How can banks improve data management?

Banks today, desire to achieve greater transparency into their operations to better assess its organisations’ financial health and also to meet informational requirements set by regulators and its stakeholders.

Our new report ‘Devil in the data: How banks can improve data management’, identifies the cultural and operational differences between the risk and finance departments which have been proven difficult for many banks to overcome. It also explores the roles of the Chief Risk Officer (CRO) and Chief Financial Officer (CFO) has in coordinating efforts to reduce or eliminate the redundancy across the two functions whilst improving its quality.

Data is the backbone of risk and finance, two departments that have historically consumed and outputted it very differently. Hence a major challenge is the way in which the risk and finance teams in banks currently operate. While the data used by respective teams often originates from the same sources, they store it differently, make unshared adjustments to it, and manage it differently. This presents difficulties in reconciling both data inputs and subsequent informational outputs.

In our experience, banks can work towards fewer discrepancies, with any inconsistencies easily traceable and reconcilable if risk and finance teams start to collaborate and be more closely aligned.

Here are the four key components of data management that encompass all disciplines related to managing data as a strategic asset:

The policies and procedures of accountability and responsibility of data may be the most critical component of data management. Surveys showed that with an appointed CDO in the organisation, risks are likely reduced by 70% with better compliance. A data governance council should also be set up; ideally led by the CDO and include the Chief Finance Officer (CFO) and the Chief Risk Officer (CRO) to oversee the execution of data policies and procedures. Ensuring alignment between risk and finance teams and empowering the CDO and the council with the ability to influence all leaders would be key towards ensuring one vision on data management across the bank.

Some banks have a fragmented system architecture that creates massive gaps in its data architecture. To resolve these issues, it is ideal that banks move toward a target-state architecture that leverages one golden source of data (“a single point of truth”), a ledger/sub ledger layer for finance, controlled adjustments, and reconciled reporting. This would help users define and classify the bank’s products, customers, and other variables in a standard way across the organisation that would reduce data replication.

Banks should try to establish models to create consistency and standardisation on how primary data is obtained and processed, and by whom. Both risk and finance functions should obtain an understanding of the needs of respective functions and achieve a consistent business information model. Banks will then be able to source from one place and govern data across both risk and finance.

With the risk and finance functions working in silos, situations where reports from both functions are unable to reconcile, prevent the bank from providing accurate information. If done right, the success of the above-mentioned metadata management and data architecture would be reflected here. It is also important to note that the IT function is integral in making the partnership between finance and risk teams possible and should be involved from the beginning to ensure that the requirements of both teams are well-supported to achieve an overall improved data management.

In conclusion, banks that master robust data management will be better positioned to make strategic business decisions based on reliable data they can trust, respond to future informational requests more efficiently and demonstrate adequate financial health and risk management competencies.

To read the full report, click here:

https://www.pwc.com/us/en/financial-services/publications/viewpoints/assets/improving-data-management.pdf