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Perspectives

Technology and data governance

Investing in a way that pays back

Financial institutions are increasingly seeing the need for an increased focus on investments in technology and data governance that can provide standard-yet-granular and high-quality data to support financial stability, and help with monitoring their safety and soundness.

May 10, 2018 | Financial Services

The right kind of data must also be easily accessible and malleable enough to be re-purposed as needed, and provide actionable insights and analysis. Beyond regulatory compliance, executives understand that their firms stand to reap other business benefits that can provide competitive advantages. This was echoed in a recent survey where CFOs were asked:

What are your most important personal contributions to your company's planning processes?

Although responses varied by industry, many CFOs cited the following: Providing insight and analysis, ensuring risks are recognized, allocating capital to the right initiatives, and challenging priorities and assumptions.

 

Figure 1: Deloitte LLP CFO Signals 4Q ’17, CFO Role in Business Planning p27. Published 10-Jan 18

How did the industry get here?

One of the outcomes of the financial crisis was the enactment of the Dodd-Frank Act and other requirements (such as Basel III, Comprehensive Capital Analysis and Review (CCAR), and Capital Liquidity Analysis and Review (CLAR)), which centered on granular, high-quality data throughout financial institutions, including heightened internal controls through an enterprise-wide governance structure. Today, most key executives such as chief financial officer (CFO) not only have to know and analyze their data as part of risk monitoring, but are mandated to attest to the quality of their data (e.g., CFO attestation).

In short, the impact of the crisis and increased regulatory requirements has changed the business landscape. Financial institutions must not only make operational changes to meet regulatory requirements, but they must also strategically position themselves to increase the business value for making investments. A key question is, “How do firms make the requisite investments to not only help comply with their regulatory requirements but also help enhance business value across the enterprise?”

Investments that pay back

While many executives are examining ways to a foster growth in their plans, capital efficiency and returns remain a focus. Financial institutions can consider the following examples of investment areas and potential payoffs when formulating their technology and data governance strategy:

Opportunity Need/challenge Investment Potential pay back
Capital efficiency

Lack of transparency and organization in transaction data can cause financial institutions to default to higher capital charges, resulting in inefficient use of capital

Cognitive Intelligence/Robotic Process Automation offers ways to look through documents that support transactions (e.g., prospectuses, loan agreements) to support applying appropriate capital to exposures

  • Lower capital charges
  • Free up “trapped capital”
Free up and re-allocate human capital resources

Large transaction volume that requires a substantial level of manual testing effort may create quality control issues and inefficient use of human capital

Automation capabilities (e.g., Robotic Process Automation, Natural Language Processing/Generation) can be applied to controls that are suited to automation to increase efficiency and improve testing coverage

  • Reduced costs
  • Greater quality/flexibility
  • Re-allocation of man hours

Financial institutions have the need to manually process high volumes of forms in the first lines, thereby reducing resources available for knowledge intensive tasks and processes

Machine Learning and Natural Language Processing provide opportunities for data extraction, processing, and integration of information from the forms into IT systems

  • Reduced re-work
  • Improved customer experience
  • Efficient resource allocation
Data aggregation and reporting

Regulators have increasingly moved toward standardized reporting via forms such as FR Y-14A; FR Y-14Q; and FR Y-14M, etc., creating the need for supporting capabilities

Sustainable data and technology infrastructure that can provide standardized data aggregation and reporting to support compliance with regulatory requirements

  • Authoritative data source per risk type
  • Robust data aggregation/flow capabilities
Data governance

Increased regulatory scrutiny on data completeness and accuracy necessitates ongoing assessment of adequacy of governance framework

Compliance assessment framework designed to identify gaps and enhance risk data controls and aggregated reporting

  • Rationalized controls/processes
  • Increased efficiency and data quality

From the design and build stage, financial institutions must think of the needed components to design/adopt a strong data architecture and technology that supports compliance with current regulatory requirements and can nimbly accommodate future changes, in light of ever evolving regulatory requirements. A strong governance framework is needed to implement robust quality controls, risk assessments, and on-going monitoring and testing. Results of monitoring and testing activities should inform proactive data compliance management.

How Deloitte can help

With an understanding of the maturity level of a data infrastructure and governance, our services can be provided through both a tactical and strategic model presented below, fostering a sustainable approach to help reduce cost and increase efficiencies:

Categories Tactical Strategic
Data & infrastructure
  • Identification of critical data elements (CDEs)
  • Documentation of data flow
  • Data integrity validation/testing



  • Rationalization of data flow across IT systems
  • Design and implementation of CDE/data management plan
  • Redesign and/or realignment of data dictionary
  • Data integrity validation/testing program
Reporting, training & testing
  • Report production support
  • Pre- & post-exam readiness
  • Testing of regulatory reports
  • Training of personnel
  • Assessment and re-design of reporting program
  • Design and implementation of testing and QA programs
Operating model
  • Report-specific automation assessment (Robotic Process Automation/Cognitive Intelligence)
  • Drafting regulatory reporting policies, guidelines, standards, and procedures
  • Design and implementation of target operating model
  • Strategic assessment of reporting programs
  • Design of a governance framework over regulatory reporting
Risk & controls
  • Controls inventory/documentation, including assessment of design and effectiveness testing
  • Risk and control data rationalization
  • Reconciliation framework


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Contact us

Marjorie Forestal
Principal | Deloitte Risk and Financial Advisory

Deloitte & Touche LLP

Ken Lamar
Independent senior adviser
Deloitte & Touche LLP
 

Claudio Rodriguez
Senior manager | Deloitte Risk and Financial Advisory

Deloitte & Touche LLP

Precious Ugwumba
Manager | Deloitte Risk and Financial Advisory

Deloitte & Touche LLP
 

Stanley Philip
Manager | Deloitte Risk and Financial Advisory
Deloitte & Touche LLP
 

Chris Spoth
Managing director | Deloitte Risk and Financial Advisory
Executive Director, Center for Regulatory Strategy
,
Americas Deloitte & Touche LLP

Irena Gecas-McCarthy
Principal | Deloitte Risk and Financial Advisory
Deloitte & Touche LLP

   

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