CRM in intermediated financial services markets: THE INSURER’S DATABASE INITIATIVE

CRM in intermediated financial services markets: THE INSURER’S DATABASE INITIATIVE

For a major insurance supplier, justifying investment in a customer database covering policies sold through partners is not easy. During the past three years companies have not only had the challenges of Year 2000 Compliance, the introduction of EMU and the 1998 Data Protection Act, but several have also had the additional challenge of accommodating mergers and acquisitions. During this period competition for scarce IT resources has been tough. All these factors applied to the company in the case study. However, a business case for developing a partnership database was put and accepted and the database built.

Given the nature of the relationships with its partners, the Insurer felt that it was best first to segment customer data by partner. Most analysis is undertaken within the context of a partner relationship and consequently the concept of data marts has had appeal. Indeed several data marts dedicated to specific partner’s customer portfolios are maintained. The database model used combines customer and transaction data pulled from the Insurer’s operational systems into its data warehouse. This is merged with data provided by partners and overlaid with external data, for example geodemographic data such as DEFINE, ACORN or MOSIAC. These latter offer additional ways of classifying customers. Out of this database comes the analysis which can drive customer-facing processes such as cross-selling and up-sell rules, retention initiatives and other ‘triggered’ activity.

The Insurer’s market intelligence systems are mainframe-based and are linked to the numerous transactional systems supporting the various insurance operations. The customer database system is LAN-based, employing several database servers and a number of workstations. The software used is from SmartFOCUS (Asp, Viper & Sidewinder) and SAS. These enable the Insurer to undertake simple counts, line of thought enquiries and ultimately to develop more complex models using CHAID and linear modelling techniques.

A good example of the application of the customer database is to compare the effectiveness of cross-selling household insurance between partners. For example, the Insurer has a sole insurer relationship with Partner A and is free to engage in cross-selling additional lines of cover to the customers. With Partner B the Insurer is simply one of a panel and therefore subject to whether the customer is best served by it or by one of the other panellists.

The customer may have both buildings and contents insured with the partner but only the contents may be placed with the Insurer. The fewer the restrictions that are placed on the Insurer by the partner, the greater the opportunity to practise CRM and to engage in cross-selling and up- selling. However, achieving volumes of business is not the primary objective. The Insurer should also be striving for business that represents value for supplier, partner and customer.

Representative APR 391%

Let's say you want to borrow $100 for two week. Lender can charge you $15 for borrowing $100 for two weeks. You will need to return $115 to the lender at the end of 2 weeks. The cost of the $100 loan is a $15 finance charge and an annual percentage rate of 391 percent. If you decide to roll over the loan for another two weeks, lender can charge you another $15. If you roll-over the loan three times, the finance charge would climb to $60 to borrow the $100.

Implications of Non-payment: Some lenders in our network may automatically roll over your existing loan for another two weeks if you don't pay back the loan on time. Fees for renewing the loan range from lender to lender. Most of the time these fees equal the fees you paid to get the initial payday loan. We ask lenders in our network to follow legal and ethical collection practices set by industry associations and government agencies. Non-payment of a payday loan might negatively effect your credit history.

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