Eviden Frictionless Underwriting Risk 4Months Implementation using Gen AI

Frictionless Underwriting - Commercial Insurance Risk Assessment powered by GenAI

Insurance Underwriting is a very complex, manual and time-consuming process. Underwriters typically have to skim through large contract documents and Insurance proposals manually. Risk assessment is done manually, making the process tedious and slower. Hence, their ability to process or reject the application slows down, resulting in a lower quote-to-bind ratio.

Innovations in Generative AI are transforming organization’s ability to make quicker and accurate decisions. Risk assessment process in the Insurance industry is getting transformed with the advent of Generative AI.

Our solution leverages our AI accelerator, the Intelligent Document Processing (IDP) framework (on Azure) to extract relevant contents and risks from documents. Generative AI then helps categorize and summarize the various risk types, generate risk scores across all the risk types and finally allow easy querying options to the underwriter.

12-16 Week Implementation Summary:

We will conduct 12-16 weeks project implementation which will involve building a scaleable solution that can handle varying data and complexities. We will ensure solution meets acceptance criteria for the client’s business users (underwriting team) from a usability, data privacy, regulatory and ethical consideration perspective.

Eviden Solution:

This Risk Assessment Solution will help underwriters to capture and score risks accurately and use the information to make decisions. This solution will help transform the risk assessment process and thereby improve quote-to-bind ratio.

Our solution leverages our AI accelerator, the Intelligent Document Processing (IDP) framework (on Azure) to extract relevant contents and risks from documents. Generative AI then helps categorize and summarize the various risk types, generate risk scores across all the risk types and finally allow easy querying options to the underwriter.

• Content Extraction: Unstructured data from the broker slip document is extracted using Natural Language Processing (NLP).
• Document Summarization: The solution leverages the Generative AI capability to provide a summarization feature, that captures a high-level summary of the contents present in the contract document.
• Risk Categorization: The IDP and Generative AI engine extracts and categorizes all risks associated with the respective contract document and provides a summary at individual risk level.
• Risk Scoring: Machine Learning algorithms provide a risk score against each risk type. The score is based on probability and severity of risk occurrences, scored on a scale of 0 to 1.
• Risk Assessment Copilot: Standard and free text querying options allow underwriters to generate responses to their queries related to the contents in the document.

12-16 Week Implementation phase will involve the following:

• Data Gathering, data cleaning and pre-processing to ensure quality and consistency, standardize formats, where necessary.
• Identify features that contribute to underwriting decisions, user acceptance criteria.
• Identify and deploy right GenAI tools (LLMs) and technologies aligned with customer’s environment and requirements.
• Regulatory compliance considerations to ensure legality and ethical use of AI in underwriting
• Interpretability – aim to build and deploy models that provide explainability to foster transparency and trust.
• Mitigate biases by regularly evaluating and adjusting models to avoid inconsistency in underwriting process.
• Implement robust security measures to safeguard sensitive client’s customer information.
• Ensure seamless integration with existing underwriting processes and systems for cohesive workflow.
• Establish feedback loop for continuous improvement, incorporating sights from underwriters/business users and training models with new information to derive better results.

Azure Set-up:

• We can help the customer with the right solution architecture for Gen AI and document processing solution using Azure.
• We offer Professional service to architect the solution using best practices of Microsoft Azure and also support in managing services on Microsoft Azure
• A dedicated Azure subscription will be required in customer’s production environment to enable development and testing