Fourth largest Swiss bank selects FinScore in its quest toward operational excellence
BCV, a leading regional Swiss bank and fourth largest bank in Switzerland, reviews its core processes - supported by FinScore - to reveal potential for further increasing its productivity by better understanding the cost of bad information quality and the measures to take to achieve this goal.
BCV offers a rich portfolio of banking products and services to its retail, private, corporate and institutional clients since more than 150 years. Today, it is the fourth largest bank in Switzerland with a balance of about CHF 34 billions, more than 70 branches, and representations in Switzerland and other countries. To learn more about BCV visit www.bcv.ch.
Innovative companies do not look at data quality management as a cost factor but rather as an opportunity to enhance their position in the market and with respect to their clients. New regulations regarding money laundering, data protection, corporate governance, and Basel II put a lot of pressure on banks. Good data quality is essential to fully comply with regulations, make better operational and strategic decisions, reduce operational costs and develop better customer relationship.
In the context of the bank's strategic initiative named "Operational Excellence" it wanted to understand and quantify the impact of information quality on process quality and productivity. The mission also had to come with a set of recommendations for achieving ambitious objectives for operational excellence.
« BCV has a great number of complex business processes fed by data originated in multiple data sources, each with thousands of specific rules for their correct interpretation. We will implement a data quality management solution that enables us to quickly discover data quality problems, understand the relationship between data and business processes, and efficiently solve the problems, » says Frederic Le Hellard, vice-director at BCV.
« FinScore’s approach has convinced us since it covers in a very systematic way all aspects of technical, statistical and business data quality. This helps us to enhance our operational performance and – most importantly – to enhance the quality of the relationships with our clients. », says Le Hellard.
Based on FinScore's Information Quality Assessment Methodology a series of interviews was carried out along key processes with representatives from business and IT departments such as marketing, client advisors, data warehousing and reporting, etc. These gave first hints towards areas high sensitivity towards information quality issues.
In a second step data source systems related to the most important processes previously analyzed were systematically screened using descriptive statistics and Data Mining techniques to discover data glitches and data quality issues. Data quality indicators were then calculated to give a powerful and summarized description and quantification of quality.
Finally, in a third step, process knowledge and data quality measurements were combined to compute the impact and cost of information quality. This resulted in a Business Case for Data Quality as well as an Information Quality Scorecard. Also, a set of recommendations for short to long term actions were derived to support the bank on its way forward.
Results and Key Benefits
The detailed assessment of BCV's information quality gave it the necessary knowledge about the current level of information quality, its impact on process and decision quality to act specifically so it can to further enhance information quality on the long run. By enhancing information quality BCV leverages the full potential of data to further strengthen the bank’s market position.