Automation in insurance industry: 34% more accurate pricing & underwriting

.NET

Business analysis

Data analytics

Data management (DMS)

DevOps

Insurance

OCR

RPA

Innowise has implemented RPA to automate claim processing, underwriting, pricing, fraud detection, regulatory compliance, and more.

Customer

Industry

Insurance

Region

Client since

2023

Our customer offers a diverse portfolio of insurance services, including auto, property & casualty (P&C), life, and commercial insurance. The company has become a trusted name in the insurance field, providing a wide range of solutions tailored to multifaceted needs for both individuals and businesses.

Detailed information about the client cannot be disclosed under the provisions of the NDA.

Challenge

Handling inquiries from policyholders manually resulted in multiple errors

Our client was experiencing significant challenges with insurance automation, reporting multiple errors while handling policyholder inquiries, manual claim registration, risk assessment, and policy administration. The primary problem revolved around the labor-intensive nature of work, where client managers had to gather and verify information from various sources, frequently bogged down in a pile of papers. These sources included police reports for auto insurance claims, photos of damaged vehicles or luggage for travel insurance, and medical records for life insurance claims. It often resulted in delays, inefficiencies, and increased risk of fraudulent claims slipping through the cracks.

Therefore, the client approached us expecting to streamline claims processing, improve fraud detection, optimize underwriting and pricing, automate policy administration, ensure regulatory compliance, and enhance their ability to respond to customer inquiries quickly.

Solution

RPA for insurance that automates claim registration, underwriting, and pricing

Based on analyzing the customer’s workflow, we developed an RPA solution that automates the entire insurance pipeline. From claim registration to query response, our specialists also significantly enhanced fraud detection capabilities.

Claims registration

Our first key focus was automating claims registration and processing while enhancing fraud detection, as these processes are the lifeblood of an insurance company. Drawing on our experience, our talented RPA developers implemented advanced data extraction algorithms based on cutting-edge Optical Character Recognition (OCR) technology. It retrieved relevant insurance-related information from various sources, including police reports, photos of damaged vehicles, text from medical records, etc. Once OCR processed information, insurance automation software employed AI-driven algorithms to verify the accuracy and completeness of data, flagging inconsistencies or potential issues for review.

Then, our specialists consolidated disparate datasets through a centralized repository that minimized the chances of data redundancy and inconsistency. This turned fragmented information into actionable insights and significantly reduced the risk of erroneous claims processing.

Underwriting & pricing

Using data integration tools, our project team enabled insurers to collect data from both external and internal sources to evaluate and analyze the risks involved in insuring people and assets. There, we introduced advanced analytics tools specifically designed for insurance underwriting that analyzed historical data, providing insights into previous claims, losses, and risk patterns. This step ensured that underwriting decisions were based on a comprehensive understanding of the client’s risk profile.

To calculate premiums and plan revenue streams, we integrated AI-driven pricing options based on historical customer claims and other risk factors. Our machine learning models analyzed data to determine the most appropriate pricing, ensuring the policyholders’ pricing strategies aligned with their risk appetite and market positioning.

Settlement automation

Besides directly adopting RPA for claims processing, underwriting, and pricing, we implemented automation to streamline transactional tasks, including accounting, settlements, risk capture, credit control, tax, and others. Our software engineers expedited previously repetitive, rule-based, and time-consuming tasks through RPA bots, instrumental in processing and automating settlements. They calculated settlement amounts based on policy terms, initiated payment processes, and updated policy records to reflect these transactions, accelerating the settlement process and minimizing errors.

Additionally, our vetted developers implemented RPA to assist in managing insurance control by monitoring premiums and fees, generating alerts for any breaches, and freezing policy transactions when credit limits were exceeded.

Fraud detection

To identify patterns and anomalies that indicate fraudulent activities, our project team equipped the RPA bots with machine-learning capabilities that analyzed incoming data, including policy applications and claims. RPA bots compared current claims against historical data and found suspicious or ineligible points. Any inconsistencies or deviations from historical trends were immediately brought to the attention of the dedicated specialists. They, in turn, triggered immediate alerts to initiate investigations and take appropriate actions.

Regulatory compliance

Last but not least, our seasoned specialists utilized RPA in performing comprehensive compliance checks. We programmed bots to verify each policy and client adheres to industry regulations, including policy terms, client details, and financial transactions. This included verifying the authenticity of client-provided information against trusted external sources. For instance, RPA bots verified the accuracy of personal identification documents and financial records, ensuring the client’s profile aligns with the information provided.

Moreover, our project team enforced data security and privacy regulations. We monitored and secured sensitive client data through access control, encryption, and compliance with data protection laws such as GDPR, guaranteeing decent protection against breaches.

Technologies

RPA

.NET, C#, Entity Framework, UiPath Studio, UiPath Data Service, UiPath Document Understanding, UiPath Test Suite, UiPath Automation Hub, UiPath Insights

Process

Throughout the development course, our team adhered to the Agile methodology to ensure flexibility and client involvement. The project was divided into 3-week sprints, each with specific and measurable deliverables and intermediate progress checks.

We began with a thorough analysis of the client’s existing processes, pain points, and requirements. Innowise’s business analysts collaborated with key stakeholders to establish clear objectives for the RPA solution. They determined specific tasks and processes that needed automation within insurance operations, such as claims processing, underwriting, compliance checks, and more. At the end of this phase, we delivered a Vision and Scope document outlining the project’s goals and scope.

Based on the analysis, our specialists created detailed flowcharts and process diagrams to map out the steps involved in automation, serving as the foundation for RPA workflows. Then, our well-versed engineers developed RPA bots according to the defined rules and logic to perform specific tasks within the insurance processes.

Our QA specialists performed rigorous testing to ensure the bots execute tasks accurately and efficiently, as well as tested them for compliance checks and exception handling.

Currently, our project team continuously monitors the RPA solution’s performance, addresses any issues promptly, and maintains bots to accommodate changes in processes or regulations.

Team

RPA Developers

RPA Business Analyst

Solution Architect

UiPath Orchestrator Administrator

UiPath Business Process Analyst

RPA Infrastructure Engineer

UiPath QA Engineer

RPA Project Manager

RPA CoE Manager

RPA Support Analyst

Results

27% faster claim registration after developing insurance automation software

Innowise has built a powerful robotic process automation solution for the insurance industry, aiding the customer in claim processing, underwriting, pricing, fraud detection, regulatory compliance, and more. Before approaching Innowise, the client struggled with cumbersome, manual operations prone to errors and miscalculations. From now on, they can benefit from RPA bots strengthened with ML that simplify paper-intensive insurance procedures, allowing managers to focus on more complicated and non-trivial activities.

Through our project team’s work, we delivered a sophisticated RPA solution that improved the customer’s operational efficiency in many areas, from enhanced accuracy and security to faster claim processing and increased business continuity.

Project duration

June 2023 - Ongoing

27%

faster claim registration

34%

more accurate pricing & underwriting

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Automation in insurance industry: 34% more accurate pricing & underwriting

Customer

Challenge

Handling inquiries from policyholders manually resulted in multiple errors

Solution