The deep learning technologies needed for this are already here — think neural networks or machine learning techniques. All of these fall under the umbrella of artificial intelligence, and will help the insurance industry move from a ‘detect and repair’ model to a ‘predict and prevent’ model.
It’s a similar story with other industries which are considering implementing AI. For example, cyber security.
>Read more on AI’s role in cyber insurance
‘The pace of change will also accelerate as brokers, consumers, financial intermediaries, insurers, and suppliers become more adept at using advanced technologies to enhance decision making and productivity, lower costs and optimise the customer experience,’ writes Ramnath Balasubramanian, partner at McKinsey, Ari Libarikian, senior partner at McKinsey, and Doug McElhaney, associate partner at McKinsey.
“Currently, the greatest benefit we see is an enhanced and prioritised customer experience, followed by streamlined back-office processing and improved fraud detection,” explains Harald Gölles, CTO at omni:us.
Related: Being a CTO for an artificial intelligence solutions provider – Harald Gölles, CTO of AI provider, omni:us, talks about his role in the organisation
“By automating tedious and labour-intensive business practices, insurers are subsequently able to increase revenue and free up time for customer-facing interactions.”
The technology has already begun entering insurance systems and processes, and started to deliver efficiency, while improving the customer experience. Automating claims processing through AI solutions is the crux of this unrelenting transformation.
Responding to the market
Why is there a need to integrate AI into the global insurance market?
Digital innovation is changing the way people engage with different businesses. Customer standards and expectations are also changing, as a result.
“While traditionally slow to innovate, insurance companies are constantly feeling the pressure to react to customers’ changing expectations and provide an optimised experience,” explains Gölles.
“AI is specifically beneficial for insurance companies as much of the delay in claims resolution comes from the vast amounts of data that must be processed.” Technology and expertise is changing that.
“Overall,” says Gölles, “artificial intelligence allows organisations to be more customer-oriented by personalising their experience, better understanding customer behaviour, streamlining the claims process and preventing fraud”.
Adapting to AI
Insurance is an industry that has traditionally been slow to adopt and adapt to new technologies.
“There’s often a lack of understanding of what AI is and its benefits,” explains Gölles.
“There’s also an inherent fear when it comes to disrupting current business practices during implementation. This is understandable as AI solutions have previously been characterised by major IT projects and high costs.”
“However, AI technology has improved drastically over the years and can be quickly and seamlessly integrated into businesses in just a matter of weeks, solving a variety of business needs.”
It’s never too late to lay the foundations for future digital improvements. Even historically slow to transform industries like insurance are starting to find small entry points along their value chain to ease the adoption process.
AI in cyber insurance
The global cyber insurance market size could reach $17 billion in premium by 2023, growing over 20%, which shows that decision makers have started to recognise the need to mitigate the risk of security breaches.
Cyber insurance represents a major growth opportunity for some insurers, but pricing and underwriting cyber insurance is not easy. Many insurers rely on historical data in the underwriting process, which may not accurately represent a company’s current cyber risk in a fast-changing, digital landscape. At the same time, consistency and scalability across a human underwriting staff is a challenge. This is where AI can help.
>Read more on Artificial Intelligence — what CTOs and co need to know
Applying AI technologies and predictive modelling to the underwriting process can ensure accurate rating of a company’s cyber risk.
The integration of AI can also achieve underwriting consistency of companies with similar digital footprints.
“The cyber threat landscape of a company in the digital era is ever changing, and the feedback loop from a machine learning system (along with prediction) enables a real-time view of a company’s cyber risk,” writes John Cammarata, VP of development, PointSource.