The rapid evolution in Artificial Intelligence (AI), especially in handling unstructured content, is poised to reshape the commercial insurance sector. While the industry’s business requirements remain unchanged, the way they are handled is set for a paradigm shift.

Commercial brokers manage vast amounts of client information that turns into millions of policy documents, encompassing core lines of business; property, FinPro, casualty, and specialty lines. Each year, brokers and carriers produce, read, and understand millions of pages ranging from policy documents to endorsements, binders, quotes, financial statements, and more. These documents are the heart of the insurance business, and that is not going to change. However, how they are processed is about to be revolutionized.

Today, much of the processing of insurance documents is still done manually, which is time-consuming and prone to errors. With advances in AI, manual document processing no longer makes any commercial sense. One AI-powered technology that stands out as the catalyst for change in the industry is Intelligent Document Processing (IDP).

Early adopters of IDP are benefitting from its power to automate workflows and deliver greater operational efficiencies . The growth of the IDP market is testament to its effectiveness as a transformative technology. Analysts project that the market will double from an estimated $2 billion in 2022 to $4 billion by 2026.

Understanding IDP

IDP uses AI and machine learning (ML), to automatically capture, classify and extract relevant information from diverse documents. The AI in IDP, enables the recognition of patterns, relationships, and context in unstructured data. Furthermore, in the context of IDP, ML models are used to recognize and predict specific data points, structures, or patterns in new documents. The ML algorithms are trained on large volumes of document data. The models can learn from experience improving their accuracy and efficiency. Together, AI and ML empower IDP systems to understand content in documents at a deeper level, substantially reducing manual interventions and enhancing data accuracy and reliability.

Significance of IDP for Commercial Insurance

The critical benefit of IDP for Commercial Insurance lies in optimising time for market facing and technical resources to do more value-add work. Documents need to be checked, reviewed, compared, and analysed in a cost effective and efficient way without errors or omissions exposure.  IDP can be used to automate much of these activities. Use cases include automation of underwriting tasks, improving the accuracy of claims processing, and identifying potential fraud risks.

IDP capabilities include:

  • Complex document analysis: IDP facilitates comprehensive and precise document analysis. It can rapidly process and extract pertinent information from the myriad of documents, to provide detailed insights.
  • Productivity optimisation: By automating document-related tasks, IDP allows insurance professionals to focus on higher value and skilled work, releasing capacity and bolstering productivity and making work more fulfilling for staff by handling repetitive tasks.
  • Enhanced compliance: Regulatory compliance is paramount in the insurance sector. IDP ensures strict adherence to these regulations and minimizes the possibility of oversights or discrepancies.
  • Risk mitigation: IDP’s capability to analyse vast quantities of data swiftly is instrumental in proactive risk identification and management. This practical approach embedded in automated processes ensures more risk visibility and better informed mitigation strategies.

IDP Case Studies

Marsh Streamlined Slip Processing, Enhancing Data Extraction

Marsh, a global leader in insurance broking and risk management services, implemented IDP to modernize the labour-intensive process of manually extracting 120 data fields from slips and supporting documentation across various business lines, geographies, and languages. IDP has resulted in faster document processing, the capture of more accurate business data and insights, and freed capacity to power business growth.

Fortune 500 Title Insurance Company Accelerates Title Verifications with IDP

Before the company adopted IDP, its agents had to manually examine more than 35 types of unstructured documents for every property, to evaluate the chain of title sanctity to generate title reports. The process steps included checking legal documents, descriptions and financial matters. The process was lengthy, time consuming and error prone. Today, the process has been largely automated and significantly speeded up with IDP. The solution from AntWorks reads the 35+ unstructured document types to extract 1,260 data points with Natural Language models generating inference to enhance its ability to read and classify different types of legal content.

The Integration of Generative AI and Large Language Models

IDP in the commercial insurance sector is further boosted by the integration of Generative AI and Large Language Models (LLMs). These advanced AI systems excel in processing and generating text that simulates human knowledge and expression. They can be trained on specialist sector knowledge and accordingly handle the nuances and intricacies of insurance documents, enhancing IDP’s overall effectiveness. Use cases include Generative AI producing synthetic data for training IDP models, and Large Language Models used to improve the accuracy of text extraction.

The Competitive Differentiator

Adoption of IDP can lead to a significant competitive edge through:

  1. Operational efficiency: By streamlining document processes with IDP, the commercial insurance sector can achieve faster operations, enabling rapid policy creations and swift claim resolutions.
  2. Stakeholder satisfaction: Efficient, mistake-free operations invariably enhance client trust. Additionally, when staff members are unburdened from mundane document checks, it results in greater job satisfaction.
  3. Informed decision-making: Generative AI’s presence ensures that front-line staff receive timely insights and support, fostering quicker and better decisions.


As ever, maintaining good data sources and accurate information is critical for the successful adoption of new intelligent technologies and IDP is no exception.

A Bright Future for IDP

The rapid growth of the IDP market shows that it is a necessary technology. It fills a gap in enterprise capabilities – a gap that is growing rapidly due to increasing digitalisation of business. Drivers for the commercial insurance sector include:

  • The growing volume of unstructured data.
  • Achieving efficiency and competitiveness by scaling up automation of document intensive processes.
  • The need for accuracy and fair claims processing in an increasingly litigious world
  • AI, ML, generative AI, and LLMs are becoming more sophisticated and capable, and this is leading to the development of more powerful and accurate IDP solutions that in turn lead to new opportunities for modernization of insurance business.


The future of IDP looks very bright across all sectors and in particular in commercial insurance, given that it is ‘the’ technology for automation of document-intensive processes. Adoption of IDP is not just about process improvements though. It is also about staying ahead as AI developments lead to an operational paradigm shift. Early adopters of IDP in the commercial insurance sector are optimizing their processes and transforming services to achieve a range of outcomes including improved accuracy, efficiency, and stakeholder satisfaction. Adoption laggards will have a much tougher time catching up with the early adopters as the technology advances and increases the gap between them.  

Stay tuned for real use cases and exciting new steps to come at Antworks.

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