Publications

This McKinsey Quarterly article (registration required) may be interesting for data miners working on insurance applications. Selected quotes:

• "It takes a portfolio of at least 200,000 to a million policies per product line (assuming access to reliable data) to produce a fine and reliable risk segmentation-the prerequisite for more differentiated pricing."
• "the segment-by-segment correlation between premiums paid and claims incurred is often low for individual insurers, and this discrepancy leads us to believe that the pricing of many carriers is more or less random and that they manage profitability on a total-portfolio rather than segment-by-segment basis"
• "Sophisticated insurers use up to 40 variables to price a simple auto or home owners' policy, against the average performer's 15 or so."
• "...the cost of losing the most profitable customers to cherry-picking competitors is too high (Exhibit 3), and, to make matters worse, insurers risk attracting the unprofitable customers whom competitors have intentionally priced away. Once this customer-base swap has taken place, it is hard to reverse, since people are unwilling to switch carriers unless the price difference is on the order of 10 to 30 percent, depending on the segment's price sensitivity. And then the only way to get customers back is to offer below-cost prices."