AI-Powered Loan Assessment: From Paper to Precision
Our Solution:
We implemented an AI-driven Financial Document Insight & Decision Platform that automated both KPI extraction and the structured assessment of a company’s financial health to support leasing decisions.
The platform featured:
- AI-Powered OCR for accurate extraction from scanned P&L statements, balance sheets, and other financial documents.
- Machine Learning KPI Detection to identify and extract revenue, expenses, profit margins, debt ratios, and other key financial metrics.
- Automated Validation Engine to ensure extracted values matched cross-referenced datasets for accuracy.
- Financial Health Scoring Model that used extracted KPIs to generate a decision recommendation (lease approval, review, or rejection).
- Centralized Financial Data Repository enabling rapid retrieval, comparison, and audit tracking.
- Role-Based Dashboards to deliver instant insights and decision recommendations to analysts, managers, and executives.
This solution transformed the process from manual data collection and subjective evaluation into a fast, accurate, and consistent AI-assisted leasing decision framework.
Business Impact:
- Reduced KPI extraction time from hours to under 30 seconds per document.
- Improved financial data accuracy to over 98%.
- Freed up 40% of analyst time for strategic work instead of manual extraction.
- Accelerated leasing decision turnaround from days to minutes.
- Increased consistency and transparency in lease approval processes.
Our Role & Execution:
- Conducted detailed workflow mapping with finance team leads to identify KPI extraction and decision-making bottlenecks.
- Created BRD and SoW outlining document types, KPIs, validation rules, and decision logic.
- Designed high-level architecture for AI/NLP processing, financial health scoring, and secure data storage.
- Managed AI model training using historical financial documents and past leasing decision records to optimize accuracy.
- Oversaw build, testing, and deployment phases, followed by user training sessions.
Technology Stack:
AI, OCR, NLP Models, Machine Learning Classifiers, Intelligent Document Processing Framework, Financial Health Scoring Model, Secure Data Repository
Keywords:
AI Assistant, Intelligent Document Processing, KPI Extraction, Financial Decision Automation, BFSI AI Solutions, Automated P&L Analysis, AI for Leasing
Client
Leading Financial Services & Leasing Enterprise
Industry
BFSI / Asset Leasing
Solution Area
AI, Intelligent Document Processing, Financial Decision Automation
Challenge
The client’s financial team regularly analyzed a large volume of critical financial documents, including Profit & Loss statements, Balance Sheets, CIBIL report and other financial reports—many of which were available only as scanned documents. Manually extracting Key Performance Indicators (KPIs) from these documents was a highly time-consuming process, often taking hours per file. This delayed decision-making on whether to approve or reject lease agreements and increased the risk of errors in reporting and compliance tracking.
Our Solution:
We implemented an AI-driven Financial Document Insight & Decision Platform that automated both KPI extraction and the structured assessment of a company’s financial health to support leasing decisions.
The platform featured:
- AI-Powered OCR for accurate extraction from scanned P&L statements, balance sheets, and other financial documents.
- Machine Learning KPI Detection to identify and extract revenue, expenses, profit margins, debt ratios, and other key financial metrics.
- Automated Validation Engine to ensure extracted values matched cross-referenced datasets for accuracy.
- Financial Health Scoring Model that used extracted KPIs to generate a decision recommendation (lease approval, review, or rejection).
- Centralized Financial Data Repository enabling rapid retrieval, comparison, and audit tracking.
- Role-Based Dashboards to deliver instant insights and decision recommendations to analysts, managers, and executives.
This solution transformed the process from manual data collection and subjective evaluation into a fast, accurate, and consistent AI-assisted leasing decision framework.
Business Impact:
- Reduced KPI extraction time from hours to under 30 seconds per document.
- Improved financial data accuracy to over 98%.
- Freed up 40% of analyst time for strategic work instead of manual extraction.
- Accelerated leasing decision turnaround from days to minutes.
- Increased consistency and transparency in lease approval processes.
Our Role & Execution:
- Conducted detailed workflow mapping with finance team leads to identify KPI extraction and decision-making bottlenecks.
- Created BRD and SoW outlining document types, KPIs, validation rules, and decision logic.
- Designed high-level architecture for AI/NLP processing, financial health scoring, and secure data storage.
- Managed AI model training using historical financial documents and past leasing decision records to optimize accuracy.
- Oversaw build, testing, and deployment phases, followed by user training sessions.
Technology Stack:
AI, OCR, NLP Models, Machine Learning Classifiers, Intelligent Document Processing Framework, Financial Health Scoring Model, Secure Data Repository
Keywords:
AI Assistant, Intelligent Document Processing, KPI Extraction, Financial Decision Automation, BFSI AI Solutions, Automated P&L Analysis, AI for Leasing
Recent Case Studies
