Artificial Intelligence and the Future of the Insurance Industry

New technologies and digital platforms are revolutionising the insurance industry, transforming the value chain from underwriting to claims. Integrating automation, artificial intelligence, the Internet of Things, big data, and blockchain enables innovative solutions that enhance customer and insurance company value.

In a McKinsey & Company article, Ramnath Balasubramanian and his colleagues outlined future scenarios for customer behaviour and intelligent solutions for insurance products and services. For example, virtual assistants in the vehicle propose alternative routes with lower accident risks and calculate risk premium adjustments. Also, life insurance policies are adjusted based on how a person lives, with small periodic increases or decreases and alerts of charges in your bank account. All are based on risky behaviours.

A fascinating future, and perhaps also disturbing. A transformation process will be evolutionary and go from a model based on “detect, analyse, and repair” to a model of “prediction and prevention”.

For example, digital assistants are needed so that the company can anticipate customers’ needs and, based on their behaviours, offer cross-selling products such as leisure trips or training courses. Also, the application of artificial intelligence to predict defaults or chatbots to resolve doubts and improve the customer experience

In this article, I would like to present and briefly describe some of the ventures I have had the opportunity to study and analyse as part of the new Insurtech Community Hub and its academy, in which I am fortunate to participate. These examples revolutionise the insurance sector and allow us to understand how artificial intelligence will progressively redesign insurance business models. These companies are Tractable, Aerobotics, Lapetus, and Friss.

Tractable: it is an initiative that has recently won the award for the best start-up in the UK. Tractable uses artificial intelligence for accidents and recovery. Currently, it is primarily focused on vehicle accidents, but there is the possibility that it will grow to cover natural disasters as well. Tractable’s AI was trained with millions of actual images of accidents and repair operations, and it can understand car damage as a human appraiser would. Tractable allows you to speed up claims and eliminate errors that can translate into higher costs.

Aerobotics, a Cape Town-based agricultural technology company, uses satellite and drone imagery and machine learning algorithms to provide early problem detection services to farmers, optimise crop yields, and benefit insurance companies.

Lapetus, an American AI company, uses facial recognition as a biomarker of ageing for life insurance, life expectancy, and wealth management, named after the Greek god of mortality.

Friss is an artificial intelligence start-up that provides an accurate estimate of fraud and risks with the help of expert rules, profiles, predictive models, text mining, link analysis, and all the information available in more than 100 sources of external data. Based on this estimation, a risk score (score) is given. The higher the score, the greater the potential risk of fraud.

Fraud in the insurance industry is a severe problem. The payment of fraudulent claims hurts the loss ratio and insurance premiums, which results in a disadvantage for everyone.

In addition, investigating “false positives” requires a great deal of time and unnecessary costs. The contribution of artificial intelligence to reducing fraud is a direct source of value for all stakeholders.

As a final reflection, it is essential to note that insurance companies must develop a long-term, progressive strategic and transformation plan that affects their business and organisational models, allowing them to compete in this new era of artificial intelligence.

Some companies in the sector have already begun to adopt new innovative approaches, such as developing innovation ecosystems, acquiring insurance companies, and creating alliances with academic institutions, prestigious consultancies, or research centres. Developing internal digital capabilities will be crucial to success.

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