Artificial Intelligence (AI) has been a game changer in many financial sectors, and the Insurance Industry has proven to be no exception. When used as an analytic tool to mitigate and manage financial risk, AI has provided data unparalleled in nuance to that produced by traditional, human techniques of old.
Faster computers
Computers can easily do the calculation work of many thousands of humans working simultaneously. The sheer operational efficiencies alone of employing computer software to categorize, compare, and calculate the data of thousands, hundreds of thousands or even millions of customers, makes it an economic necessity in the modern age of Risk Management.
Machine learning
Artificial Intelligence has upped the ante in the management and consideration of risk factors in business, not just because of the volume of data it can crunch, but what it can actually DO with that data. Computer systems are now using techniques that normally needed human intelligence to accomplish, such as isolating previously hidden large-scale and small-scale group behaviours as data patterns.
Consumer behaviour
By uncovering the sometimes-hidden trends in the analysis of combinations of inclusive or exclusive data sets, Artificial Intelligence systems allow industry authorities to flag behaviors deemed risky in real time. Using Artificial Intelligence in this way often has a positive outcome for customer service, financial planning for a company, as well as better overall Risk Management for investors and the industry alike.
Scalability
One human’s ability to analyse and see trends in the behavior of thousands or millions of pieces of data are far out-scaled by the introduction of Artificial intelligence into any Industry that has, at its core, a requirement of financial stability and growth. Technology has been rewriting how risk and its mitigation are being approached in the Insurance Industry.
Conventional Risk Management methods are quickly being supplanted with the increased speed, insight and accuracy that intelligent computer systems bring to the table.
These changes ultimately signal learning that can be used to create a better experience for the consumer, as well as a more stable, easier risk path to charter for the Insurance Industry as a whole.
