CASE STUDY
Surveillance And Monitoring Using Deep Learning Surveillance & Monitoring | Machine Learning on ELK
About Client
Our customer is a global investment manager with 16Bn AUM, based in NYC. The firm’s investment flexibility accommodates continual repositioning of the portfolio to capitalize on the most compelling risk-adjusted investment opportunities with specific return and liquidity objectives. The firm fosters a culture based on openness, global teamwork, and inclusion. It strives to unravel the complexities of investment strategy, management, and corporate culture, with its commitment to excellence.
Business Challenge
- Proactively detect any unauthorized sharing of information with fraudulent intent
- Monitor documents without manual intervention
- Maintain statutory compliance
Key Highlights
- Rule-based approach leveraging Kibana’s filter mechanism
- Machine learning approach leveraging anomaly detection
Results
28%
Compliance team’s
costs savings
Increase in processing
potentially fraudulent
activities
Testimonial
Testimonial
The Magic FinServ team has a thorough knowledge of our business ecosystem, which helped define a solution that fits right within our existing processes and multitude of workflows. They accomplished it without a significant learning/implementation curve for our team, which speaks volumes about their commitment to customer-centricity. We are looking forward to working with them for applying machine learning across several other areas of operations.
Senior Partner, Global Alternative Investment firm with $16Bn
Case study
Surveillance And Monitoring Using Deep Learning
Just fill out this form to download the case study.
Fill the details to download