Risk and Reward
Enhancing analytics precision and the bottom line through artificial intelligence.
- Georges Prouty
- July 2018
Regardless of the risks [associated with AI], the potential for improvement is significant.
Not a day goes by where we’re not reading something about the realized or potential benefits of artificial intelligence and its subset capabilities machine learning and deep learning.
The value of these advanced analytic capabilities is well-documented, concluding that it’s a game changer for all types of commercial enterprises including insurance. While benefits can certainly be overstated based on current levels of AI maturity, real value can be had and provide companies with greater efficiencies, reduction of repetitive manual tasks, better predictive capability and analytic leverage of digital engagement, internet of things and autonomous vehicles.
The economic impact of AI will be significant year-over-year. Accenture, in its research of 12 developed economies, predicts AI could double annual economic growth rates in 2035, with a projected increase in labor productivity of up to 40%.
In 2030, AI’s global economic impact could total $15.7 trillion from labor productivity improvements ($6.6 trillion) and increased consumer demand ($9.1 trillion), PwC reports.
Examples of AI insurance value include:
- Increased precision in fraud identification with reduction in inefficiencies.
Automation of underwriting, reducing costs and improving flexibility and profit.
Straight-through claims handling and loss visualization for faster decisions delivering customer delight.
Enhanced customer knowledge driving better digital delivery.
Reduction in data management time and effort with analytic robots providing automation.
Better emerging risk identification, including AI risk itself.
The dollar value of potential savings through precision, efficiency, reduction of leakage and brand will be measured in the trillions. The realization of value will be dependent on overcoming potential obstacles which include regulation, AI transparency requirements, privacy concerns and other external unknowns.
With all this good news about AI, is there any downside?
There is inherent risk in any business or human change, especially with something as impactful as AI.
Some of the other risks that could diminish or increase value include: displacement of jobs through AI automation affecting underwriting, claims, IT and administrative positions; changes in job responsibilities spanning the industry with AI able to handle and go beyond some of the traditional static modeling work; bias in data and algorithms leading to incorrect or damaging results; rise of litigation due to AI mistakes and moral issues for autonomous cars leveraging AI.
Regardless of the risks, the potential for improvement is significant. That will provide better bottom-line value through insight, automation and efficiency, which leads to an enhanced market and competitive standing.
The value is well-articulated in the trillions of dollars. And as AI continues to evolve, it will erase some of the current potential risks for companies.
Companies need to create an iterative roadmap for AI usage and operationalization. That roadmap should take advantage of key areas of need and value in the enterprise to transform organizations.
(Best’s Review contributor Georges Prouty is a senior insurance industry consultant with Teradata, specializing in insurance analytics and telematics. He can be reached at email@example.com.)