How Intelligent Automation for Insurance Can Boost Your Bottom Line

How Intelligent Process Automation in Insurance Boosts Your Bottomline


2024 is being called the “Year of Automation” for the insurance industry since an increasing number of insurers are investing in RPA and AI technologies to improve their operations. The era of robotic process automation (RPA) coupled with deep learning is here and boy, is it creating waves across industries and insurance is witnessing its benefits! 

The insurance industry is under intense pressure to adapt swiftly and cost-effectively to customer demands. Enter RPA for insurance and Intelligent Automation. These technologies overhaul key insurance processes like product development, underwriting, policy management, and claims processing. It's a game-changer, enabling insurers to process information faster, more accurately, and economically. On its own, robotic process automation can be invaluable when it comes to functions that are prone to human mistakes, automating mundane tasks and reducing duplication and error rates.

Juniper Research on automation in the insurance industry says that almost half of all insurers will invest in RPA by 2024. Another study from McKinsey on digital disruption in the insurance industry, found that AI automation can cut the cost of insurance claims processing by up to 30%.

RPA vs Intelligent Automation: What’s the difference?

Both RPA (Robotic Process Automation) and AI (Artificial Intelligence) play crucial yet distinct roles. RPA doesn't rely on machine learning or AI; instead, it adheres to predetermined rules and decision trees. Its forte lies in automating routine, manual tasks, bringing efficiency and accuracy to processes.

On the other hand,  AI is geared towards handling cognitive tasks that necessitate intelligence. This includes tasks like data analysis, pattern recognition, and decision-making in complex scenarios.

When RPA and AI are brought together, we get an explosive mix which is intelligent automation. This dynamic duo takes automation to new heights, marking a shift in future trends within the industry. The synergy not only maximizes the utility of RPA but also aligns with the evolving landscape of automation in insurance.

RPA can be described as mimicking human actions while AI mimics human decision making. RPA  for insurance will handle repetitive tasks while AI will bring in decision-making and analytical capabilities improving end-to-end automation capabilities.

RPA Spend by Insurance Companies by 2024

Also Read: AI for Insurance - Everything You Need to Know

Implementing cost-savings through RPA

Nearly every function in the insurance operation can be supplemented with intelligent automation driving strategic decision making, underwriting processes, fraud detection and prevention, claims processing and handling, and even customer-servicing functions. When automation takes over repetitive tasks, key employees will have more time to handle higher-impact requirements. This can drive higher revenues, spilling over to a robust bottom-line improvement.

Use cases for intelligent automation for insurance:

First Notice of Loss (FNOL): This marks the initial phase of claims processing, where policyholders furnish comprehensive incident details. An intelligent bot can seamlessly guide policyholders through information submission, photo capture, and system input without requiring human intervention.

Claims Document Processing: NLP-powered bots excel in extracting data from paper claim submissions, categorizing documents, and entering the extracted information into the claims system.

Fraud Prevention: Bots, trained on fraud detection algorithms, play a pivotal role in identifying and flagging potentially fraudulent claims.

Top use cases of RPA in insurance

Let’s consider how you can implement intelligent automation through a hypothetical new product:

An idea is born

John Wallace, an executive in the automobile division of ABC Insurance Company, is processing a large amount of client data. Using Natural Language Generation (NLG) AI technology, he finds that 30% of the insurer’s existing customers have children on the brink of legal driving age. Wallace immediately recognizes the potential cross-selling opportunity here.

Yet, there is the looming concern of insuring new, high-risk drivers that could increase costs. Wallace makes use of an actuary function that relies on RPA tools to create what-if scenarios that outline a risk-benefit model. The endeavor led to a Usage-Based Insurance product option called the “New Driver Program”, wherein newly-licensed drivers could have a risk-monitoring device installed in their cars that would track their driving behavior.

A product is created

Wallace intimates the product creation and IT departments of this new idea. Using NLG, advanced business intelligence functions and AI automation, the team quickly begins its production. Since ABC Insurance Company has a system that is highly configurable with microservices architecture that allows quick integration of new features with external devices like Alexa, and Google Home, the product speed to market is accelerated.

Marketing is completely automated, with triggered messages sent to customers with children. ABC Insurance Company also times the messages to a month before the potential new driver’s birthday. Copies of the offer are also marked to the client’s agents to make it easy for follow-up, avoiding duplication and human errors. For a foolproof plan, the marketing message for the New Driver Program is also flashed on their consumer portal for all visitors.

Testing the new product

To service its clients efficiently, ABC Insurance automates manual work processes through real-time claims coverage verification, auto-renew, auto-cancel and workflow. Even eligibility, pricing and coverage options are automated using RPA tools that integrate with third-party data sources. This improves pricing efficiency and also helps with process consistency.

The company offers customers and prospective agents to access the product through their website and mobile application. A two-way integrated bot steps in to help both agents and internal users navigate the product features and functionality. For instance, one of the things ABC Insurance’s bot does for the New Driver Program is to notify users about the risk concentration limits on a quote.

Once a user begins purchasing the new product, AI automation features like intuitive context-based navigation, elastic search, and voice-to-text functionalities reduce average handling time. Billing and checkout processes are automated online while smart payment processing supports quick customer checkout and reduces internal loads.

For the claims process itself, ABC Insurance uses an intelligent system for the first notice of loss (FNOL) function, one of the most important touch points in insurance. AI tools here enable real-time coverage verification, automatic claims base reserves are set and claims processing is also auto-assigned.

Monitoring performance

After all requisite approvals, Wallace launches a pilot of the New Driver Program and monitors its progress. Using intelligent business software, he tracks agency and internal performance, hit-ratios, profitability, claims frequency and severity illustrating results. AI indicators show promising results for the pilot program and a possibility for profits of up to 20% in case of adoption. Satisfied with the outcome, ABC Insurance rolls out the product in its key geographical market.

Also read: The 4 Disruptive Technologies Reshaping Insurance Operations

From the hypothetical to real-world transformation

Take the case of Switzerland’s largest insurer, Zurich Insurance. In 2014, the insurer saw the potential benefits of RPA for insurance processes and set out to achieve cost improvements. Through a complete redesign of its claims processing, armed with digital RPA tools and a re-haul of its legacy systems, the insurer was able to achieve over 70% efficiency and 51% cost reductions in areas where it used automation.

Through the transformation, Zurich Insurance Group also freed up employees to work in other important segments, improved claims payments because of correct estimations and completely recalibrated its operations.

Also Read: P&C System TCO – What Are All the Factors in Figuring This Metric?


From the above illustration, you can see how RPA tools and intelligent process automation can completely transform insurance processes. From idea generation and risk analysis to claims processing and policy management, the use of AI automation tools in insurance is multifold. With the industry in the throes of a digital revolution, now is the time to pull the automation lever and transform your operations for good.

If you are looking for the right integration partner to get started on this journey, look no further. At SimpleSolve, we have the perfect software solution for your insurance needs. Our integrated platform is backed with leading technology that will transform your insurance process across all important touchpoints. Contact us to learn more.

Topics: Intelligent Automation

Antony Xavier

About The Author

Antony Xavier

Antony is the President and Co-Founder of SimpleSolve Inc. a company delivering innovative technology solutions to the insurance industry for over 20 years. He brings his decades of experience in finance, insurance and technology to develop modular and configurable enterprise-grade insurance platforms leveraging emerging technologies that bring true value to the industry. Outside of work, Antony spends time traveling, fishing and in the kitchen experimenting with gourmet cooking.

Reach Out To Our Team