Web scraping + metadata DB
Collects web-sourced contract information and stores contract metadata in a dedicated database.
// loading…
Accreditations
Case Study · European Financial Services Firm
An NLP and AI-powered automated contract-review solution for lease review and due diligence. Using web scraping, image processing and NLP, it identifies legal-expert-defined parameters, extracts key details (terms, party details, compensation, liability) and generates a predefined summary file per case — achieving 94% data accuracy, 5% human intervention and 70% cost saving.
Industry
Finance & Legal
Region
EU
Year
2023
Finance & Legal / NLP / AI / Document Processing
The project develops an automated document-processing solution for legal contract review and due diligence. The objective is to reduce the manual effort of reviewing legal documents and give users the key insights and important information within contracts. The solution uses NLP and AI to identify predefined parameters considered important by legal experts, and generates a summary file for each case.
Business requirements & challenges
The client needed to turn slow, manual lease review and due diligence into an automated pipeline that surfaces only the key information.
Key requirements
Solution
An NLP and AI-based solution processes and understands contract information. A model was trained on the key parameters to identify, using a large annotated dataset, and the completed solution generates a summary file per case — improving document-processing efficiency and reducing error time.
Stack
How it works
What's new
Collects web-sourced contract information and stores contract metadata in a dedicated database.
The document-processing engine combines image processing with NLP to read and analyse contracts.
Identifies the key parameters defined by legal experts as the information to extract.
A large annotated dataset trains the NLP/AI model for contract information extraction.
Extracts terms, other-party details, compensation and liability clauses from full contracts.
Generates a predefined summary file for each case, so users don't read the whole document.
Business benefits
A high proportion of the review runs automatically, with high extraction accuracy and substantial cost savings.
94%
data extraction accuracy
5%
human intervention remaining
70%
cost saving
At a glance
| Primary Objective | Automated contract review & due diligence |
|---|---|
| Input Sources | Web source + PDF/Image data |
| Data Collection | Web scraping |
| Storage | Contract Metadata DB |
| Processing Engine | Image Processing + NLP |
| AI | NLP & AI |
| Training | Annotated large dataset |
| Key Extraction | Contract terms, party details, compensation, liability |
| Output | Summary file for each case |
| Business Value | Higher efficiency, reduced errors, lower processing cost |
Related
Oil & Gas
An OCR and NLP document-intelligence solution for the Oil & Gas domain — digitising legal and contract documents, extracting relevant information and entities, discovering relationships between documents, and recognising ID documents. It achieved 90% straight-through processing, a 4% false-positive rate and an 80% headcount reduction.
Major Oil & Gas Operator
90%
straight-through processing
Finance
A rule-based automated loan-appraisal platform for a European financial-services major specializing in corporate, personal and home loans — enabling it to acquire more customers without increasing operational spend or skewing risk tolerances. Applicants enter their details for automatic processing; a rule engine (using rules defined by the loan-appraisal department) checks every application and provides input on the applicant's financial position and loan eligibility. The result: an 80% reduction in cycle time, 99.9% right first time, and an 80% reduction in mundane back-office tasks.
European bank
EU
80%
reduction in cycle time
Finance
A web-based financial credit appraisal solution for a Swiss finance company — letting customers enter their financial details and get immediate lead verification, financial-stability assessment, minimum-criteria checks and business-prospect evaluation. It builds a complete credit profile, lets customers self-verify eligibility and maximum available funding, and automatically calculates and benchmarks financial ratios — reducing appraisal time, team workload and financial risk.
Swiss Finance Company
EU