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Development of AI-Powered Insurance Data Extraction and Analytics Platform

techwings.com

Insurance

Data Silos and Manual Processing Inefficiencies

SecureAssure faces challenges with fragmented insurance data locked within unstructured PDF documents. Manual data entry processes are slow, prone to errors, and hinder the ability to derive actionable insights from their existing data assets. The lack of a centralized, automated system prevents efficient risk assessment, fraud detection, and customer service optimization.

About the Client

A leading InsurTech company providing innovative insurance technology solutions to streamline data processing and improve decision-making for insurance providers and businesses.

Key Project Objectives

Develop a robust AI-powered platform for automated insurance data extraction from diverse document formats.
Build a scalable and high-performance architecture capable of handling large volumes of insurance data.
Enable real-time access to structured insurance data for analytics and reporting.
Improve data accuracy and reduce manual data entry errors.
Facilitate seamless integration with existing insurance industry platforms.
Provide an intuitive user interface for data retrieval, visualization, and reporting.

Functional Requirements

AI-powered data extraction from structured and unstructured insurance documents (e.g., policy documents, claims forms, underwriting reports).
Data validation and cleansing to ensure data accuracy and consistency.
Automated data structuring and mapping to a standardized data model.
Secure data storage and access control.
User-friendly dashboard for data visualization and reporting.
Integration with existing CRM and insurance management systems.
Role-based access control.

Preferred Technologies

Microsoft Azure Cloud Platform

ASP.NET Core

Angular

MS SQL Server

Docker

Machine Learning (ML) Models (e.g., NLP, OCR)

Required Integrations

CRM systems (e.g., Salesforce, Microsoft Dynamics 365)
Insurance Management Systems (e.g., Guidewire, Duck Creek)
Data Warehouses (e.g., Snowflake, Amazon Redshift)

Key Non-Functional Requirements

Scalability to handle increasing data volumes and user load.
High performance and low latency for data extraction and analysis.
Robust security to protect sensitive insurance data.
Compliance with industry regulations (e.g., HIPAA, GDPR).
High availability and disaster recovery.

Expected Business Impact

The successful implementation of this platform is expected to significantly reduce operational costs associated with manual data entry, improve data-driven decision-making, enhance risk management capabilities, and accelerate time-to-market for new insurance products. The platform will position SecureAssure as a leader in the InsurTech space and enable them to expand their market reach and customer base.