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Leverage Turing Intelligence capabilities to integrate AI into your operations, enhance automation, and optimize cloud migration for scalable impact.
Advance foundation model research and improve LLM reasoning, coding, and multimodal capabilities with Turing AGI Advancement.
Access a global network of elite AI professionals through Turing Jobs—vetted experts ready to accelerate your AI initiatives.
50% Faster Underwriting Decisions with Automated Risk Classification
AI-powered automation and OCR-driven document processing accelerated underwriting decisions, improved risk classification accuracy, and reduced manual workload for underwriters, enabling faster policy approvals and business scalability.
50%
Faster underwriting processing: AI reduced manual review time, accelerating policy issuance.
70%
of non-STP proposals automated: Freed underwriters to focus on complex cases.
60%
More accurate risk classification: Minimized human error.
About the client
A leading health insurance provider specializing in retail and group health coverage, overseas medical insurance, and personal accident policies. With a pan-India presence and a network of 7K+ hospitals, the company serves millions of customers, pioneering innovative insurance solutions and industry-first offerings.
The problem
The client’s non-STP underwriting process relied on manual workflows, causing delays, inefficiencies, and high operational costs. Key challenges included:
- Manual proposal reviews: Underwriters spent excessive time reviewing medical documents, slowing policy approvals.
- Inconsistent risk classification: The lack of automation led to inaccurate risk categorization, increasing underwriting discrepancies.
- High operational costs: Manual document handling and risk assessment required extensive resources, limiting scalability.
These inefficiencies increased loss ratios, delayed policy issuance, and impacted business expansion efforts.
The solution
Turing developed an AI-driven underwriting engine, integrating OCR, LLM-powered risk assessment, and intelligent document processing to automate underwriting workflows.
- Medical entity extraction: Utilized Azure OpenAI’s LLM to extract and categorize medical conditions from unstructured documents.
- Risk classification engine: Implemented AI-powered categorization into Red, Amber, and Green risk levels based on underwriting heuristics.
- Intelligent document processing: Deployed OCR-based data extraction, digitizing medical records for faster decision-making.
- Automated pricing decisioning: Introduced AI-assisted pricing models, reducing dependency on manual assessments.
- User-friendly interface: Developed a Streamlit-based UI, enabling seamless document uploads and real-time underwriting summaries.
The result
- 50% faster underwriting processing, reducing manual workload and accelerating policy issuance.
- 70% of non-STP proposals automated, freeing underwriters to focus on high-risk cases.
- 60% more accurate risk classification, minimizing human errors in risk assessment.
- 30% cost reduction, lowering manual processing expenses and improving operational efficiency.
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