CRM in intermediated financial services markets: IMPROVING CUSTOMER PROFITABILITY

Within each partner portfolio, Company X wants to know who are the most and least valuable customers, how more higher value customers can be attracted, retained and developed, and how negative value customers can be avoided. Customer value is defined as the product of all contributions made by the customer (in this case premiums paid) less all expenses incurred (acquisition, renewal, claims and other servicing costs). In the case of one partner’s customer portfolio, Figure 2 shows the sum of contributions made by decile (10 per cent) bands of customers ranked from the most valued on the left to the least valued on the right.

The best decile (20,000 customers in this portfolio) contributed 58 per cent of the total value of the portfolio. The best 20 per cent here contribute approximately 80 per cent of the total value of the portfolio. The worst decile makes a 28 per cent negative contribution! But what do these profitable and unprofitable customers actually look like? How can they be identified? The transactional data provided very few descriptors, making it difficult to differentiate between ‘good’ and ‘bad’ customers in any meaningful way.

Customers’ value to the supplier and partner is determined by:

—     the amount of cover requested, which affects the size of the premium — generally the more the better

—     the length of tenure or how long the customer remains with the company — the longer the better

—     the size and frequency of claims experienced — the smaller and less frequent the better.

However, knowing this is only the first step to improving profitability. How can these behaviours be predicted from the information available about the customer?

The first step was to analyse customer profitability by a series of variables (see Figures 3—8).

Figure 2 Customer Value Analysis

Analysis by age

First, the Insurer looked at the relationship between the ten value scores and the customer’s age. It discovered that the 35—54 age band were significantly more likely to be in the high value deciles than the other age groups. The Insurer expected the under 35s to be less profitable than the rest because historically this was true. However, the over 50s had been targeted as a desirable segment for several years on the understanding that they were highly profitable. In fact, due to the heavy discounts needed in order to attract this age group from their existing insurers, a significant proportion of this age group gravitate towards the less profitable deciles.

Figure 3 Profitability vs Age Band

The next set of analyses was made possible by overlaying external data onto the individual customers’ records based on aggregated summaries at postcode level.

Analysis by household income

Perhaps not surprisingly, the better-off households were most likely to fall into the most valuable deciles. This makes sense in that they have more possessions to insure and therefore carry higher premiums but do not necessarily experience higher claims costs.

Figure 4 Profitability vs Household Income

Analysis by family structure

Postcodes where households are predominantly occupied by families are significantly more profitable than those with either married or unmarried couples. Where residents are predominantly singles the households tend to be unprofitable to insure.

Figure 5 Profitability vs Family Structure

Analysis by tenure

The time a customer has spent in their present home has a strong influence on value and it is interesting that the value is highest at six to ten years with value rising to this peak and then dropping off again.

Figure 6 Profitability vs Time at residence

Analysis by creditworthinesss

Creditworthiness is measured by applications for credit and the level of County Court Judgments (CCJs) by postcode. A low level of CCJs is a very positive attribute for insurance some of these single variable observations are probably reflecting a similar phenomenon. For example, younger age groups are more likely to be single, low paid and to have recently moved house. Therefore the Insurer employed a more complex classification tool where a combination of variables could be simply applied.

Figure 7 Profitability vs Creditworthiness

Figure 8 Profitability vs DEFINE Category

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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