How Strong Is The Impact Of Artificial Intelligence In The Insurance Industry?
While artificial intelligence (AI) is already in use across many industries, it is projected to grow exponentially in the future. So-called “weak” AI — such as today’s chatbots — in coming decades will give way to more human-like “strong” AI, which will probably disrupt current business models. How will insurance be affected? How can insurers prepare?
Current AI Trends
Artificial intelligence (AI), or machine learning, is software that can think and learn like a human. Today, basic forms of AI can perform specific tasks — like checking an insurance claim for fraud — but future generations will be capable of solving complex problems and making decisions.
AI promises to improve productivity through automating simple tasks and offering new insights from analyzing data and is expected to boost national economies worldwide in the upcoming future. However, for businesses, potential AI threats could easily counterbalance the huge benefits, as they face new liability scenarios and challenges as responsibility shifts from humans to machines.
Already, AI is used in almost every industry: from financial assistance chatbots to driverless cars and from the eradication of certain incurable diseases and delivery of healthcare to remote areas to software that better predicts the weather and tracks the effects of climate change with smart technology and sensors that help reduce emissions.
“Weak” and “Strong” AI
AI “smartness” is proportional to the amount of learned data and not based on high-level semantic concepts such as “risk”, “competition”, “pay-back”, “goal”, “fairness”, etc. Such a difference between how AI and humans learn and conceptualize the world is what differentiates current from future AI systems — respectively “weak” AI and “strong” AI.
“Weak” AI refers to AI technology currently deployed in the business. In contrast, “strong” AI, which will approach human cognitive abilities, are theoretical and not expected to arrive in the market sooner. The introduction of “strong” AI agents will most likely disrupt society as we know it. One of the sectors which AI has already influenced and which it will increasingly disrupt in future is insurance.
Transforming the Corporate Insurance Sector
Insurance, which uses lots of data and repetitive processes has been an early adopter of machine learning, partnering with technology firms and investing in start-ups on many applications. To date, insurers have mainly focused on developing AI applications for personal lines while those in the life and health market are already using AI to review and analyze policy wordings and validate claims.
But, increasingly, insurers are beginning to analyze how AI will impact commercial insurance, including the large corporate market where such products as motor and workers’ compensation lend themselves to automation.
AI is likely to impact insurance in three key areas:
- automation of insurance processes, such as claims and underwriting;
- improved understanding of business risks; and
- increased direct interaction with customers.
AI has the potential to bring about significant cost savings, as well as to speed-up the insurance transaction process. It should enhance services like analyzing submissions, checking or verifying policy documents, developing new insurance solutions and flagging potentially fraudulent claims. There are many areas, such as reputation, cyber, supply chain and economic and climate risk scenarios, where machine learning could help better assess risk.
The claims process, in particular, would benefit from increased automation. AI and automation would make for a much faster and more efficient settlement for lower value claims. Even with more complex commercial claims, however, AI could support claims decisions, speed-up some processes and make for a more customized claims service.
By automating repetitive tasks, people would be free to focus on value-added work, such as client relationships, risk assessment or providing technical support. Insights gained from data and AI-powered analytics could expand the boundaries of insurability, extending existing products, as well as giving rise to new risk transfer solutions in areas such as non-damage business interruption and reputational damage.
But there are also challenges for insurers. To maximize the most benefits of AI, traditional covers such as liability, casualty, health and life insurance will need to be adapted to protect consumers and businesses alike and insurance will need to better address certain exposures such as cyber-attack, business interruption, product recall, and reputational damage.
The 24/7 Insurer
Improved 24/7 customer/market analysis and advising will be the result of increased AI use, along with improved binding, servicing and claims.
For large commercial and corporate clients, insurance needs to be bespoke, allowing for a platform approach to service. AI can help create an environment for insurers and third parties, offering a more targeted spread of risk management and insurance services.
AI could also boost data and analytics and will be the key to unlocking data, especially as more is made available by the Internet of Things (IoT). It could enable insurers to better understand customers’ risks, help businesses reduce exposures and find solutions for perils that currently may not be insurable.
AI-powered analytics could help companies better understand their cyber risks, improve security and even defend against cyber-attacks. At the same time, AI could assist insurers in assessing and spotting the accumulations of cyber exposures.
There are many areas — such as reputation, supply chain and economic and climate risk scenarios — where machine learning could help companies better understand their risks.
As technology becomes more sophisticated, AI applications for analyzing risk will evolve. AI could act as an “intelligent agent” able to create different scenarios and outcomes and potentially make decisions. The next generation of machine learning will move from increasing risk awareness to proactive decision-making.
AI will also work alongside other technologies, most notably the IoT and blockchain, to increase our understanding of risk and enable insurers to offer new, faster and more customized services. For example, sensors on shipping containers are already providing data on the location and condition of cargo, which, once analyzed, can trigger insurance cover or mitigation measures if the goods are damaged.
Insights gained from data and AI-powered analytics could expand the boundaries of insurability, extend existing products, and give rise to new risk transfer solutions in areas like a non-damage business interruption and reputational damage.