InsurTech organizations are facing challenges in gaining trust and credibility within the insurance industry due to rising loss ratios and pricing inaccuracies. Chris Gray, the Chief Technology Officer at Inshur, an on-demand embedded insurance services company, believes that many InsurTechs have developed a negative reputation by overpromising technological innovations, such as automatic claims payments with AI, that fail to deliver on their claims. This has led to a decline in reinsurance partnerships and a lack of insurance capacity to pay out on claims.
Inshur operates in the niche market of commercial auto insurance for on-demand drivers in major cities. However, capacity issues within the insurance industry make it a challenging environment to operate in. The company has over 40 years of loss ratio data specifically for fleet, taxi, and delivery drivers, which allows them to understand the demands of on-demand drivers. Inshur is actively working on developing new rideshare and courier insurance products.
Gray emphasizes the importance of adapting insurance models to the on-demand economy. He suggests that incumbent insurers need to embed insurance products into the platforms used by drivers to remain competitive. Failure to do so may result in more agile insurance players with complementary technologies entering the market and meeting the growing demand.
The old breed of InsurTechs focused on growth at all costs, using AI-first pricing and claims handling as a way to attract customers and capacity partners. However, they overlooked the fact that insurance is a specialized field that requires expert knowledge and data. Inshur has taken a different approach by using artificial intelligence and machine learning as augmented assistants rather than replacements for insurance expertise. Their platform incorporates AI for tasks such as ID verification, fraud detection, and claim triage and handling.
To address regulatory challenges, Inshur focuses on refining data models using machine learning before implementing them in real-time. They leverage Google Big Query and AutoML to identify pricing factors and trends, allowing their actuarial team to adjust prices and underwriting criteria while removing biases. Inshur also collaborates with embedded partners like Amazon and Uber to gather bespoke data about customers’ driving experiences, ensuring fair risk pricing for all parties involved.
The article highlights the importance of maintaining human operatives in the decision-making process, even as the industry shifts towards digital and automated services. Inshur’s AI tools are designed to enhance and assist claims handlers, with final decisions made by highly trained professionals. The company also utilizes Google Explainable AI frameworks to understand decision-making processes and minimize bias.