Automating Underwriting in Insurance Using Python-Based Optical Character Recognition
About Automating Insurance Underwriting with Python OCR
Industry: Finance
Business Type: FinTech
The underwirting services are used to validate the authenticity of client’s insurance documents which contains personal & financial information.This was done manually which is to be automated using AI-based technologies such as NLP,Machine Learning & Cognitive computing. Given the surge in customer demand, implementing automation to enhance customer engagement and reduce manual tasks has become crucial.
Our Process
1
Conceptualization
Competition Analysis
Customer Data Analysis
Customer Data Analysis
2
Design
User Journey Mapping
App Design Improvement
App Design Improvement
3
Development
Android App Development
iOS App Development
iOS App Development
4
Deployment
App Store & Play Store Deployment
Post-Deployment Support
Post-Deployment Support
Our Project Challenges
1
The traditional method of underwriting is tedious as it involves manual verification of various documents & proofs.The assessment has to be carried cautiously by the professional as it is vital to safeguard the company’s risk.Such a process result in large verification cycle and possess room for errors resulting in churn of customers.
2
The client’s prerequisite was to develop an OCR model to scan these documents,transcribe them & render a digitized copy.The client was looking for an experienced partner to be their AI Solution Partner who can craft tailored solutions for insurance industry.
The Results
Enhanced Data Accuracy: By leveraging document classification, our OCR model improved data accuracy and minimized the risk of duplication. Time Savings: Automated underwriting tasks led to a 40% reduction in processing time, allowing more focus on critical activities Strengthened Security: Risk scoring and fraud insights bolstered security measures.Improved Customer Experience: A streamlined end-to-end claims processing workflow enhanced the overall customer journey