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How to Build a Successful Business Case for AI in Insurance

Expert.ai Team - 2 February 2021

The insurance industry is at a critical juncture right now. As combined ratios continue to narrow and business processes remain inundated by text-heavy documentation, organizations are in desperate need of process efficiencies to improve their economic outlook.

Fortunately, artificial intelligence has proven effective in augmenting numerous time- and text-intensive underwriting processes including risk engineering, policy review and claims management — among others. But it’s not quite so simple.

AI is a powerful technology that, when applied correctly, can transform the way a business functions. The problem is that companies fail to put enough thought into the business cases that should be driving these projects forward. This is why nearly 80% of companies have reported their AI projects stalling, according to Dimensional Research.

This goes to show that AI is not a silver bullet, but rather a technology that you must carefully approach and integrate into your larger business function. So how do you draft a business case for AI that covers all the bases before you fully commit? I’ll show you how.

Establishing Your Core Business Case

Preparation makes all the difference when it comes to establishing AI at your company. Those who are most successful with it are those that have thought out every detail well ahead of time and know exactly how it can and should impact the business. There are many factors to consider, so let’s start from the top.

Identify Your Business Objective(s)

Artificial intelligence is not a one-size-fits-all solution — especially within the insurance industry. How one company hopes to benefit from AI will not necessarily align to the needs of your own. So be clear as to what you seek to gain from AI because this is the foundation of your investment. You do not have the benefit of throwing things at the wall and seeing what sticks.

More than likely, you are looking for AI to support one at least one of the following:

  • Process acceleration
  • Reduce cost of service
  • Loss reduction/avoidance
  • Scale your capacity

You can certainly work towards multiple objectives, but be careful not to overextend yourself. You are better off focusing on one primary objective then expanding your scope once you have established some modicum of success.

Establish Areas in Need of Intelligent Automation

Once you have identified your business objective, you can begin to consider where AI can provide these benefits. Take a look across the business and identify the specific lines of business that are particularly exposed from the standpoint of expense or loss. Not every line of business will benefit from AI or benefit enough to make it a worthwhile investment, so it is important to zero in on those that can deliver the most value.

This requires a thorough review of the economics of each business line. Two quick metrics you should consider when framing the potential impact of a solution include:

  • How many cases/transactions does this function (e.g., claims or policies) handle?
  • What target efficiency gain (e.g., hours saved per claim) is realistic?

You may have your mind set on how you intend to use AI, but if the numbers tell you to start somewhere else, listen to them.

Define Your KPIs

Regardless of your business objective, every investment is ultimately measured by its economic impact on your business. Though it can be tricky to apply tangible KPIs to artificial intelligence initiatives, there are several that you can point to in your business case.

  • By how much have you reduced exposure? Leakage is one of the most pressing issues facing insurers today. By applying AI to your risk engineering process, you can assess risk evaluations faster and establish a more consistent grading system.
  • How much more efficient has your process become? Speed is the name of the game for several underwriting processes. By cutting down the processing time of lengthy documents like risk evaluations or policies, you can significantly increase both your output and capacity.
  • Are you winning more business? Improving process efficiency can also impact your success with the end customer. By turning policies around faster, you can stay top of mind with customers and put yourself in a better position to win their business.

If you do not have firm KPIs in place to monitor your progress, you cannot accurately assess the value AI provides to your business. This is your opportunity to define how you achieve your business objectives, so be sure to align them closely.

Mapping Out Your Infrastructure

Finally, you must evaluate the work necessary to customize and operat­e a platform that fits the needs of your application area. AI is not a plug-and-play solution, but rather a complement to your existing processes. So instead of putting the cart before the horse, carefully map out what you need with regards to expertise, data and more.

“One of the biggest [reasons] is sometimes people think, all I need to do is throw money at a problem or put a technology in, and success comes out the other end, and that just doesn’t happen.”
Chris Chapo, SVP of Data and Analytics, Gap

Compare and contrast various application options based on their potential to produce both short-term wins (e.g., quicker return on investment) and long-term strategic improvements (e.g., higher level of explainability). In light of other corporate initiatives, this serves to establish a cognitive roadmap for your business.

Final Thoughts

There are already plenty of well-established business cases for AI in the insurance industry (e.g., control expenses, reduce leakage, etc.), but the technology is still maturing, and new applications are emerging every day. It’s up to you to figure out what best applies to your organization.

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