Money Movement Transaction Fraud Detection

## Project Overview

Developed and maintained a **real-time Money Movement Transaction Fraud Detection platform** designed to monitor financial transactions, identify potentially suspicious activity, and trigger fraud alerts based on configurable business rules and transaction patterns.

The platform follows a **microservices and event-driven architecture**, using Java, Spring Boot, and Apache Kafka to process transaction events reliably and at scale.

## Key Responsibilities

* Developed scalable backend services using **Java and Spring Boot**.
* Designed and implemented **REST APIs** for transaction processing and service-to-service communication.
* Implemented **Apache Kafka** for real-time transaction event publishing and consumption.
* Developed transaction validation and fraud detection business logic based on configurable rules and transaction attributes.
* Processed high-volume transaction events asynchronously using Kafka consumers.
* Implemented communication between multiple microservices using REST APIs and event-driven messaging.
* Integrated backend services with relational databases using **Spring Data JPA / Hibernate**.
* Implemented exception handling, validation, logging, and error-management mechanisms.
* Designed services to support reliable transaction processing and minimize duplicate event processing.
* Implemented transaction status tracking and processing workflows.
* Worked on fraud-alert generation when transactions matched predefined suspicious patterns or rules.
* Developed unit tests using **JUnit and Mockito**.
* Debugged production issues, analyzed logs, and performed root-cause analysis.
* Improved application performance, reliability, and scalability.
* Used **Git** for source-code management and followed standard Agile development practices.

## Technology Stack

**Backend**

* Java 8/11/17+
* Spring Boot
* Spring MVC
* Spring Data JPA
* Hibernate
* REST APIs

**Messaging & Event Processing**

* Apache Kafka
* Kafka Producers
* Kafka Consumers
* Event-driven architecture

**Architecture**

* Microservices
* RESTful services
* Asynchronous processing
* Event-driven communication

**Database**

* SQL / Relational Database
* JPA / Hibernate

**Testing**

* JUnit
* Mockito
* Unit Testing
* Integration Testing

**Development Tools**

* Git
* Maven
* IntelliJ IDEA / Eclipse
* Postman
* Docker (where applicable)

## High-Level Transaction Flow

**Transaction Initiated → Transaction Service → Kafka Event → Fraud Detection Service → Rule Validation → Risk/Fraud Decision → Alert/Transaction Status**

When a money movement transaction is initiated, the transaction service validates the request and publishes the transaction event to Kafka. The fraud detection service consumes the event and evaluates the transaction against configured detection rules and relevant transaction attributes.

Depending on the evaluation result, the system can identify suspicious transactions, generate an alert, and update the transaction processing status for downstream services.

## My Contribution

I worked primarily on the **backend development and transaction-processing components**, including microservice development, REST API implementation, Kafka producer/consumer development, business-rule implementation, database integration, exception handling, testing, debugging, and production issue resolution.

I also collaborated with other developers and teams to understand business requirements, design technical solutions, implement features, and troubleshoot issues across distributed services.

## Key Features

* Real-time transaction event processing
* Fraud/suspicious transaction detection
* Kafka-based asynchronous communication
* Microservices-based architecture
* Transaction validation
* Configurable business rules
* Fraud alert generation
* Transaction status management
* Exception and failure handling
* Database persistence
* Scalable and reliable event processing
* Comprehensive unit testing
* Production troubleshooting and monitoring

## Project Highlights

The project provided hands-on experience with **real-time financial transaction processing, distributed systems, event-driven architecture, and microservices**. Working with Kafka and Spring Boot helped build reliable asynchronous workflows capable of handling transaction events across multiple backend services.

The architecture was designed with scalability, reliability, maintainability, and fault tolerance in mind, which are important requirements for financial transaction-processing systems.