Data quality is high on the list of priorities of senior management, supervisory boards and managing boards at financial institutions.
Data quality, aggregation and validation should not merely represent a routine check-box in a compliance officers’ to-do list. There are benefits that extend far beyond fulfilling the letter of the compliance requirements in areas such as collateral management, stress-testing planning or assessing the resolvability of a systemically important bank.
Data quality is therefore high on the list of priorities of senior management, supervisory boards and managing boards at financial institutions. The recent past has been tumultuous for the financial services sector and banks still face challenges today. Regaining public trust with a diversity of stakeholders, most notably the customer, is one of these challenges. A lot of negative media attention around financial institutions concerned the bail out of financial institutions with tax payers’ money, fraud cases and fines. This resulted in a variety of new rules and regulations from the ECB and national central banks, for example IFRS9, Asset Quality Review, Basel III, BCBS239 and Deposit Guarantee Scheme. An important portion of these rules deals with showing that institutions are ‘in control’ and delivering correct information to stakeholders such as regulatory reporting to the central bank. One issue lies in ensuring that the quality of the data used meets the requirements of correctness, timeliness and completeness for internal processes on accounting, financial risk management or for reporting to regulators.
Currently a number of banks face difficulties regarding the timely availability of correct and complete data. Banks discover that their information is outdated, not always completely administered or that earlier reports were made up of incomplete and incorrect data. Noncompliance with laws and regulations can result in fines and reputational damage for banks; something the banking sector is doing its best to prevent.
Regaining public trust means that banks need not only focus on regulators, but on clients, personnel and shareholders at the same time. This will result in a much more service and customer oriented bank with transparent information, correct client data and efficient processes. Notwithstanding big data enthusiasts, it appears that the data question represents a significant challenge. Today many banks have at least one significant project on their radar to improve data management, IT infrastructure and reporting. However the focus tends to be around control, governance and architecture – we would suggest that more attention now needs to be given to how the data is ultimately used in order to find the opportunity in this challenge.
Data is to be seen as one of the most important assets within a bank. Not only from a reporting but also from a customer point of view. Therefore the business taking ownership of data is an important step. What is required from a data and information perspective is capturing the customer relationship in a single, accurate and complete view. This is not an easy task since mergers and acquisitions have led to many banks being made up of multiple customer systems with duplicate and inaccurate or incomplete date. We have seen clients where less than 50 percent of client data remains after weeding out duplications, incomplete entries and scores of customers with erroneous names.
Creating a single customer view from an accounting, risk management and regulatory reporting perspective as well as having insights into the profitability of a single customer (or specific customer segments) should be one of a bank’s main goals in order to steer business operations. Another benefit is the ability to set risk exposure limits for customers quickly and much more accurately; banks can use all the information available on their customers to decide which customers are high or low risk. In the case of low risk customers, lending can be increased resulting in faster decision making when customers apply for a line of credit. Furthermore, the added information helps with marketing and cross-selling products – providing offers that are much more relevant to the customer.
Having a single customer view can also benefit customers, as banks will be able to provide information on customers’ financial position, suggest relevant products, share income and spending trends and facilitate their financial decision-making process. Thus a seemingly technical matter like data quality can have a big impact on yield if customer requirements are not driving the data model.
Brigette Beugelaar, Partner RC IT Advisory, KPMG in the Netherlands
Mark E. Straub, Global Financial Services Customer Lead