Term in an easy to use self-service paradigm. Most banks have historically completed these analytics across many disparate teams in many disparate and disconnected systems or spreadsheets. Enabling the aggregation of data from upstream source systems and empowering the transition of free standing spreadsheets into a central business analyst-friendly interactive repository – all in the creation of a comprehensive data aggregation and reporting pipeline – is crucial.

The ideal architectures must give financial services institutions the ability to:

• Apply enterprise-wide governance to achieve a single source of truth
• Instantly see the lineage of any data
• Ensure data quality with automation and access control
• Achieve real-time audit readiness

BCBS 239 deadlines are fast approaching, and the industry Regulation Regulation Like any other industry with a high net worth, the financial services industry is tightly regulated to help curb illicit behavior and manipulation. Each asset class has its own set of protocols put in place to combat their respective forms of abuse.In the foreign exchange space, regulation is assumed by authorities in multiple jurisdictions, though ultimately lacking a binding international order. Who are the Industry’s Leading Regulators?Regulators such as the UK’s Financial Conduct Authority ( Like any other industry with a high net worth, the financial services industry is tightly regulated to help curb illicit behavior and manipulation. Each asset class has its own set of protocols put in place to combat their respective forms of abuse.In the foreign exchange space, regulation is assumed by authorities in multiple jurisdictions, though ultimately lacking a binding international order. Who are the Industry’s Leading Regulators?Regulators such as the UK’s Financial Conduct Authority ( Read this Term waves won’t stop there. As banks prep IT infrastructures and processes for compliance, the right architecture will ease the preparation process and minimize the aftershock.