{"id":70811,"date":"2025-09-24T08:51:52","date_gmt":"2025-09-24T08:51:52","guid":{"rendered":"https:\/\/www.cloudthat.com\/resources\/?post_type=resources&#038;p=70811"},"modified":"2025-09-25T12:11:48","modified_gmt":"2025-09-25T12:11:48","slug":"ai-powered-policy-document-extraction-and-processing-solution-for-a-financial-services","status":"publish","type":"resources","link":"https:\/\/www.cloudthat.com\/resources\/case-study\/ai-powered-policy-document-extraction-and-processing-solution-for-a-financial-services","title":{"rendered":"AI-Powered Policy Document Extraction and Processing Solution for a Financial Services"},"content":{"rendered":"<p>PolicyProcessorAI is a Mumbai-based platform (est. 2021) that delivers insurance and financial products to India\u2019s emerging middle class and underserved markets, using a digital-first approach to make financial services accessible and affordable.<\/p>\n","protected":false},"author":325,"featured_media":70812,"parent":0,"template":"","cat_resources":[6],"technology":[32],"published_by":"325","primary-authors":["6647","917","6068","349"],"secondary-authors":["349"],"acf":{"banner_image":70813,"resources_label":"","download_url":"https:\/\/content.cloudthat.com\/resources\/wp-content\/uploads\/2025\/09\/Finhaat_Two_Pager_CaseStudy.pdf","client_logo":"","highlights":{"first_part":{"icon":336,"title":"90%","subtitle":"Reduction in document processing time "},"second_part":{"icon":335,"title":"95%","subtitle":"Field mapping precision "},"third_part":{"icon":334,"title":"90%","subtitle":"OCR accuracy"}},"the_challenge":"The client faced significant operational challenges in processing large volumes of policy documents, with their manual and semi-automated methods struggling to handle up to 5,000 document processing requests monthly. The existing workflow required staff to manually extract key data points and store information in databases, creating a time-intensive process that consumed substantial resources. This approach struggled to efficiently extract and map critical data fields from diverse document formats, including PDFs and images, resulting in processing bottlenecks, increased operational costs, extended processing times, and potential errors that could impact customer service delivery.","client_testimonial":{"image":"","description":"","author":""},"solutions":"\u2022 Uses Amazon Bedrock\u2019s Claude 3 Sonnet for accurate text extraction and field mapping from insurance documents.\r\n\u2022 Deploys 8 insurance templates with dynamic prompt generation for precise extraction.\r\n\u2022 Secure uploads via Amazon API Gateway, AWS Lambda, and pre-signed S3 URLs.\r\n\u2022 Automated workflow with AWS Lambda functions processes documents into structured JSON responses.\r\n\u2022 Stores metadata efficiently in Amazon DynamoDB for audit trails and integration.\r\n\u2022 Enterprise-level security with AWS IAM access controls, Amazon CloudWatch monitoring, and Amazon CloudTrail auditing.\r\n\u2022 Serverless architecture scales automatically and maintains 99.9% uptime for up to 5,000 API requests monthly.\r\n\u2022 Automates manual processes into a digital workflow, eliminating data entry.","the_results":"Automated GenAI-powered extraction reduced processing time by 90%, improved field mapping accuracy to 95%, and cut manual effort by 85%, enabling fast, reliable, and scalable document handling.","about_client_left_side":[{"field_63315a4dc06e1":"15085","field_63315a5bc06e2":"Industry\u00a0","field_63315a61c06e3":"Financial Services"},{"field_63315a4dc06e1":"15083","field_63315a5bc06e2":"Expertise\u00a0","field_63315a61c06e3":"Amazon Bedrock, Amazon DynamoDB, Amazon CloudWatch, AWS IAM"},{"field_63315a4dc06e1":"15084","field_63315a5bc06e2":"Offerings\/solutions\u00a0","field_63315a61c06e3":"GenAI automation on AWS replaced manual processing with fast, scalable document handling."}]},"_links":{"self":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources\/70811"}],"collection":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources"}],"about":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/types\/resources"}],"author":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/users\/325"}],"version-history":[{"count":1,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources\/70811\/revisions"}],"predecessor-version":[{"id":70815,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources\/70811\/revisions\/70815"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/media\/70812"}],"wp:attachment":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/media?parent=70811"}],"wp:term":[{"taxonomy":"cat_resources","embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/cat_resources?post=70811"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/technology?post=70811"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}