Director, Enterprise Data Warehouse, Scotiabank
Scotiabank banks on SAS Data Quality to meet future challenges
The financial services industry is a high-risk, competitive business. To meet these challenges, Scotiabank – Canada's largest international bank – needed a solution to help manage data quality across its retail, small business and commercial banking lines, as well as new acquisitions and mergers. It is leveraging the integrated platform solution for a single version of the truth across the organization, enabling deep insights into customer relationships and improving time-to-market on projects.
Scotiabank, one of North America's premier financial institutions, offers a broad range of products and services including personal, corporate, commercial, and investment banking to more than 12.5 million customers in some 50 countries around the world. In the highly competitive world of banking, Scotiabank has to remain relevant to customers and invest in areas that will not only be profitable today, but also down the road, while at the same time mitigating risk.
The bank was also faced with the challenge of managing data quality in its data warehouse when bringing in new data from mergers and acquisitions. To identify and mitigate potential problems, Scotiabank turned to SAS for an integrated technology platform that enables organizations to analyze, improve and control their data to build a unified view of customers, products, suppliers or any other corporate data asset.
"Knowing how customers interact with Scotiabank is critical to remaining profitable," said Neil Freyke, Director & Head of Enterprise Data Warehouse for Scotiabank. Freyke's team of analysts integrates customer data from different product groups across the organization and presents it in a form that can be used for decision-making. "SAS Data Quality helps us understand customer behaviour and come up with strategies and campaigns to leverage our data assets and remain profitable."
Freyke's team provides services and support to marketing department initiatives, such as direct mail campaigns. But they also provide analytics, reporting and support to all of Scotiabank's business lines – from small business banking to commercial banking to retail banking – making sure each group gets the information it needs to make solid decisions about how to manage the business.
SAS helps us understand customer behaviour and come up with strategies and campaigns to leverage our data assets and remain profitable.
SAS Data Quality has become part of Scotiabank's methodology, allowing analysts to profile data and understand data quality issues. Over the past couple of years, the bank has evolved its CRM data warehouse into an enterprise-wide data warehouse, which expands beyond retail customers to small business, commercial and corporate customers. It's also expanded its use of analytics in the marketing department to include analytics for risk and compliance.
"Using SAS, we've been able to integrate our data assets and present them in a way that can be leveraged across the organization, not just marketing," said Freyke. "Now we have a single version of the truth, where customer information is integrated across the board, and where different product groups can ensure their data is having a greater impact across the organization."
SAS allows analysts to identify if acquired customers already have an existing relationship with Scotiabank, which provides the conversion team with deeper insights into how best to manage a conversion project when acquiring a new company. "The strength of the data warehouse is in the integration of the data, and understanding how that data should be managed down the value chain," said Freyke.
The value of a strong vendor commitment
Scotiabank is working with the SAS Professional Services team on a "match and flag" initiative, where they derive and match profiles of customers on separate systems to see how a customer exists within different areas of the bank. If there's a broken connection, SAS can be used to understand that connection.
"At Scotiabank, any investment we make has to derive as much value as possible," said Freyke. "Our use of SAS helps us understand what drives our customers. And that can be translated through to how we communicate with our customers and what service offerings we bring to the table. SAS helps us achieve this on a tight budget and with limited resources."
WIthout SAS Data Quality, analysts would be managing data quality on the fly by running lots of queries and pulling out sample data. Using SAS, they're able to get to the end result faster and understand the data in more detail. As a result, Scotiabank has been able to decrease its business analysis cycle and ensure data issues are known upfront before they ever become an issue in development. This translates into faster time to market on projects and lower overall development costs.
SAS is committed to education and making sure Scotiabank's analysts remain up-to-date with their skill sets, said Freyke, to drive value for the different product groups and, ultimately, for customers. SAS also helps Freyke's team keep up with the latest industry trends and challenges, such as prospecting for new customers; Scotiabank is in discussions with SAS about its prospecting strategy for the Canadian market, as well as fraud solutions and other areas where SAS could bring value to the business.
"SAS is in touch with what's happening in the financial services industry, and helps us identify how to remain current and viable and relevant, and how we can best leverage the assets we've already purchased from SAS to better position ourselves to face the challenges ahead," said Freyke. "They've taken the time to get to know our business and how they can add value to ensure we're going to remain successful."
Scotiabank needed a solution to help manage data quality across its retail, small business and commercial banking lines, as well as new acquisitions and mergers.
SAS ® Data Quality
SAS provides an integrated platform solution that gives Scotiabank a single version of the truth across the organization, enabling deep insights into customer relationships and improving time-to-market on projects.