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Credit Suisse

Situation

One of the world's leading financial services companies, Credit Suisse Group provides banking and insurance solutions for private clients, companies and institutions. The Group primarily focuses on investment banking and managing customer assets. Based in Zurich, Switzerland, Credit Suisse employs 80,000 people worldwide.

Challenge

Competition in the financial services industry is intense, and obtaining new customers is an expensive proposition. In order to maximize profitability, Credit Suisse focused on three areas:

Solution

In 1997, Credit Suisse started the "Loyalty Based Management" program, with the primary goal of retaining profitable customers. They invested in a six-member "data mining team" that used the Clementine tool from SPSS Inc. to analyze a robust data warehouse of its 2.5 million customers, each with more than 400 attributes. The analysis was used to identify potential leads among Credit Suisse's customers and intelligently market to them based on their individual preferences and histories.

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Results

Thanks to its smooth functionality, easily editable data flow, and precise algorithms, SPSS Inc.’s PASW Modeler has helped optimize marketing and improved risk management. “Credit Suisse’s data mining activities—analysis and modeling—have been fully integrated into our business processes and have proven their value in many different applications,” said Dr. Alex Nippe, head of data analysis/data mining, Credit Suisse. “The demand for data mining within the  bank is rising all the time, and the strategic component is becoming increasingly important.”

With the help of SPSS Inc., Credit Suisse's data mining activities — analysis and modeling — have been fully integrated into our business processes and have proven their value in many different applications. The demand for data mining within the bank is rising all the time, and the strategic component is becoming increasingly important.

Dr. Alex Nippe
Head of Data Analysis/Data Mining
Credit Suisse

Generated improved customer leads for consultants

In the early stages of the Loyalty Based Management project, customer leads based on data mining analysis were mainly generated for product-related database marketing. Consultants had very limited resources and depended on information that enabled them to use these resources as efficiently as possible. The consultants’ services were also costly and their time and services had to be used effectively.

As a result of the success of the Loyalty Based Management project, Credit Suisse consultants began to see data mining’s benefits and started to use it to sell specific customers targeted services. With PASW Modeler, Credit Suisse can now identify customers, typically the top one percent, who are extremely likely to buy a service, thus increasing the opportunities for cross-selling and retaining customers.

Tailored marketing programs to segmented customers

Detailed segmentation of its vast customer base allows Credit Suisse to develop targeted solutions for its customers. This segmentation is executed inductively using the cluster algorithm and the dimensions are tailored directly to the customer requirements. Each cluster serves as a starting point for individual marketing campaigns. This hierarchical system is advantageous because the customer database is continually researched and monitored. As a result, changes in the cluster structure are quickly identified and appropriate responses are triggered.

Increased efficiency of direct marketing campaigns

It’s not enough to know whether customers are interested in a product. Will they actually follow though and purchase it? Credit Suisse used PASW Modeler to analyze situations where customer interest in a service did not correlate with a purchase. Many times, customers did not have good enough credit and were subsequently refused the service. Improved models factored in credit as a criterion. As a result, the percentage of customers interested in purchasing a service but who were refused due to bad credit was reduced by almost half in subsequent campaigns. The reductions have allowed substantial cost savings. Dr. Nippe affirmed, “We recouped the total costs of the project within two years.”