Data Quality for Banking
The company, born from the merger of large IT service providers for banking, specializes in IT outsourcing back-office services for the banking sector and offers its clients integrated and flexible technological solutions aimed at improving business performance."
The context
The lack of a centralized tool for data governance and quality exposed the company to risks and delays.
Processes for each individual banking area were segmented and inefficient, and no quality controls or automated remediation and correction processes had been designed for the most critical data, such as those related to customer data, regulatory reporting, anti-money laundering, and accounting.
In the absence of clear standardization of processes and applications, the client banks each used a different system, creating a negative impact on the quality of banking data and making the maintenance of individual systems complex and costly.
The company had already initiated a large-scale Data Governance project aimed at involving and converging all of its clients' banking data processes toward a centralized system, easily usable and capable of managing large amounts of data in a virtuous way, in compliance with the stringent regulations required by the banking sector in Italy and Europe.
Within the master Data Governance project, a key role was assigned to the design and implementation phase of activities aimed at improving data quality, with the objective of creating processes capable of detecting errors and imperfections in data and ensuring rapid revision. The company needed a partner able to oversee the development and execution of the Data Quality project and turn the identified objectives into reality.
Solutions
In the first planning phase, we carefully analyzed the context of the scope and the Data Quality requirements identified by the client, who provided us with the necessary guidance on the controls needed for the areas under examination. We then developed the individual controls and moved on to the execution phase: the controls were applied across the board to all banking data, in order to identify anomalies and deviations from the established quality standards. The results of the control, classified as positive or negative, were automatically recorded in detailed reports.
In the next step, we performed a dual check: on one hand, we ensured that the processes were carried out correctly - without any operational errors - while on the other, we verified that the positive and negative outcomes recorded were indeed consistent with the rules set during the development phase.
The negative results of the control, once obtained and validated, were then reported to the respective Data Owners, so they could proceed with the remediation phase, in which the data that failed the control is reviewed and corrected to ensure it returns a positive result in the next control.
The results
The company has started converging all its internal Data Quality processes into a single application. The outcomes and evidence from periodic Data Quality controls in the involved areas are now collected in a centralized and standardized manner. By using a single, user-friendly dashboard, the company is able to provide its clients with clear reporting, highlighting the results of the controls and enriched with all the necessary details to take corrective actions on the data.
The existence of a central hub now allows the company to replicate the employed model and gradually extend the Data Quality project to cover all areas that require the production and management of data.
Thanks to the system for reporting negative results, the Data Owners now have full awareness of where and how to make the necessary corrections, thus minimizing the effort required for data control. In this way, the information assets of the bank clients gain uniformity, improve in quality, become more reliable, and the company’s clients are protected from sanctions and reputational risks.