Neo-Banking Debit and Credit Card Development Project – DS Digital Solutions

?? Project Overview

This project focuses on developing a Neo-Banking platform with debit and credit card issuance and management for SMEs and retail customers. The platform will enable instant debit and credit card issuance, virtual and physical cards, real-time spending control, AI-powered fraud detection, and seamless card integration with digital wallets. Dimitris Souris will serve as the Scrum Master, leading this project under the Scrum framework across 4 teams.

?? Scope

• Platform Focus: Create a fully integrated debit and credit card system within the Neo-Banking platform.
• Target Audience: SMEs and retail customers across Europe.
• Core Features:Instant debit and credit card issuance (both virtual and physical).Real-time balance tracking and transaction notifications for debit cards.Spending controls (limits, freeze/unfreeze cards).AI-powered fraud detection for credit and debit transactions.Integration with digital wallets (Apple Pay, Google Pay).Credit card features: Real-time credit score-based approval and dynamic interest calculation.

?? Objectives

1. Implement real-time debit card management, enabling instant payments, spending controls, and transaction tracking.
2. Develop a credit card system with AI-based credit scoring, offering instant credit approval and dynamic interest rates.
3. Issue both virtual and physical cards, allowing customers to start using their virtual cards instantly.
4. Achieve 99.99% availability using scalable cloud infrastructure to support card transactions in real-time.
5. Launch within 6 months, ensuring full-scale testing, UAT, and compliance with PCI DSS (Payment Card Industry Data Security Standard).

?? Deliverables

1. Debit Card Issuance System: Fully operational by Sprint 5.
2. Credit Card Platform: Developed and integrated by Sprint 7.
3. Virtual Card Issuance: Ready for use by Sprint 6.
4. Fraud Detection System: Fully integrated by Sprint 8.
5. Mobile and Web Card Management: Ready by Sprint 9, supporting real-time card controls, transaction tracking, and digital wallet integration.

?? Documents Required

?? Project Charter: Establishes the project's scope, goals, key deliverables, and stakeholder agreements.

?? Product Backlog: A comprehensive, prioritized list of features and functionalities, including card issuance, fraud detection, and transaction controls.

?? Sprint Backlog: Detailed tasks for each sprint, derived from the product backlog and refined during sprint planning.

?? User Stories: Focus on customer-centric functionalities, such as “As a customer, I want to freeze/unfreeze my card instantly.”

?? Technical Architecture Document: A full document detailing the card issuance system, API integration with third-party payment networks, and security protocols.

?? Data Flow Diagrams: Visualize how data flows from card transactions, through the bank’s backend, to external networks (Visa, Mastercard).

?? Risk Register: Identifies and tracks potential risks, such as security breaches or regulatory non-compliance, with mitigation strategies.

?? Test Plan: Ensures quality control through functional testing, security testing, penetration testing, and integration tests with payment networks.

?? Deployment Plan: Outlines the steps for deploying the card issuance system, including environment setup, PCI DSS compliance, and rollback procedures.

?? Technical Feasibility

Technology Stack:

• Backend: Java (Spring Boot) for managing card issuance, transactions, and user account integration.
• Frontend: React.js for web applications and Swift (iOS), Kotlin (Android) for mobile apps to enable seamless customer experience with card controls, balance tracking, and real-time notifications.
• Payment Network Integration: API integration with Visa, Mastercard, and other payment gateways to handle card transactions.
• Database: PostgreSQL for storing card details (encrypted), transaction histories, and user settings.
• Fraud Detection System: Python (Scikit-learn) to analyze transaction patterns and detect anomalies in real-time.
• Cloud Platform: AWS Lambda for serverless transaction processing, with auto-scaling and high availability.
• Security: PCI DSS-compliant encryption (AES-256), tokenization, and multi-factor authentication (MFA) via AWS Cognito.
• Digital Wallet Integration: APIs for Apple Pay, Google Pay, and Samsung Pay.

Challenges:

• Complying with PCI DSS regulations and ensuring data security for cardholder information.
• Managing the scalability of real-time card issuance and transaction systems.
• Ensuring seamless integration with Visa and Mastercard networks without delays in transaction processing.

