Multiple Dimensions of Price Sophistication
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Multiple Dimensions of Price Sophistication

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  • 1. 14 | Emphasis 2009/2 PROPERTY & CASUALTY INSURANCE MULTIPLE DIMENSIONS OF PRICING SOPHISTICATION Enhanced pricing sophistication has reshaped the property & casualty insurance landscape. A company’s sophistication will be determined by where it places itself along a spectrum of pricing methods with five critical dimensions. By Charles R. Wolstein and Christopher W. Hurst Predictive modeling has been instrumental I competitive sensing could conclude that red cars tended to in driving improvements in pricing sophis- have higher loss costs than white cars, the I pricing strategy. tication that have reshaped the competitive company first had to capture data on car landscape in personal lines over the last color. A current example is advance quote Disaggregating pricing sophistication into five to 10 years. Generally, more sophisti- discounts, whereby prospective policy- its components gives management and cated raters have grown and profited at holders are eligible for a discount if they staff from across functions (from statistical/ the expense of less sophisticated raters. solicit a quote far enough in advance of analytic gurus, to line management, to Pricing improvements continue to spread their current policy’s expiration date. strategic planners) a common vocabulary throughout the industry — from large Obviously, if you don’t collect this infor- for understanding how to enhance pricing companies to small, and from personal mation, you can’t incorporate this feature sophistication, consistent with the compa- insurance to mainstream and specialty into your rating plan. ny’s business strategy, organizational commercial lines. capabilities and competitive position. Sophistication along the data dimension Nevertheless, some insurers have been slow is also a function of what you do with the Data to adopt this transformative technology, data you have before applying modeling The first dimension is data. Arguably, the creating big differences in pricing sophis- techniques. Companies’ databases are often predictive modeling breakthrough came as tication across companies. too aggregated to be useful for modeling, much from recognizing the power of data typically because they were designed for as a source of competitive advantage as In prior articles we have described predic- univariate analysis. To maximize value from the application of advanced statistical tive modeling, competitive market analysis for rating plan design, data need to be modeling techniques. and price optimization. Here we provide accessed at nearly the transaction level. a framework for understanding the key Also, data may require considerable The data you are able to use are a function elements of pricing sophistication, using manipulation and restructuring. For exam- of the volume, type and quality of data that personal auto insurance in the U.S. as an ple, a number of rating factors should be you capture. For each customer segment example. considered not only at the individual analyzed, there must be sufficient and cred- driver level but also for households, ible data from which to draw meaningful DECONSTRUCTING THE DIMENSIONS offering additional potential price discrim- correlations with loss experience and OF PRICING SOPHISTICATION inators. Finally, inserting suitable default competitive prices. Often, thin-data seg- Although many people think of pricing values for incomplete data (for recently ments can be supplemented with external sophistication as primarily a function of programmed rating variables, for example) or competitive benchmarks to increase the rating plan design, it is in fact multidimen- and/or estimating missing values through reliability of the resulting data set. Further, sional. To discuss rating sophistication, modeling techniques can further enhance the data must be systematically captured we will use the framework in Exhibit 1, the value of the starting database. and maintained in a structure that can be on page 16, which displays five dimen- accessed. sions along a spectrum of increasing The richer and more reliable the data about sophistication: policyholders and the vehicles, property While data credibility is important, the I data and businesses they want to insure — type of information available is at least as whether collected internally or purchased I modeling approach important, because breadth of data tends from external sources — the richer and to enable the creative breakthroughs. To I rating plan design more reliable the insights that can emerge take a simple example from the early days from the analysis. of predictive modeling, before one insurer
  • 2. Emphasis 2009/2 | 15 Charles R. Wolstein is a Principal of Towers Christopher W. Hurst is a consultant with Perrin in Washington, D.C. He has expertise in Towers Perrin in St. Louis. He specializes in both life and property & casualty insurance, ratemaking, rating plan design, competitive and specializes in distribution strategy and market analysis, and pricing strategy for per- economics as well as organizational perfor- sonal and commercial lines, as well as reserv- mance improvement. Mr. Wolstein received an ing for warranty lines of business. Mr. Hurst M.B.A. with honors from Columbia Business is a graduate of Northwestern University and School with a dual concentration in finance a Fellow of the Casualty Actuarial Society. and international business. Modeling Approach Finally, the more sophisticated modelers At the upper end of the spectrum, compa- Once a data set has been created, the com- not only use more advanced modeling nies are creating innovative rating variables pany can apply a variety of statistical techniques to better predict loss costs, by leveraging new sources of external data techniques to the data to develop a new they also model other important factors