 By Sarah Ludwig, Freelance Writer on behalf of Jooble
This is just one of the valuable lessons that you can learn on the Jooble platform, which also provides a wealth of job opportunities.
How exactly has underwriting evolved?
Before we look into what you can do about the evolution in underwriting, it is worthwhile to step back and assess just how the practice has evolved over the years. As underwriting started accelerating, claims started becoming more and more complicated to the point where an increasing number of risk factors and other unexpected elements illustrated holes in the system. Technology started advancing to the point where underwriting became automated, and now advanced analytics are capable of not only managing processes, but predicting future patterns and needs. You might have questions about what a reasonable salary is these days, given all the changes that are going on. Specifically, to learn about what 40K salary means in the UK, you should first gain an understanding of how technology is changing the field. Then you can figure out where your place should be.
Let’s start by looking at what advancements technology and AI specifically are providing:
Recognition. AI can identify correlations across datasets that can easily be missed by underwriters.
Natural Language Processing. Medical records can be transformed and insights extracted to create structural patterns.
Predictive analytics. Programs can predict such things as emerging risks and future outcomes based upon long-term patterns and historical data.
All these advancements are monumental, indeed. However, they don’t have to mean the end of insurance professionals’ careers. AI is an extremely useful tool, but it cannot act alone.
Risks of letting AI act alone
Employers and employees alike need to keep in mind that there are serious risks to simply letting AI programs run free. One of these risks is of automated cyberattack. We have to remember that AI gathers all the data that it can, and even algorithms can only go so far to dictate what its programs include and don’t include. If there is potentially malicious data out there that AI can potentially grab and include in an analysis, it is perfectly conceivable that a program can do this. Automated cyberattack is a real concern.
Another thing to look out for is bias. The insurance industry has by no means always been fair when it comes to evaluating customers for policies, claims, and other aspects of the industry. While AI can do an excellent job of coming up with detailed analyses, it is up to human professionals to assess results and make decisions about their viability.
How can professionals best use AI to their advantage?
To make our point even more clear, we should look at some examples of different aspects of the industry, and how professionals can work together with their technologies to produce the most effective and accurate outcomes.
Underwriting. People use AI in underwriting to refine the process of risk assessment. AI can be assistive in looking for things like credit reports, debts, and outstanding loans. It can use predictive analysis to make assessments of property location and any other relevant information. However, it can also be wrong. Neighborhoods can change character, for example, and this information might not be available for AI to catch. Therefore, humans are always necessary to check assessments.
Claims. In looking for first-notice-of-loss data, smart triaging, and document processing that are often involved in complex claims, AI can be very effective in gathering and processing the required data. However, this is another area in which the human element continues to be critical. Professionals can complement the analysis done by AI in checking its results. If a professional notices a discrepancy, it can make a big difference in the result of the claim.
Customer service. AI can be assistive in helping insurance companies with various aspects of customer service. For example, chatbots on company websites can provide information on basic company policies, how to file claims, and other standard procedures. For existing customers, bots can become personalized and remember individual information, previous questions, and many important details about individual policies. However, bots are never 100% reliable. There can always be complex situations that go beyond the capability of bots.
Sales. When it comes to sales, professionals can take the analysis generated by AI tools and use it to create long-term sales plans. AI autonomous sales agents are capable of gathering large volumes of unqualified leads and prioritizing them appropriately. It can also help staff both prepare for and summarize sales meetings, which can greatly help reduce workloads for people. In assessing the results of AI analysis, professionals can strategize and help create a more refined long-term vision for their company.
Your job isn’t necessarily at stake, but be careful
For all these reasons, insurance professionals should appreciate the reciprocity that exists between AI technology and their own personal input. If you are wondering if it is still possible to land a decent position with a good salary, the answer is yes. There are definitely jobs out there, but you need to be prepared for the changes that are taking place in the industry. Rather than fearing AI, you can help your cause by learning to understand it better. Keep an eye out for things that it might be doing incorrectly as this is where your role will be.
If you succeed at making necessary adjustments to AI analyses that were produced by your company’s technology, you will have proven your value to the company without question. But you can’t simply sit back and wait for the results; take active measures to work with your company’s software, and the results will become clear before you know it.
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