The Art of the Possible with GenAI in Insurance

May 23, 2024 / by Sachin Kachare

Today, there is a lot of buzz surrounding generative artificial intelligence (GenAI) and its potentially significant implications for the insurance industry. The use of GenAI in insurance is taking a large step forward, leading the paradigm shift in AI and machine learning (ML) due to its efficient and innovative features. In the dynamic realm of insurance, burdened by cumbersome manual processes, traditional AI solutions are limited. GenAI transcends these limitations, offering transformative solutions to streamline insurance workflows and propel the industry forward.

Why is GenAI Different?

In our opinion, beyond everything else, the following three characteristics of GenAI make it very different from previous generations of AI/ML:

  • Generally Pre-Trained: GenAI tools come out of the box with the impressive ability to understand the English language and reduce the overhead of training task-specific language models.
  • Ability to Analyze/Synthesize Complex Language: GenAI can effectively summarize text and create new content with little training.
  • Large Context Abilities: GenAI tools can work on large volumes of text to draw inferences.

Insurance Complexities and Limitations of Traditional AI

Insurance is saddled with enormous manual processes that make it error-prone, expensive, and slow. A lot of insurance processes still rely on exchanging documents up and down the value chain. Brokers need to fill out complex forms, review multiple quotes and policies to effectively inform their insured clients about their choices, and then check policies thoroughly for errors. Issuing certificates, managing mid-term alterations, and renewals are all still largely done manually. Insurance companies are also still analyzing forms sent by brokers, reading claims reports and matching them against policy coverage, issuing reinsurance bordereau, and performing many other similar tasks manually.

Traditional ML tools cannot process and analyze insurance language or extract insights from these complex documents. Standard workflow and robotic processing automation (RPA) technology do not support true AI-guided workflow or AI-guided human review and decision-making. This is where GenAI can make a huge difference.

The BluePond.AI Approach to Making GenAI Work in Insurance

While GenAI tools natively bring a high degree of English language understanding and analysis capability, they do not understand insurance concepts. To make effective software for automating human tasks, machines need to understand the insurance terminology, the context of a process or purpose of a document, the references between various documents (e.g., the policy associated with a claim assessment report), different coverage types, and more.

Therefore, to solve complex insurance process automation and document-understanding tasks, BluePond.AI has built our proprietary “P&C Domain Reference Library” to serve as a repository for insurance language, entities, values, fields, coverage, and document types. This reference library is the master orchestrator of the repository consisting of traditional and GenAI tools that, when used in symphony, can execute tasks like a trained insurance professional, thus creating a unique P&C insurance “CoPilot.”

Whether you're an insurer, reinsurer, third-party administrator, or broker, our GenAI-based “CoPilot” approach can help resolve persistent challenges within the insurance industry.

Insurers & MGAs

  • Automatic Audit of Delegated Underwriting: GenAI can assist with the automatic monitoring of policies written under delegated underwriting authority by program managers, MGAs, or cover holders, to ensure issued policies comply with underwriting guidelines at the time of underwriting.
  • Claims Document Monitoring: GenAI tools can automatically identify incoming documents, extract data enabling the population of the claims system, and flag any major risk or severity factors.
  • Ingestion of Loss Assessor Notes: GenAI can identify, match, and extract event details and loss cause/estimate from assessor notes. Plus, it can generate claim trends, seasonality, and complexity insights for underwriting and product development.
  • Matching Claims to Policy Coverage: GenAI can offer automatic matching of claims against policy coverage, including looking through language that changes coverage under certain circumstances.
  • Policy Checking: GenAI tools can help with checking issued policies against submission data, underwriting instructions, and prior terms to ensure there are no errors.

