New technological breakthroughs in areas like AI, machine learning and RPA (robotic process automation) undoubtedly, change the landscape of the business world at breakneck speeds. However, when we speak about them, we usually think about high-tech industries: manufacturing, IT and so on. Traditional areas of human activity, like insurance or finance, do not immediately come to mind in this context. Meanwhile, the transformation they undergo is no less and probably more dramatic than anything robotics can do with your average factory floor. In this article, we will look at how this new tech changes life insurance and what it means in the long term.
1. Policy Issuance Automation
Issuing an insurance policy, especially when it comes to life insurance, is a notoriously document-heavy process. To successfully complete it, one has to do an enormous amount of paperwork, collect the necessary documents and fill in forms. Mistakes at any stage can make it necessary to redo a significant portion of the procedure. RPA and AI can completely change how it is done by automating a huge part of this work and reducing turnaround times.
What are some of the benefits of doing so:
- Order-to-cash process
- Supply chain management and procurement processes
- HR onboarding process
- SAP login process
- SAP S/4HANA migration from SAP to other business software applications
- Interface monitoring
- Data consistency checks
2. Automation of Renewals and Cancellations
Dealing with renewals and cancellations is an essential and time-consuming part of life insurance work. Introducing AI and RPA systems allows one to automate this process with strategies like:
- Opt-in For Automatic Renewals
- Flexible Package Choices and Pricing
- Multiple Renewal Methods
- Advance Notice of Expiry
- Mobile-Friendly Renewals
- CRM and Billing Integration
- Renewal Automation
They will send out renewal reminders automatically, without wasting the valuable time of human employees. However, it is only a part of their potential application and a rather trivial part at that. What is more important is that they can automatically handle feedback during cancellation, gathering it, compiling it in meaningful form and analyzing it to provide valuable insights for future use.
3. Faster Risk Assessment
With all their attractiveness for both insurance companies and their clients, tailor-made policies have one serious problem: personalized risk assessment takes a lot of time and occupies a lot of effort on the part of the company’s employees. Automated AI-powered systems can significantly speed up this process and underwrite these policies faster than any of the company’s conservative competitors can.
4. Automated Claim Processing
Claim processing is one of the most time-consuming and error-prone parts of insurance work. The introduction of systems based on machine learning allows for automation of at least a significant part of it, freeing up human employees’ time and increasing the general efficiency of the organization. In addition to faster claim resolution and settlement, it offers yet another advantage – introduction of high-quality anti-fraud algorithms allows the insurance firm to detect fraudulent claims at an early stage and more effectively than usual. With how much fraud costs the insurance industry, the importance of this point cannot be overestimated.
5. Real-Time Updates
Every transaction with a customer requires an update of the data in many different databases and data storage. If it is done manually, it takes a lot of time, and occasional mistakes are unavoidable. Introducing automated algorithms allows for real-time updates for almost all customer transactions across all company’s databases. Not only does it increase the speed, but also dramatically reduces the likelihood of errors and overall costs. As a pleasant bonus comes an opportunity to improve the customization and personalization in communication with each client.
6. Better Omnichannel Support
The omnichannel model is getting more and more traction across the business world, and the insurance industry is not an exception. Automation allows for its more effective and efficient enablement, leading to creating a seamless customer experience no matter what channels he/she uses to deal with the company.
7. Personalized Insurance Pricing
Traditionally, risk assessment when dealing with a client was done by analyzing sets of impersonalized data. However, today, with the advent of the Internet of Things and AI algorithms, we get an opportunity to get personalized data about each customer. Automated analytics allow for heavily customizable insurance policies based on a variety of data types. Smart cars can provide information about the customer’s driving habits, wearables, give insights into his/her health, and so on.
As you can see, the new tech has many, not always immediately obvious applications in the world of insurance – applications that can greatly improve early adopters’ positions.