beyond credit scores (e.g., census data, GPS rating plan. As with the other dimensions, such as expenses, conversion/retention technology) and nontraditional internal available resources (e.g., time, financial, and customer lifetime value. data (e.g., billing history, policyholder skilled personnel) and the perceived value information collected for other lines of of advanced approaches in meeting pricing Rating Plan Design business). Such companies may also be needs dictate where companies end up on The rating plan design refers to the rating increasing the level of dependency (or the sophistication spectrum. variables and territory structure that deter- “interactions”) between variables to fur- mine the number of price points included ther improve the risk-based accuracy of On the low end of the spectrum, compa- in the plan. Rating plan sophistication the proposed premiums. nies may either rely solely on competitive is a function of the number of variables, information and agent feedback to update the segmentation of the variables and the Territory structure is an important element their rating plan, or do simple, univariate interactions among the variables. of rating plan design. At the low end of analyses. With univariate analysis, indicated the sophistication spectrum for territorial premium relativities are developed for Many companies have historically associated structure, companies adopt historical ISO just one variable at a time, without regard price sophistication with this aspect of territory definitions in the U.S. This to how these variables interact with other their overall pricing scheme, although it is approach is simple, inexpensive and conven- variables (e.g., age versus gender). Such only one of several important dimensions. ient, especially for companies that don’t a simple approach can lead to gross have enough data to develop their own overstatement or understatement of charged On the low end of the sophistication spec- territory definitions. Moderately sophisti- premiums by segment compared to rates trum are companies that have not yet cated companies develop and file their developed using multivariate analysis. adopted recent segmentation innovations own territory definitions, typically based (such as credit scoring and tiering) or even on analysis of internal loss costs at the In the middle of the spectrum are compa- expanded the number of price points for ZIP-code level. nies that apply simple generalized linear existing variables (e.g., moving from modeling techniques with very few variable banded age ranges to individual driver age More sophisticated companies vary terri- transformations and/or interactions among rating factors). These insurers typically rely tory definitions by coverage or peril — for variables. Such approaches might include on more traditional rating variables such example, a company might have separate just an age variable, whereas more as age, gender, marital status and merit personal auto territorial definitions for advanced approaches could also include rating to determine premiums. Today, rel- liability, collision and comprehensive age/gender or age/credit score combination atively few insurers fall into this category coverages, and distinct homeowners terri- variables, among others. More advanced — but many have moved only modestly torial definitions for fire, theft, wind and approaches might also include different beyond this level, perhaps adding a narrow other coverages. Some also adopt non- transformations of a single variable using tiering structure or a few new variables to contiguous territorial definitions. Exhibit 2 curve-fitting techniques to transform a their traditional rating plan. Reasons for on page 17 illustrates how noncontiguous variable, or other statistical techniques such such a limited approach range from limited territories can help achieve the goal of as clustering, decision trees or neural net- data and resources to lack of management territory design with fewer territories. works to group like values of the variable. appreciation of the need or value.
  • 3. 16 | Emphasis 2009/2 EXHIBIT 1 Five dimensions of rating sophistication NONE LOW MEDIUM HIGH VERY HIGH Data Limited (internal) Internal Low, plus: Medium, plus: High, plus: Bureau Purchased credit More internal data Components of credit Transformed variables Externally purchased info score (i.e., combinations of Geo-demographic, More detailed insured internal/external info) weather, etc. data Modeling None Univariate Simple multivariate Complex models with More complex models Approach significant variable interactions Rating Plan Traditional “ISO” type Few tiers Low, plus: Medium, plus: High, plus: Design Age, gender, marital Country/city/ZIP More tiers Credit (proprietary) Creative new variables status, etc. variations Multiple new variables Interactions between Cross-LOB variables Follow historical ISO Independent territories variables Vary expenses by segment territories (often ZIP-based) Different and complex Different rate for every territories varying by ZIP, possibly for every coverage/peril location Competitive None Quantitative Small sample/profile Rating engine Rating engine Sensing agent-driven Pricing Cost-based Cost-based Cost-based Cost-based with Price optimization Strategy Uniform rate charges Uniform rate charges Limited cross-subsidy competitive/marketing Competitor behavior by class by class consideration Price elasticity Possible variations Possible variations by tier (consumer behavior) across territories to reduce cross-subsidies It is the combination of territory design on competitor rates. However, quite a few price points for this kind of sampling and the number of discrete territorial rates invest relatively modest amounts of time, approach to provide a reliable view of that provides competitive advantage, not effort and resources in this activity (see how they are pricing or how your rates just the number of territories. If the number “Overcoming the Challenges