Financial Fraud Detection
with AI and ML
HOW IT WORKS
Risk and fraud management
Risk profile creation for customers and merchants
Predicting money laundering activities
Discovering gambling behaviours
Analysing misbehaved customers and merchants
Fraud detection and prevention based on time, location, amount, frequency, etc.
Desktop application GUI
User-friendly interface (drag and drop)
Ready to integrate with existing banking systems
High-level fraud analysis blocks
Modular components in a data processing workflow
Rich source of ML methods
Anomaly detection using statistics and machine learning techniques
Suspicious activity recognition
Wide range of classification methods (great in imbalanced datasets)
Initial ideas of Bita (Banking Intelligent Transaction Analysis) product have been born five years ago by a group of academic and professional data analysts who were motivated to apply their analytical skills in industrial domains.
They explored a variety of domains, such as employee satisfaction, telecommunications, society welfare, and financial domain in depth.
After implementing a few successful case studies in the financial domain, mainly around fraud detection, team decided to gather their experience in this area and bundle it in a product named Bita to share with the wider industry.
The product is now battle tested in production where it is detecting fraudulent behaviour everyday while easily integrated into other banking systems, analysing huge amounts of financial data in a timely manner, and usable by domain experts who might not have the depth of knowledge of a machine learning expert.
Our vision is to become a world-leading AI/ML company in financial technology industry By 2025. Fraud detection is where we have started this journey.
We have bundled state-of-the-art statistical analysis, AI and machine learning technologies into our products. Our software architecture is completely modular and easily extendable to use emerging methods.
Our architecture is based on:
Spark as core of data processing
PyQt and Plotly for UI and presentation
Cassandra as data repository