Offsiteteam
Monitoring financial transactions to detect fraudulent activity
Empower your financial security with our cutting-edge fraud detection system.
Java Python Docker JRules
Solution
A number of AWS services, including rule engine, anomaly detection and UX interface
Engagement model
Technology partner
Methodology
Waterfall
Industry
Mobile Payment
Team
AI Architects 1
Back engineers 2
Front engineers 1
DevOps 1
Company name
Hidden
Location
Finland
Business activity
Mobile Payment

Monitoring financial transactions to detect fraudulent activity

The challenge lies in identifying fraudulent activities in incoming payments, ensuring regulatory compliance, and handling high transaction volumes. Our goal is to create an efficient and scalable system that combines a powerful rule engine with cutting-edge AI anomaly detection, empowering security admins to swiftly assess and prevent fraudulent transactions.

Case highlights

Rule Engine
Recurrent Neural Net
AWS service architecture
Fraudulent Transaction detection

Challenge

Our partnership with a middle-sized company embarks on a mission-critical software development project to establish an advanced financial transaction monitoring system. The primary goal is to detect fraudulent activity in incoming payments while adhering to strict regulatory compliance. The company seeks a solution that strikes the right balance between ease of implementation and the potential for future enhancements. Additionally, the system must exhibit high performance, effortlessly handling a substantial influx of incoming transaction requests.

Solution

Offsiteteam presents a strategic two-stage roadmap designed to address the company's needs effectively. In the initial stage, we lay the foundation with a robust rule engine, made to accurate identification of potential fraudulent transactions. This pivotal step ensures a quick setup and enabling it to deliver immediate value. Building upon the success of the rule engine, we progress to the second stage, infusing the solution with the latest advancements in AI anomaly detection. The result is a solution capable of efficiently adapting to emerging fraudulent tactics, safeguarding financial interests with unparalleled vigilance. The intuitive UX interface empowers security admins with real-time visibility, allowing them to swiftly review, approve, or reject transactions based on risk assessments. Additionally, the interface offers customizable detection settings, empowering admins to fine-tune sensitivity levels in response to evolving threats. To ensure the solution's scalability and high performance, we deployed it as a set of services on the AWS cloud. This architecture guarantees exceptional reliability, resilience, and the ability to handle surges in transaction volumes with ease.
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