It’s almost inevitable. Spend your working life identifying, analyzing, quantifying and ascribing monetary value to risk, and you’re likely to have a fairly strong aversion to it. More accurately, an aversion to undertaking new endeavors with inadequately understood consequences. The insurance industry is, on any number of levels, the very definition of risk-averse.
Yet, for all the commentary suggesting otherwise, insurance still has an appetite for innovation. If the insurtech sector is any indication, then an interest in and requirement for new solutions is being recognized and slowly addressed.
Insurance may not employ the language of disruption that runs through the wider fintech market, may be short a few unicorns and may be unable to boast some of the record-breaking funding rounds, but a quiet tech evolution has been building in insurance, nonetheless. Hence the advent of automated underwriting facilitated by more advanced algorithms and data analysis.
Where insurtech does overlap with its more vocal fintech counterparts is in the greater use of artificial intelligence (AI) and machine learning to solve age-old problems around data analysis and interpretation.
It’s about five years or so since AI first became a topic of conversation in insurance. Since then, despite the intensity of the debate, it has often felt like a reality that is always just over the horizon – a destination that kept moving even as more and more efforts were directed toward it.
But recent research suggests that the journeys made so far have not been in vain. We are at a point where embracing AI is about to step up a gear. The global value of insurance premiums underwritten by AI has reached an estimated $1.3 billion this year, as stated by Juniper Research; and they are expected to top $20 billion in the next five years. As a destination, AI is closer and more attainable than ever before.
See also: Untapped Potential of Artificial Intelligence
However, AI is not an island. Its promise of $2.3 billion in global cost savings to be achieved through greater efficiencies and automation of resource-intensive tasks will not be achieved in isolation.
AI remains part of a more complex ecosystem of data gathering and analysis. It can apply new technologies to get the best out of the already established and still-emerging data sources that feature in underwriting offices around the world. It emphatically does not require these existing investments to be ripped out, replaced or downgraded.
It is more helpful, therefore, to see AI as the differentiating factor in the latest generation of insurance IT: augmented automated underwriting, or AAU for short.
AAU lets underwriters spot patterns and connections that are, frankly, either invisible to the human eye or that take normal, human-assisted processes unfeasible amounts of time and resource to identify.
Whereas earlier generations of automation were able to pick up the low-hanging fruit of insurance markets – the individuals whose driving history fit into clearly delineated boxes, for example – AAU can take into account all of the rich complexity of the human experience. It can spot the nuances and individualities that populate the life market, for example, and translate those into accurate policies.
That’s good news for both underwriters and their customers. AAU can significantly reduce the need for separate medicals, repeated questions, and lengthy decision-making processes and drastically increase the speed at which a potential insurer can get a quote and cover – while continually improving the way risk is calculated and managed.
AAU can make sure the decision-making process remains in the hands of underwriters rather than IT departments, enabling them to set and update the rules and parameters as befits their preferred business model. It consequently makes advanced, complex and precise decision-making available to a broader range of underwriting businesses – which is good for those businesses, good for customers and ultimately good for the entire industry.
See also: Strategist’s Guide to Artificial Intelligence
AAU – augmented automated underwriting – is an example of the realization of AI’s promise. As such, it’s set to become one of the key talking points and disruptive technologies of the insurance industry. And this time, AAU is both a journey and destination that all progressive insurance organizations need to be considering.
Finally Realizing the Promise of AI
Augmented automated underwriting, or AAU for short, is destined to become one of the key talking points in insurtech.