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AI-Driven Merchant Analytics Platform for Financial Institutions

emerline.com

Financial services

Information technology

Challenges in Merchant Data Intelligence

European banks face significant challenges in acquiring comprehensive merchant data for effective customer retention strategies and targeted audience acquisition due to insufficient transactional insights and manual categorization processes.

About the Client

Data collection and analysis service provider specializing in merchant intelligence for banking institutions

Core Project Goals

Develop automated machine learning algorithms for merchant categorization
Implement intelligent URL scoring mechanisms for merchant analysis
Create product recognition systems aligned with banking requirements
Establish real-time data categorization pipelines for transactional insights

System Capabilities

Merchant classification engine using transactional data
Human-like URL scoring system for merchant websites
Product/service recognition from merchant data
Custom category mapping based on client requirements
Real-time data transmission to banking systems

Technology Stack

Gensim

Doc2vec

TF-IDF

XGBoost

LightGBM

Optuna

Python

NumPy

System Integrations

Banking transaction data APIs
Payment processing systems
Merchant database repositories
Customer relationship management (CRM) platforms

Operational Requirements

High-throughput data processing capabilities
99.9% system availability
GDPR-compliant data handling
Real-time analysis performance (<500ms response)
Scalable cloud architecture

Business Value

Enables financial institutions to enhance customer retention through actionable merchant insights, improve market positioning via advanced analytics capabilities, and increase operational efficiency by automating previously manual data categorization processes.