Brokers and Agents

  • Policy Checking: Despite Errors and Omissions (E&O) lawsuits against brokers being on the rise, many brokers and agents struggle to make time for tedious policy checking. With GenAI, policies can be checked thoroughly against expiring quotes and detailed submission schedules when and where required.
  • Quote Comparison: GenAI can create easy-to-understand summaries of complex quotes from different carriers/MGAs even if they widely differ in format and inclusions.
  • Certificate of Insurance (CoI) Issuance: CoI processing is largely a manual process, with various types of non-standard requests making it a complex, time-consuming, and expensive operation. With GenAI tools, we can automate the understanding of CoI requests, extract the right information from policies, and digitize request processing – taking a big operational load off agents’ shoulders.
  • Submission Verification & Inspection Matching: GenAI can intelligently automate submission data verification across various documents and cross-check against third-party data sources.
  • Placement Recommendations: GenAI tools build recommendations on the right coverage for the insured and best-suited markets to place the risk based on the extraction of data from historical quotes and policies of similar insureds.


  • Bordereaux Ingestion: Data entry from numerous long bordereaux remains an operational challenge for reinsurers, which also creates information asymmetry and can lead to leakage of premiums and overpayment of claims. With GenAI-based tools, reinsurers can extract granular data from premiums and claims bordereaux, saving time and cost of data entry while also ensuring treaty conditions are being complied with at a granular level.
  • Claims–Premium Matching: GenAI can automatically match claims information in relation to the assumed (or ceded) premiums and direct premiums through various contract documents to help improve inaccuracies and manual errors.
  • Run-Off Book Monitoring: GenAI tools allow reinsurers to set their own parameters to monitor run-off claims development and flag any adverse or unexpected developments.
  • Loss Portfolio Transfer (LPT) Assessments: LPTs carry billions of dollars of investments and need an accurate analysis of the underlying portfolio to avoid the risk of underperformance. With GenAI tools, the bottom-up assessment of an LPT book becomes feasible, with the ability to scan for exact exposures carried in the policies, assessment of reserve adequacy, adverse claims development indicators, and more.
  • Audit of Cedent Underwriting: GenAI can perform data-driven audits of cedent underwriting based on ingestion of details from bordereaux and cedent underwritten policies.

BluePond.AI: Taking the Friction out of Deployment

The potential of GenAI in the insurance industry is vast. We foresee there being a significant ability to automate complex human processes, leverage AI to guide human review and decision-making, and extract not just data, but also insurance insights from the language in complex documents. That’s why we created the P&C CoPilot Platform. The platform can analyze documents, extract values and fields, and derive insurance insights from complex language (e.g., coverage comparison from two different types of policy documents). However, one might wonder about the difficulty of executing a GenAI strategy in-house. Even if you have a team with deep experience in software engineering or traditional AI, the fundamental construct of GenAI systems is different so it requires a different approach to execution.

For that reason, we have configured our P&C CoPilot Platform as a ready-to-deploy Platform as a Service (PaaS) for any P&C industry participant. With this approach, you will not waste time procuring, testing, configuring, and integrating the fundamental building blocks that are required for a typical GenAI application. The platform is fully configured and ready for quick deployment either as a fully managed PaaS in your environment or as a multi-tenant Software as a Service (SaaS) in ours. It is designed to connect to various data and document sources, an API gateway to connect to internal and external services, and enable seamless enterprise integration.

BluePond.AI manages the ever-evolving GenAI landscape and connects to various best-of-breed services behind the scenes so that you can focus on the insurance use case. We offer complete execution support on data science and software engineering, and post-production human-in-the-loop processing support if required. Even if you have the right GenAI expertise and infrastructure, our platform can still save up to 12 months of setup time and expenses, while providing use case acceleration with our P&C reference library.

To learn more about BluePond.AI and how you can successfully leverage GenAI, visit

Tags: Technology, Data & Technology, P&C Insurers, Data/Tech, Underwriting, AI, Artificial Intelligence, Brokers, Insurance Agents, MGA, BluePond.AI

Sachin Kachare

Written by Sachin Kachare

Sachin has held senior technology leadership roles for many insurance technology companies over the last 20 years. He has driven large-scale underwriting transformation programs for many of the U.S.’s largest P&C insurers. Prior to joining BluePond.AI as their Head of Engineering, he worked at Intellect SEEC as its Head of Products and led the build-out of AI-driven commercial underwriting solutions.

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