Newcleus DocAI
Case Study
AI-Powered Document Intelligence for Newcleus
We developed an innovative AI solution for Newcleus, a US-based financing strategy provider in the banking industry, specializing in compensation, retirement, and financial advisory services. This project focused on automating the extraction and analysis of insurance policy data from PDF documents to streamline financial comparisons.
The Vision
To empower Newcleus with cutting-edge AI technology that automates complex data extraction and analysis, driving efficiency, accuracy, and informed decision-making in financial strategy and advisory services.
Scenario
Automating Insurance Policy Analysis
Newcleus needed a solution to automate the time-consuming and error-prone process of manually extracting data from insurance policy PDFs. The goal was to consolidate this data into a structured format, enabling efficient financial comparisons and advising clients on optimal insurance strategies.
What we did
We designed and implemented an AI-powered tool to automate the extraction of key data fields from insurance policy PDFs and streamline the analysis process
Developed an AI-powered tool to automate the extraction of required data fields from insurance policy PDFs into JSON format. Created prompts to accurately extract information such as Insured Name, Date of Birth, and Policy Number. Implemented data validation by comparing AI-extracted data with manually stored data in Excel.
Utilized Databricks to process and analyze the validated data, performing financial calculations (surrender values, premiums, payouts) and assessing tax implications. Automated the generation of presentations (PPTs) to visualize the analytics, supporting brokers in making informed recommendations about insurance policy decisions.
Key features of the experience
The Impact
The AI-powered solution delivered significant benefits to Newcleus
Enhanced Efficiency
Reduced time spent on data extraction, allowing staff to focus on strategic activities.
Improved Accuracy
Minimized human error in data extraction, leading to more reliable data.
Cost Risk Accuracy
Decreased labor costs and mitigated financial risks associated with errors.