Aligning risk and finance functions through developments in four key data management components

Various banks/financial institutions/financial institutions find it problematic to meet the informational demands of regulators and other stakeholders. Structuring improved & recovering data management competences is crucial to meet these demands. To be effective, banks/financial institutions/financial institutions should align their risk and finance functions while concurrently making developments in four key components of data management:

• Data ownership and stewardship Discusses about the policies and procedures concerning the accountability and responsibility of data. Though some banks/financial institutions have established policies and procedures that define the accountabilities for data owners and stewards, they haven't been principally effective in fulfilling these responsibilities and introducing lasting change in how data is overseen. To help achieve roles and responsibilities, some institutions have chosen to employ a Chief Data Officer (CDO) to oversee the bank's enterprise-wide data governance and its use of data as an asset. According to a current study conducted by Forrester Research, establishments with a CDO were 70% more likely to reduce risk and well ensure compliance than an organization without a CDO. Yet some banks/financial institutions that have a CDO remain to struggle in figuring out the scope and responsibilities of this new specialised individual.
• Data architecture A bank's data architecture is a collection of blueprints intended to regulate how data is collected, processed, stored, and consumed across the enterprise and aligned with the business strategy. In our experience, maximum of the banks/financial institutions work with a fragmented, sometimes archaic, systems architecture that creates gigantic gaps in the processes of storing, querying, retrieving, and utilizing data. Though the past period has seen a tendency to resolve these gaps, yet several banks/financial institutions still lag behind.
• Metadata management Metadata is data about data—data that tells us when, where, and how primary data was acquired, created, or revised; how it is formatted; where it is located; and who is responsible for it. Many banks/financial institutions have been working to create consistent business information models that standardize, format, and reference data. Although there has been success managing metadata for risk or finance individually, there is more work to do to make sure these two are aligned.
• Data delivery Data delivery refers to an institutions ability to efficiently provide accurate information to the right users. Both the risk and finance functions are now being asked to provide more detailed reporting, more quickly than in the past. In cases in which reports include similar information, the two functions are being asked to reconcile their numbers, demonstrating that what has been provided by finance matches what has been provided by risk. The following examples are all heavily dependent on accurate reporting of daily financial product performance and capital information: daily liquidity reporting, CCAR reporting, market-risk reporting, and liquidity stress testing.