of CMA,” compare across your book of business. of discrete territorial rates is limited (i.e., Emphasis 2008/1 for details on alternative many territories have the same rate), methods). The most sophisticated companies are having more finely specified territories using comparative raters to run their entire provides less value. The low end of the spectrum is defined book of business through competitor rating by qualitative, agent-driven competitive algorithms. This approach provides much Competitive Sensing insights. Indeed, if you sell through agents, more comprehensive, reliable and specific As rating plans have become increasingly like it or not, you will hear from them information about how their rates compare sophisticated and the number of potential about how your prices compare to those to those of competitors. price points has increased exponentially, of competitors. The problem with this understanding competitors’ rating approaches type of input is that it tends to be anec- Pricing Strategy and prices has become much more difficult. dotal and, sometimes, skewed. The next step is to combine data, modeling, But it has also become more important, rating plan design and competitive sensing given the consequences of falling behind This deficiency is the same one that hampers into a coherent and compelling pricing competitors in pricing sophistication and the most common approach to competitive strategy. rate competitiveness. Pricing needs to sensing — rating a sample of risks using reflect (or at least recognize) competitor your best interpretation of competitors’ Target competitiveness is one aspect of rates, as well as insurance risk and cost rating plans. This defines “medium” sophis- pricing strategy, e.g., does the company considerations. tication along our spectrum. Historically, want to target rates at the midpoint of its rating a sample basket of risks could competitive peer group or, say, in the top Very few insurers these days fail to perform provide a reasonable perspective on com- quartile? Another issue is cross-subsidiza- some type of competitive analysis focusing petitors’ pricing, but no more. Sophisticated tion — how much do we want between raters simply offer too many different
  • 4. Emphasis 2009/2 | 17 EXHIBIT 2 Indicated North Carolina personal auto territories — bodily injury (illustrative) Contiguous clusters Noncontiguous clusters 70% When the complexity and costs of further 59% improvements outweigh their practical 60% Percent of total variance Pre-Clustering benefits, you have reached the point of within territories 50% diminishing returns. But since companies 40% continue to invest in this area, even your 30% latest innovation will likely soon be out of 20% Contiguous date. Pricing sophistication really is the 10% Noncontiguous proverbial treadmill — you must keep moving simply to avoid losing ground. The 0% more resource-constrained you are, the 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 harder it is to keep up. Sophisticated and Number of territories large competitors understand this dynamic and are continuing to press their advantage. new and renewal business, across classes I How should we prioritize our efforts to ENHANCING PRICING of business, across territories? (Generally realize the highest and fastest payback? SOPHISTICATION speaking, the lower the inadvertent cross- The case for enhancing pricing sophistica- subsidies, the further to the right on the How far you need to move along the spec- tion is clear. A decade ago, companies sophistication spectrum.) trum is a function of your competitive that started down this path took a major circumstances. If you routinely compete leap of faith, and have benefited from Another fundamental consideration is the against the large national players that have their trailblazing. Today, pursuing rating basis for pricing. On this question, every- been investing heavily in pricing sophisti- sophistication using predictive modeling thing left of center on the spectrum can be cation for a long time, you will need to techniques is “table stakes.” thought of as traditional cost-based pricing. move further along the spectrum to close the At the high end of the spectrum, companies competitive gap. If you tend to compete The questions, then, become tactical: in are exploring price optimization, whereby more with local and regional competitors what areas to move forward, how far to price is a function of loss costs, competi- that have not made such significant invest- move, how quickly to move. Understanding tor rates and customer demand elasticity ments in this area, then you need not move the dimensions of rating sophistication can — factors that allow for optimum trade- so far, at least for now. Keep in mind that help you think through these questions offs between growth and profit (see “Price you will always be at a disadvantage and establish your own road map, either to Optimization for Profit and Growth,” compared to every company that is more retain (or regain) competitive advantage or Emphasis 2008/4). How this “free market” sophisticated than you in its pricing. to close the gap with more sophisticated thinking will fare in the face of the current competitors. regulatory environment is a question that Your company’s focus will depend on your will play out over time. starting point in each dimension and the For comments or questions, call or e-mail particular expertise you can leverage. Some Charles R. Wolstein at 1-703-351-4757, CHOOSING A PATH dimensions require more effort to address charles.wolstein@towersperrin.com, or Our intent is to clarify the dimensions of than others (e.g., addressing significant Christopher W. Hurst at 1-314-719-5846, pricing sophistication to assist in answering data deficiencies tends to be a long-term chris.hurst@towersperrin.com. some key questions, such as: effort with significant technology/infra- I How far do we need to go in each dimen- structure implications). sion to be able to compete effectively?