Destination AI: The Advent of Augmented Automated Underwriting

AAU gives underwriters the ability to spot patterns and connections that are either invisible to the human eye or which typically take unfeasible amounts of time and resource to identify.  

 Declan O’Neill //

(Image credit: Gerd Altmann.)

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. Or 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.

And 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.

It may not employ the language of disruption that runs through the wider fintech market, it may be short a few unicorns and 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 towards it.

AI Stepping Up a Gear

But recent research suggests that the journeys made so far have not been in vain. We are at a point where embracement of AI is about to step up a gear. The global value of insurance premiums underwritten by AI have reached an estimated $1.3 billion this year, as stated by Juniper Research; but they are expected to top $20 billion in the next five years. As a destination, it is closer and more attainable than ever before.

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.

AUU, the Latest Generation of Insurance IT

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 gives underwriters the ability to spot patterns and connections that are, frankly, either invisible to the human eye or which 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, 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.

Disruptive Technology

It 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.

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 for their future operations.

AI and New Technology Adoption in Commercial Lines and Workers Comp

 Declan O’Neill //

Declan O’Neill joined Munich Re Automation Solutions in 2015. Munich Re Automation Solutions is a subsidiary of Munich Re, and is a provider of digital new business, underwriting and analytics solutions to the insurance industry. O’Neill is currently Executive Vice President, Product & Data with responsibility for the ideation, develop and on-going management of the Munich Re Automation Solutions’ global product suite. Declan has over 20 years of experience in the life insurance industry. Prior to joining Munich Re, he worked for a primary insurer in a variety of senior management roles across actuarial reporting, model development, IT, product development, marketing, and multi-channel distribution management. O’Neill is a graduate of University College Dublin, Ireland, with a Bachelor of Actuarial and Financial Studies and a Masters in Business Administration. He is a Fellow of the Society of Actuaries in Ireland and Institute and Faculty of Actuaries, and is also a Qualified Financial Advisor. In his spare time, he serves on the Board of Trustees of Pieta House, the primary Irish suicide and self-harm prevention charity.

Leave a Comment

(required)