Insuring Full Customer Service
As a consumer, 15 years ago it was easy to define an insurance business vs. a retail bank vs. a financial institution. In today's competitive market, however, the differences between banking, insurance and investment activities are not as clear. Banks are now selling insurance, insurance companies are selling stocks and mutual funds, and investment firms are offering loans to consumers. The landscape of the financial services industry has changed, creating a homogenized industry by which companies are free to pursue growth opportunities for products and services that in the past were off limits.
These new product opportunities offer increased revenue opportunities for insurance companies, but also bring with them significant challenges, especially when you consider their organizational structure. Traditionally, insurance companies were organized into business groups, with each unit representing a specific type of service. A typical insurance company would have a business group for Group Life, Group Health, Property & Casualty and Individual insurance. Customers were treated as customers of business units and not as customers of the company as a whole. Today, as traditional insurance companies develop into financial service organizations, they need to manage customer relationships from an enterprise level and control customer acquisition costs for their new product offerings.
Consolidating Customer Data
One solution that many insurance companies are turning to is to consolidate their customer information into a central repository or data warehouse. This enables them to view the entire customer.
Developing a consolidated view of their customers allows these companies to provide better customer service, identify cross selling opportunities and treat their customers as individuals. Without having to re-engineer their entire business, companies are using customer information systems to help them effectively manage their customer relationships.
A good example of this is what a large northeastern mutual insurance company was able to accomplish by building a Customer Information System. In two years the company increased their customer retention by 2 percent, which, according to the American Customer Satisfaction Index, is equivalent to cutting operating costs by 10 percent.
To look at it another way, consider a company that generates $20 billion in revenue annually and has 40 million customers. The annual value of a customer, on average, is $512. A 2 percent increase in customer retention represents 800,000 customers a year, which translates into over $409 million in annual revenue due to customer retention (see Table 1).
Annual generated revenue: $20 billion
Customer database: 40 million names
Average customer value: $512
Increase in customer retention: 2%
Additional customers retained: 800,000
Customer retention opportunity: $409 million
Table 1: Customer Retention Value and Data Quality
Data Integrity - A Critical Success Factor
Let's take a closer look at what the mutual insurance company in the Northeast did to manage their data more effectively. First, they developed and implemented a customer information data warehouse that serves as a central repository of customer information. The data warehouse pulls customer information from each of the individual operational systems that are managed by each of the company's business units. The data is extracted and then merged on a regular basis so client level portfolios can be maintained, offering the company an enterprise-level view of their customers.
The insurance company quickly realized, however, that the data they were pulling from each of the business units had quality problems - the same customers were entered into more than one database under different spellings of their names, much of the data was out-of-date and data, such as telephone numbers and social security numbers, was missing. Without good quality data the company's efforts to consolidate their customer information and use that data effectively were severely hampered. As the Vice President of Operations and Systems stated, "None of us will be able to tell you the actual cost of having bad customer data, we just all know there is a cost."
By improving the accuracy of names and addresses and populating information that was missing, this insurance company obtained a higher match rate when they consolidated the data, reducing the number of duplicates in the warehouse. They were also able to improve the overall accuracy of their customer information. In fact, the accuracy of the data contained in the warehouse has improved so significantly that the company now plans to feed the data from the warehouse back to the individual operational systems to improve each business unit's day-to-day operations.
As insurance companies transition from being just insurance companies to financial services institutions, they need to understand and manage each customer's varying needs. In order to gain a greater share of each customer, they need to know who that customer is and in order to understand who that customer is they need to have high quality, consolidated customer information.
ABOUT THE AUTHOR:
Eric Malmborg is Director of Technology at Pitney Bowes Software Systems, a Chicago-based data quality solutions company. For more information, visit the Pitney Bowes Software Systems Web site at www.pbss.com, or call (800) 624-5377.
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