As an insurance executive, you know that the industry is constantly evolving. With new technologies emerging every day, it’s important to stay ahead of the curve to provide the best possible coverage for your clients. One of the most exciting developments in recent years is the use of real-time data to build parametric insurance. In this guide, we’ll show you how to use this cutting-edge technology to create innovative insurance products that meet the needs of your clients.

Introduction

Real-time data is changing the way we think about insurance. By using data from sensors, satellites, and other sources, insurers can create policies that pay out automatically when certain conditions are met. This approach, known as parametric insurance, is faster, more efficient, and more accurate than traditional insurance. It’s also more flexible, allowing insurers to tailor policies to the specific needs of their clients.

Step 1: Identify the Risks

The first step in building a parametric insurance policy is to identify the risks that your clients face. This could include natural disasters, supply chain disruptions, or other events that could impact their business. Once you’ve identified the risks, you can start gathering data to create a model that will trigger the policy payout.

Step 2: Gather Real-Time Data

To build a parametric insurance policy, you need real-time data. This could include data from weather sensors, satellite imagery, or other sources. The key is to gather data that is relevant to the specific risk you’re trying to cover. For example, if you’re building a policy to cover crop damage, you’ll need data on rainfall, temperature, and other factors that impact crop growth.

Step 3: Build a Model

Once you have the data, you can start building a model that will trigger the policy payout. This model should be based on the specific risk you’re trying to cover and should take into account factors like location, time of year, and other relevant variables. The model should be designed to be as accurate as possible, so that payouts are triggered only when the specific conditions are met.

Step 4: Test and Refine

Once you’ve built the model, it’s important to test it to make sure it’s accurate. This could involve running simulations or testing the model against historical data. If the model isn’t accurate, you’ll need to refine it until it meets your standards.

Step 5: Launch the Policy

Once you’re confident in the model, you can launch the policy. This could involve partnering with other companies to provide the coverage, or offering it directly to your clients. The key is to make sure that the policy is easy to understand and that your clients understand the benefits of parametric insurance.

Conclusion

Parametric insurance is the future of the industry, and by using real-time data, you can create innovative policies that meet the needs of your clients. With Riskwolf, you can turn real-time data into insurance. Using unique real-time data and dynamic risk modelling, we enable insurers to build and operate parametric insurance at scale. Simple. Reliable. Fast. Contact us today to learn more about how we can help you build the insurance products of the future.

Source: Weekly Tech Pulse