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Automated Underwriting Decisions in Seconds

Automated Underwriting Decisions in Seconds

How a Leading Insurance Company Uses Machine Learning and Artificial Intelligence to Make Complex Decisions Instantly?

We were constrained and losing business with every new application. We were getting over 1,000 insurance applications a day which mostly needed to be manually reviewed because of our technology limitations. By the time our team was able to review the applications, in some instances it was already too late. Customers were frustrated with the response time and oftentimes went somewhere else.

Our current system was unable to handle the complexity of applications and our underwriters were overwhelmed with the amount of applications that needed to be reviewed daily. Our current technology platform was costly to upgrade and didn’t keep up with what the new technology platforms provide. Every rule change required a full IT lifecycle to implement. We brought on RapidValue and they worked with us to research and implement a new solution that automates 97% of all applications and made it easier for non-technical resources to author their own rules. It handled all kinds of scenarios and made accurate decisions with surprising accuracy. It allowed our underwriters to focus on the cases that needed deeper thought and research.

We went from kick-off to production roll-out in 4 months. I couldn’t be happier with the results.

~ VP of Operations, A Leading Insurance Company

The client had a tough decision to make. They could continue to use their proprietary system for underwriting decisions or look at implementing a new solution, which is often cost-prohibitive and no guarantee of results. The cost of not implementing a solution was costlier than not exploring other new technologies.Here is a snapshot of process improvement the client achieved after implementing our solution as compared to the existing system.

And here is a chart of how our client significantly reduced the effort involved in application processing with the new system.

The graph below shows improvement in the automation level achieved with the RPA-led Underwriting Decision Engine.

Automated Underwriting Decisions in Seconds

How we did it?

Digital Strategy

We focused on four areas before deciding what technology to implement.

1. Ability to handle “smart” decision making – Does the platform have theability to learn from previous applications, including manual applications,and use technologies such as AI and Machine learning to make decision onits own under our guidance of rules?

2. Ease of use – Can the business add and test rules on their own withoutinvolving a full IT lifecycle?

3. Scalable and can be used by partner portals – Can we extend this tomultiple parts of our business as a service?

4. Implement in under 4 months – Can we get this up and running in ashort time frame, and sunset the existing system?

Together, we decided to use cutting-edge technologies like RPA, AI, ML because it met all of our requirements, and we’ve seen great results in the past for similar clients.

Engineering Excellence

After research and requirement gathering conducted by our technology consultants, RapidValue’s product engineering team along with domain experts set out to build a new underwriting system. To accomplish this, we looked at the customer journey of an insurance applicant and created a digital transformation roadmap that fits the needs of their customers.

We built a scalable Underwriting Decision Engine (UDE) using cuttingedge technologies like RPA, AI and ML. With in-built Artificial Intelligence, the new system can learn from historical records and past interactions and automate underwriting decisions for cases that were being referred to manual underwriters. Rating based profiling system was used for quicker and reliable decisions.

From finding the best-fit technology to implementing it within stringent timelines, the RapidValue team worked closely with the client to build an intelligent underwriting system.

Automated Underwriting Decisions in Seconds

Execution Excellence

Given that we had less than four months to implement a production ready, AI decision making underwriting system, we had to be diligent in the structure of our team and processes.

We made the following decisions:

  1. Agile led execution – We implemented an Agile project implementation structure that fit the needs of their organization and allowed us to move quickly.
  2. Implement QA from Day 1 – We didn’t wait to perform QA until the end of the deployment. We used our testing implementation software to automate many tests as possible and involved the client QA team to perform QA at the end of each sprint cycle.
  3. Roll-out deployment in stages – We were conscious of our timeline, and we wanted to make sure the roll-out was smooth and allow our client’s business users to adapt the new software over a period of time instead of doing a full blown transition.

Digital Transformation Roadmap

When it comes to true digital excellence, it requires a roadmap for the entire lifecycle of insurance application.We looked at the customer journey of an insurance applicant and built out a digital roadmap that fits the needs of their customers.In summary, the client continues to benefit from an AI based Underwriting platform and we are happy to be part of that journey.

About Client

Our client is a leading long-term life insurance provider in India. It offers a range of individual and group insurance solutions that meet various customer needs such as Protection, Pension, Savings, Investment and Health. They have over 30 individual and 10 group products in its portfolio, catering to a diverse range of customer needs.

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