How do you price a product without knowing production costs? This is one of the critical challenges that the insurance industry faces constantly. Most industries know the cost of resources - materials, labor, etc. and the profit margin to calculate the price of their products. However, on the contrary, insurance companies do not know the cost of an insurance product when it is initially sold. The cost of the actual insurance product may not be known for years, until all the claims are paid (especially casualty products which can have a long claims tail). So insurance companies (underwriters and actuaries) rely on historic data to predict future risk trends and to determine premium rates so they can price their products accordingly.
Insurance companies remain competitive via customer service, claims experience and financial strength, but mostly by price. So, in order to gain a competitive advantage, insurers need to use price optimization. And insurance product pricing is much more than just the rating process. It includes using tools such as predictive analytical models, impact analysis and what-if scenario simulation to increase rating accuracy and improve profits. Although price optimization is fairly new to the insurance industry, it has been used in other industries, such as travel and retail for a number of years.
Regulations and a lack of reliable IT tools are the typical reasons for price optimization use within the insurance industry. In addition, recent changes to relax regulations and the availability of information on the web mean that price optimization is becoming more prevalent in the insurance industry.
Insurers who want to implement a price optimization solution should consider these essential components:
- Predictive Modeling: Insurers use analytical tools to create what-if scenarios and impact analysis to predict future behavior and improve underwriting performance
- Data Management: The quality of data, especially historic policy, customer and claims data combined with external big data availability is the key to using price optimization
- Analytics Processing: The recent availability of analytics tools, like dashboard tools, helps insurers better understand and evaluate critical risk elements. For example, 20 years ago, credit score was not a widely used input in determining premium rates. Now it is used extensively
- Competitive Landscape: Price optimization requires a thorough understanding of the competition, industry pricing strategies, customer data and customer buying preferences
Primarily, in line of business where price is a key differentiator - such as personal lines auto, home and even some commercial lines - price optimization is a key factor in the success of insurance companies offering these products.
What other factors do you think can insurance companies use to optimize pricing? Leave your comments in the section below.