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Interview with Marco D'Ambrosio: "A disruptive approach to risk management in the insurance industry."

How to revolutionize the insurance industry with models and solutions to assess risk, build customer loyalty, and detect fraud? We asked our Chief Mobility Technology Officer.

The technological evolution represented by the combination of Internet of Things (IoT), Artificial Intelligence (AI), and Automation has proven to be a winning bet in several industries. In the insurance field, particularly in Insurance Telematics, these emerging technologies offer unprecedented opportunities to improve efficiency, reduce costs and provide better service to customers. 

We recently interviewed our own Marco D'Ambrosio on the topic, who provided us with a broad and comprehensive overview of why to take a specific approach and the resulting benefits for companies that choose to integrate these three technologies.

Marco, how would you define with one adjective the integrated use of Internet of Things (IoT), Artificial Intelligence (AI) and Automation in Insurance Telematics?

"Disruptive" is the adjective I use most often to qualify the approach that Insurance Telematics offers to risk management in the insurance industry, bringing benefits to both companies and customers. The integration of IoT, Artificial Intelligence and automation creates new opportunities for improving efficiency, reducing costs and offering personalized service. Insurance companies that adopt these innovative solutions will be able to remain competitive and provide added value to their customers in an ever-changing market.

Point us to four significant use cases that help us understand the benefits of the integrated approach of IoT, AI and Automation in Insurance Telematics?

  1. I would definitely start with Risk Assessment and Rates. Through the use of drivers' driving data collected through telematics devices, it is possible to quantify customers' risk in real time. This data allows insurance companies to set rates appropriate to each customer's driving profile. With detailed risk analysis, prudent drivers can be rewarded with lower rates, thus incentivizing responsible and safe driving behavior. In addition, this innovation can support coaching actions, helping drivers adopt responsible behavior with a significant impact on traffic accident prevention, thus contributing to greater road safety and positive social impact.
  1. There is also an objective advantage in Demand Management. Process automation based on customer data enables more efficient insurance claims management. With the integration of AI and automation, it is possible to automate the prioritization of claims based on importance and automatically approve those that are simple and well documented. This not only speeds up the claims handling process, but also improves customer satisfaction by reducing waiting time and simplifying the claims process. However, I always emphasize that automation does not completely replace human involvement, but complements it. Claims evaluation and approval can be supported by AI systems, but human oversight is always needed to ensure accurate analysis and make appropriate decisions.
  1. A third winning use case? Certainly that, in the long run, of customer retention: the use of customer behavioral data makes it possible to identify the likelihood that a customer will switch to competitors. The information gathered can be used to reach at-risk customers and provide them with personalized offers. Through targeted marketing strategies and appropriate incentives, insurance companies can actively work to retain acquired customers, thereby improving retention and reducing churn rates. However, never forget that an ethical and responsible approach to the use of customer data is always a priority: it is mandatory to respect customer privacy and ensure the security of personal information.
  1. Then there is a fourth use case I would like to mention: the use of integrated Insurance Telematics for fraud detection. The fight against fraud is a common challenge in both the banking and insurance sectors. The use of AI-based predictive models enables insurance companies to estimate the probability that a claim is fraudulent. These claims can be targeted for further investigation, thereby reducing losses caused by fraudulent behavior. Automation of fraud detection processes helps prevent and counter fraud attempts, ensuring greater reliability and integrity in the insurance industry. As with the previous point, fraud detection must be balanced with the protection of customer privacy. Insurance companies must ensure compliance with data privacy regulations and ensure that they use customer information only for legitimate and legal purposes, such as fraud prevention.

Thank you Marco! A truly comprehensive review that shines a spotlight on several aspects of Smart Mobility that are absolutely effective for companies wishing to access integrated and innovative technology solutions. One last suggestion for those who will read this interview?

My dispassionate suggestion, for anyone who feels like embarking on a path of business innovation, is to contact us. At Frontiere, we are constantly working to facilitate access to innovations in all market sectors and, therefore, to innovative business models. It is the principle that has always guided our research and development and that makes our approach to smart mobility and risk management in the insurance industry disruptive.

Get in touch with us

Alessandro Niglio
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