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Using Technology to Reduce Operating Costs in Insurance

In February, we published a blog post on “Using Technology to Add Value in Insurance”. That post, referenced Matt Josefowticz’s article – Technology May be the Answer for Insurers, but What Was the Question?, in which he states that there are only three levers of value in insurance: 1. Sell More, 2. Manage Risk Better, and 3. Cost Less to Operate.

This post dives into greater detail on the final lever – Cost Less to Operate. One clear way to reduce operating costs in insurance is to add automation to complex decision-making processes, such as underwriting and claims handling. To keep processing costs in check, many insurance carriers have a goal to increase the percentage of their claims that can be processed and adjudicated with no human decision-making involved. In other words, increasing their rate of straight through processing. By using decision management technologies like business rules, predictive analytics, machine learning, and artificial intelligence, insurance carriers can increase their straight through processing rates and focus team members on higher value activities. For example, underwriters won’t have to spend time making decisions about each policy application, only the exceptions. This frees up valuable time for analysis and business development.

Even for claims that need to be reviewed by an adjuster, decision management technologies expedite the process, improving speed and reducing operating costs. Increasing straight-through claims processing rates also means carriers can decouple the historically-based ratio of adjusters needed by the amount of policies being written. Automating underwriting and claims handling with decision management goes a long way in helping carriers operate more cost-effectively.

Another way to reduce operating costs is to increase the effectiveness of marketing and sales programs. Decreasing the cost of new customer acquisition, customer retention, and cost-effectively cross-selling and upselling clients to maximize the value of the relationship enables carriers to spend less on marketing and sales. Cross-selling can be challenging for insurance carriers because they have only infrequent interactions with customers. Therefore, the offers that are integrated into those limited interactions need to optimize the opportunity to cross-sell and up-sell the customers into higher value products and services. To further improve operating costs, these marketing programs can be fully integrated with agent productivity and effectiveness programs.

Finally, operating at a lower cost means better managing risks and fraud. Predictive analytics can make a significant impact on lowering risk. In the underwriting process analytics help ensure that carriers accept and price policies to properly balance the medical or financial risk against the value of the premiums. Predictive analytic models can also address complex interrelationships between data elements that contribute to risk or fraud and may be too subtle to be recognized by an underwriter or adjuster. The use of predictive analytics to manage risk enables underwriters to focus on those areas of an application where evaluation by an individual can make a difference in the outcome.