Description
Our fraud analytics services help identify, prevent, and mitigate fraudulent activities using advanced data analytics techniques. We focus on real-time detection and risk management.
Benefits
Phases
Deliverables:
Client responsibilities:
Location
On site and remotely.
SLA
Included with defined performance and service levels.
Includes project management
Comprehensive planning and coordination throughout the project.
Payment frequency
Project-based, monthly, or time and material.
Contract duration
1 year, 3 years, 5 years (against minimum commitment)
Case Study
Fraud Analytics Service – Advanced Data Analytics Project Overview
Our Fraud Analytics service is designed to help organizations identify, prevent, and mitigate fraudulent activities through real-time detection and robust risk management. Leveraging advanced analytics techniques, we employ state-of-the-art tools to ensure fraud is detected and addressed promptly. The technologies used include DataRobot, Cloudera, HPE Ezmeral, Apache NiFi, Apache Airflow, and other open-source solutions to provide a seamless and scalable platform for fraud detection.
Study Cases
Insurance Sector
We developed a real-time fraud detection system for a leading insurance provider, reducing fraudulent claim payouts by 30% in the first six months. The system integrates data from multiple sources, including customer profiles, transaction data, and historical fraud records, enabling real-time scoring and intervention.
Telecommunications Sector
For a major telecom operator, we deployed a fraud prevention platform that identifies abnormal patterns in call data records, leading to a 25% decrease in SIM card fraud. The solution analyzes vast amounts of network and transaction data to flag suspicious activities in real time, allowing rapid response and mitigation.
Team Experience & Expertise (for a specific case study):
Team Size: Our technical team consists of 5 experts specializing in data engineering, machine learning, and advanced analytics.
Skills: The team possesses expertise in data integration, real-time processing, risk modeling, and fraud detection algorithms. Experience: With experience in delivering fraud analytics solutions across multiple industries, our team has successfully implemented fraud detection systems for leading organizations in the insurance and telecommunications sectors.
Detailed CVs of our technical team are available upon request.
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