I recently wrote a post about why insurance companies should consider data consolidation. In that article, I discussed how having your business data in one place could help you make better decisions for your business.
And, at the same time, create a better experience for your customers.
Of course, one might argue that all of that data being streamed into this central “vault” would need to be assessed and analysed to get any value from it.
That’s where artificial intelligence (AI) and machine learning (ML) come into the picture.
Repairer Driven News, a news site for collision repairers, very recently discussed how technology—specifically AI—makes it easier for insurance companies to produce quotes.
Whilst this article discusses auto insurance specifically (given the nature of the publication), what it says is just as easily applicable to other parts of life that require insurance.
Using AI to Calculate Risk
In the past, risk calculations were done manually, based on information provided by the customer. With AI, however, risk calculations can be automated. And, they tend to be more accurate.
Accuracy, as it turns out, is extremely desirable in the world of insurance. That leads to a more logical premium for the customer, which is good for them and the insurance provider.
At the same time, AI is much better at detecting fraud.
Fraud detection requires pattern detection. And, if the fraud is sophisticated enough, humans might not be able to see that pattern. AI, on the other hand, can and will.
According to this article by Business News Daily, machine learning algorithms can detect fraudulent claims with a 75% accuracy rate. Of course, as technology evolves, fraudulent schemes will as well. However, all that means is that data scientists will need to keep up so that AI/ML can keep up as well.
Using AI to Calculate Cost
The article discusses how predictive analysis can determine if a vehicle can be repaired or if it should be written off. It can do that based on information such as the year and model of the vehicle, the type of impact, whether the airbags deployed, and so on.
It also talks about how AI heat mapping technologies can identify which areas of the vehicle were damaged.
With all this information at its “fingertips”, AI can very quickly complete an estimate with no additional help.
In the same way, AI could be used to predict risk and come up with personalised quotes for health and medical insurance, home insurance, pet insurance, and more.
Again, with a better understanding of the cost of treatment or reparations, insurance companies can service their customers better.
Using AI to Mitigate Risk
Safety technology in vehicles is reaching a point where cars can safely (well, more or less) drive themselves. While not all vehicles are autonomous, they do have features that can help human drivers operate a little more safely.
Some of these features, such as parking sensors, rear-facing cameras, and lane detection, can also gather information. This information, in turn, can be processed by AI to help drivers make better decisions; better decisions that lead to fewer collisions.
Helping Insurance Companies Harness the Power of AI and Data
Insurance software providers like Zinnia are offering solutions that help businesses make the most of their data. At the same time, these solutions also help them design better products for their customers, giving them the best experience as well.
For example, Zinnia’s life insurance solutions include data consolidation as well as management. This secure “source of truth” can be used by AI to generate better outcomes for everyone.
And, isn’t that what you want for your insurance business?
Parul Mathur has been writing since 2009. That’s when she discovered her love for SEO and how it works. She developed an interest in learning HTML and CSS a couple of years later, and React in 2020. When she’s not writing, she’s either reading, walking her dog, messing up her garden, or doodling.