Business Simulation for Insurance: Best Practices and Getting Started

Insurance companies have a long history of modeling outcomes in order to assess potential future real-world risks and optimize decision making in policyholder strategies. Beyond the predictive models that project individual, coverage or policy segment claim costs – that ultimately lead to premiums charged – carriers also use simulation to make broader business decisions around price disruptions, geographical distributions of policies, investment portfolio risks, and catastrophe concerns.

This reliance on business simulation is critical because insurance carriers must make strategic, integrated decisions across multiple channels and the breadth of their policyholders to reach their objectives. Simulation enables carriers to translate proposed internal changes and external market scenarios into estimated metrics that can help them determine whether they are headed in the right direction. As policyholder journeys and insurance company processes become more digitized and automated, each individual business decision can influence these important metrics – leading to a need for even more robust simulation capabilities. 

Simulation can provide both the experimentation and the guardrails helping insurance companies to explore multiple paths while making sure that they are confident in the path they ultimately choose.

Why Simulation Is Important

Merriam-Webster defines simulation as “the imitative representation of the functioning of one system or process by means of the functioning of another.”  Importantly, it adds “examination of a problem often not subject to direct experimentation by means of a simulating device.”

These definitions speak almost directly to the kind of hurdles insurers face in decision making. For the following reasons, U.S. and Canadian insurers are often perfect use case for the need to simulate real world decision making:

• They are highly regulated. Insurance companies need to answer “what if” questions from regulators on a regular basis where the answers often lead to even more questions. An ad-hoc method to answer each of these questions can be very inefficient.
• They cannot execute “in market” testing. Carrier results are often based on untestable events. Natural disasters cannot be created for review and even standard claim cost development takes too long to use in experimental design.
• They have estimated real-world results that are dependent on a string of decisions. Policyholders have extended journeys potentially across a variety of products and coverages. In a simple example, a claim decision may affect a subsequent renewal decision.

This is especially true as the market becomes more digital and moves at a faster pace. Estimating the result of one decision – for example, coverage premium level – may indicate a positive financial result for annual loss ratio. But without also understanding how online price shopping is influencing retention behaviors, that positive projected outcome may be very short-lived. A comprehensive way to think about and execute simulated results is central to really understanding the strategies that are being implemented.

Current ad-hoc business simulation procedures may be limited both by the challenges in collaboration across groups as well as the ability to quickly create new scenarios to analyze. Picture a scenario where data is accessed by a business outcome simulator that analyzes current and proposed decision strategies and gives business analysts comparisons of the financial and other metrics that matter. This simulation infrastructure can reach into different sources of data as well as decision strategies across the enterprise.

Three Aspects of Simulation to Improve Business Results

A strong simulation platform’s key benefits include organization of enterprise-wide strategies, measurement of cost/benefit metrics, and the ability to empower business and data analysts to drive the process with limited IT support. Each plays a key role in any insurance company’s ability to understand the estimated impact of current and proposed decision making, even when business decisions are interconnected, and markets are volatile.

As carriers look to adopt more comprehensive business simulation solutions relative to estimated real world results, they will need to think differently to generate the best results. Here are three steps to get moving in the right direction.

1. Empower business users to experiment with different scenarios

The most difficult challenges around simulation can be the technical requirements to make the data available, run the decision/strategy logic, and produce the reports for analysis. Often the individual pieces are resident in different technology systems that lead to workarounds and inefficiencies. Imagine an analytic team building a predictive premium coverage model in Python and then a business team having to recode that in Excel to incorporate into their underwriting logic – while participants in both teams wait for IT to produce a database of test cases for the combined strategy.

Even if the teams make this work, what happens when the participants want to tweak the predictive model or modify the test cases to reflect a more competitive market? These disconnects lead to a constrained ability to test scenarios, which means that many potential scenarios will be left unanalyzed.  Using centralized technology where data, analytics and decision logic are accessed makes for the most effective use of any simulation capability. Strong business simulations – and ultimately mathematical optimizations – require the ability to mix and match components in order to uncover the best alternatives.

2. Understand the complete set of metrics related to your results

There are often multiple key metrics related to any business decision or set of decisions. A decision within the claims process can not only affect the ultimate claim cost for the coverage but also the resources necessary to manage the claim and the satisfaction rating given by the policyholder after the completed claims process.

A valuable business simulation gives the carrier not only an estimate of the top-line metric that historically has been measured, but the trade-offs that might offset a “good” or “bad” result. In order to make this happen, it often requires collaboration among groups within the insurance company.

3. Expand simulations around multi-decision journeys

Carriers often have utilized some sort of simulation methodology around individual business decisions. How will this new premium structure affect individual policyholder estimated retention? How would a strong hurricane in Florida change our claim costs nationally? How will a set of new coverages on this life insurance policy grow our presence in this state? However, those individual decisions are just one part of the story.

The new set of coverages mentioned above may show great growth, but their commission structure and cancellation rates by year two may have made the decision a costly one. The new premium structure may have kept retention rates high enough in year one, but the lifetime value of those policies may have told a different story.

Simulation: Understanding before Execution

Simulation is important for insurers because even though the volume of individual transactions can be low, policyholder journeys can span many channels and many years with different kinds of decisions and different value assessments along the way. Simulation is the way to gain an understanding of this policyholder, to project how the policyholder will move through their individual journeys and to execute the chosen strategies that will drive the most important metrics.

With a centralized, platform-based simulation approach, insurers can bring together the pieces needed to run simulations, can put the power of their analysts directly into the scenario building and review, and act quickly to improve customer experiences in an ever-changing market.

How FICO Delivers Insurance Business Simulation

• Read more about business outcomes simulation for insurance
• Watch the webinar Moving at the Speed of Business by Leveraging Decision Testing and Business Outcome Simulation | FICO
• Learn how FICO Platform provides a comprehensive technology foundation for the entire enterprise, including simulation