Underwriters should turn to artificial intelligence (AI) to cope with an array of new and complex risks.

Warren Buffett’s caution about underwriting cyber-insurance put the spotlight on one of the big challenges facing carriers today – how to address a slew of new insurance risks.

The Oracle of Omaha told shareholders at the Berkshire Hathaway AGM that he didn’t want the group’s insurance business to pioneer cyber-cover because the risks were largely unknown and potentially too big. Berkshire Hathaway might write some cyber-policies to stay competitive, added Buffett, but it would not be among the top three providers in this market.

Underwriting complex new risks such as cyber-insurance, as well as meeting the rising demand for cover for other risk-heavy occurrences such as natural catastrophes and corporate fraud, promises substantial revenue for carriers. Global premium revenues for cyber-insurance, for example, could hit US$7.5 billion by 2020, according to researcher Statista. Cover related to digital products and services could also yield healthy additional income. The new revenue streams are welcome news for many insurers that have watched income from traditional products plateau in the past few years.

However, as Buffett points out, venturing into unchartered territory can be hazardous ̶ especially when we don’t know the scope of the hazards. Catastrophe cover, for example, which must now contend with uncertainty related to climate change, cost US insurers dearly last year. The effects of three major hurricanes, Harvey, Irma and Maria, as well as the extensive wildfires in California, all contributed to a spike in underwriting losses. The net underwriting deficit among US property and casualty insurers leaped from $4.7 billion in 2016 to $23.2 billion the following year, according to a report compiled by research firm ISO and the Property Casualty Insurers Association.

Insurers are not only being forced to make calls on new types of risk. They must also handle the growing complexity of the underwriting required for some of their established offerings. The spread of corporate ecosystems and supply chains across many varied countries, for example, has heightened the complexity of commercial risk assessment. So too has the rise in trade and business regulations imposed by governments around the world.

What’s more, insurers must also accommodate a flood of new data streams. While these additional sources of data provide valuable insight into commercial risks and consumer behavior, they also compound the complexity of insurers’ underwriting systems and processes.

To meet the rising challenge of new and more complex underwriting requirements, insurers need to get a lot smarter. Improving workers’ skills and hiring more talent won’t be enough. Insurers need to deploy intelligent technology. Only by using artificial intelligence (AI) will underwriters be able to manage the new, complex risks that are confronting them.

Our research shows that more than 75 percent of insurers plan to use AI to automate tasks in the next three years. Many of these applications are intended to improve efficiency and productivity. The big gains in AI, however, are likely to be achieved by using this technology to improve decision-making.

In my next blog post, I’ll discuss how advances in AI can help underwriters make smarter, quicker decisions. Until then, have a look at these links. I think you’ll find them useful.

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