Even insurance companies are automating some aspects of their business. Here are five ways insurance companies are using this proven technology.
Life Insurance Claim Processing
When a life insurance claim is made, the information has to be passed through many departments to verify it. If the share is large, there may be additional layers of approval before an insurance adjustor can release the money to the beneficiary. A bot can take the information entered by the claimant and pass it along to each department automatically — saving time and reducing errors.
Within a claims department, several steps must happen before a claim gets paid out or denied. A bot can pass the same information through each step until all of them have been completed and then move on to the next step automatically. This eliminates human error and ensures all steps are completed before moving on to the next.
Insurance companies use independent firms to help determine how much they should charge for premiums based on risk factors - like location and driving record. A company could use a bot to pull data from its database and create reports that go back years for each potential customer or employee in one or two clicks. It would take several employees to manually gather, analyze, and present this data in different forms from different programs.
With automation in place, a company can review a person's browsing history – what they looked at but didn't purchase – and make recommendations in real time instead of having someone manually conclude patterns from those numbers later. Your company can then recommend up-sell additional policies without human intervention.
Underwriting determines if someone is eligible for insurance coverage based on their application information. A bot can verify the data against prior claims, review credit scores and risk algorithms if desired, and pass this information along when needed instead of requiring someone to input this information into different systems.
What is required to get started? Here's a short list.
This is the most crucial step because there will be no further steps without it. You need to convince your management that automation has great potential. Prove that it can help businesses achieve operational efficiency and drive better revenue. In addition, you should know which applications represent the best opportunity for automation based on data volume and complexity, availability of well-defined rules and measurement of cycle times/ lead times for manual processes.
Once you've convinced management of the business benefits, you need to figure out how much impact a bot can have on your company's operations in reducing costs or increasing ROI. You need to find out if it can streamline your operational activities. Based on your preliminary findings, evaluate several approaches, such as which applications are best suited for automation, how much time and money you want to invest into this project, and what kind of return you want to get from it. For example, if your goal is cost savings, try to measure existing labor costs against potential savings using different scenarios. Check if it makes sense to invest in data preparation upfront or not. Suppose you are planning a longer-term automation journey. In that case, consider an 'end-to-end' solution that enables you to easily extend your solution set over time without significant technical disruptions or increases in operating costs.
Business User & End User Teams
After figuring out where automation has the most significant impact on your business, you need people who understand the subject matter and can define detailed workflows for each process and measure the effectiveness of each step for manual tasks. Ideally, business users should be part of departments that directly use applications under consideration for automation. The ideal working model is creating lightweight teams comprising business users, end users, and IT resources who can quickly agree on workflow definitions, test them and measure results against human performance metrics. Conduct a pilot using existing assets, such as an initial set of rules based on historical data, which only needs minor tuning (if any) before scaling up the solution across other applications or systems. This saves money in upfront investments; otherwise, organizations often try to create everything from scratch before deploying automation.
As mentioned earlier, a collaboration between business users, end users, and IT resources are essential for ultimate success. So make sure you have at least one dedicated person to support lightweight teams during the pilot project. It takes little time, but s/he should have good knowledge about the automation solutions available in the market and the ability (or resources) to evaluate those products. Make sure this resource coordinates with development teams so that they can get all the necessary information about APIs needed for automating specific processes. Ideally, they should also know something about code-level programming languages, but we realize this skill set is only sometimes available within IT organizations.
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July 19, 2023