Cost saving implications of latest technological advancements attract many companies to invest in them. This is now extra important as firms face heavy pressures due to increasing expenses. Otherwise, they have to make hard choices which could result in losing customers and falling behind in the competitiveness order. In an industry like insurance, many CEOs feel that they have to find digital solutions just to keep up with their rivals.
They have been investing in digital channels for years and it appears to be paying off handsomely. According to cheapautoinsurance.net, most auto insurance policyholders prefer to get in touch with their carriers through websites, rather than using agents. It is a significant shift in customer attitudes which would certainly encourage further investment to bolster this cheaper channel. The good thing is that these companies have deep pockets.
What Is Machine Learning?
Computers can perform many tasks very efficiently and lightning fast using powerful servers, fast internet connection, complicated programs and artificial intelligence. All these are now available for many applications and getting more commonplace and cheaper. They can go through incredible amounts of data, make sense of it and apply to solve problems.
Machine learning is the next step in this process. It allows computer systems to improve on themselves by artificially and automatically understanding the operation they are working on to improve them based on available data without the need to be specifically programmed. That is why it is a mind-blowing cost saving prospect for industries in many ways.
Why Is Artificial Intelligence Promising in the Insurance Field?
There are three characteristics of the insurance industry that makes it ideal for nearly all of the latest technological developments, including big data and smart contracts.
Firstly, Insurers are data hungry because they want to predict customer reactions to things like increasing rates. They want to find out how expensive they can be without existing policyholders walking out on them. The thing is that most people are loyal and trusting. They don’t even get alternative quotes to check how expensive their insurers are unless they get a very high renewal quote. Considering they have millions of customers, being able to charge even $100 more would mean $billions for them.
Secondly, they have tons of information they need to go through and sort out every year. Furthermore, they have an incredible amount of past data that can be used in the machine learning process which is essentially looking at past data, learning from it and applying it to new information presented to them.
What Are the Machine Learning Applications in Insurance?
One area that costs most money in the industry is naturally the claims. A large portion of the premiums collected is paid back to policyholders who need compensation for the losses they suffered. Economies in this area can easily turn the fortunes of an insurance company very fast. Handling them manually is an expensive and slow process and it is highly frustrating for the customers and carriers.
Also, there is enough information to feed through the system that will assist in the machine learning process. Once the customer fills in the details and sends the pictures, computers are able to read it, load it to the system and start comparing the damages with the other similar incidents in their database. This is one area that is very encouraging for the future developments and investments.
Currently, several companies use this technology successfully. They are so happy with the outcome that they actually trust the system to complete the whole process and pay out the claimant. There may be a few glitches but the cost saving implications mean that they can be overlooked. Furthermore, it is believed that it will sort itself out by learning and improving automatically.