?? Economic Feasibility

• Initial Budget: €800,000 allocated for development, testing, infrastructure, and PCI DSS compliance.
• Operational Costs: Cloud infrastructure costs (AWS, payment gateway fees) estimated at €40,000 per month post-deployment.
• ROI: Expected 250% return within two years, driven by transaction fees, interchange fees, and credit card interest revenue.
• Cost-Benefit Analysis: Automated card issuance will reduce operational costs by 20%, while AI-driven fraud detection minimizes financial losses due to fraudulent transactions.

?? Quality Assurance (QA)

• Functional Testing: Unit and integration tests will be performed for every feature, including card issuance, transaction processing, and spending controls.
• Automated Testing: Implemented through Jenkins pipelines, using JUnit for backend, Selenium for front-end, and Postman for API tests.
• Penetration Testing: Conducted to ensure the platform is secure and resistant to attacks, particularly focusing on cardholder data and API security.
• Compliance Testing: Regular audits and scans to ensure full compliance with PCI DSS, ensuring card data is protected at all times.
• Regression Testing: Ensures new features or updates do not disrupt existing functionalities through automated regression tests.

?? Teams and Roles

1. Debit and Credit Card Team: Responsible for developing the card issuance system, real-time transaction processing, and integration with payment networks.
2. Fraud Detection Team: Focuses on building and integrating AI models to detect fraudulent activities and flag unusual spending patterns.
3. Mobile and Web Team: Develops and tests the mobile and web-based interfaces, providing users with real-time card controls and transaction notifications.
4. QA and Compliance Team: Responsible for maintaining high standards of testing and compliance with PCI DSS regulations.

Scrum Master: Dimitris Souris Product Owner: Prioritizes features in the product backlog and works closely with stakeholders to ensure the project delivers maximum value. Development Teams: Work in self-organizing Scrum teams to build and deliver functional increments.

?? Architecture

?? System Architecture The platform follows a microservices architecture, which allows for independent scaling of key components such as card issuance, transaction processing, and fraud detection.

• Card Issuance Service: Handles virtual and physical card generation, integrates with Visa and Mastercard APIs for card network registration.
• Tech Stack: Spring Boot for backend services, PostgreSQL for storing card details, and secure integration with Visa/Mastercard for card issuance.
• Transaction Processing Service: Manages real-time authorization of debit and credit transactions, applying spending limits and controls
• Tech Stack: Spring Boot, integrated with Kafka for real-time transaction monitoring and alerts.
• Fraud Detection Service: Analyzes each transaction in real-time, using machine learning models to detect unusual patterns and flag potential fraud
• Tech Stack: Python (Scikit-learn, TensorFlow) for fraud detection models, Apache Kafka for real-time data streaming and anomaly detection.
• API Gateway: Provides a secure communication layer for mobile/web apps to interact with backend services
• Tech Stack: Spring Cloud Gateway for API management.
• Security Layer: Implements AES-256 encryption, tokenization, and OAuth 2.0 to ensure all cardholder data and transactions are secure
• Tech Stack: AWS Cognito for user authentication, OAuth 2.0 for token-based access control, and AES-256 encryption for securing sensitive data.

?? Data Flow

?? Data Flow Diagram

• User Requests Card Issuance: Users can request virtual or physical debit/credit cards via the mobile/web interface
• Tech Stack: React.js (web), Swift (iOS), and Kotlin (Android) handle the front-end request. The request is processed by Spring Boot services on the backend.
• Card Generation: The backend generates the card details and registers it with Visa/Mastercard .
• Tech tack: PostgreSQL for card storage, Visa/Mastercard APIs for registration.
• Transaction Authorization: When a user makes a transaction, the system checks the balance (debit) or available credit (credit) and applies any spending controls.
• Tech Stack: Spring Boot for backend processing, PostgreSQL for transaction validation, Kafka for real-time monitoring.
• Fraud Detection: The transaction data is analyzed for anomalies using AI-driven models in real-time.
• Tech Stack: Python (fraud detection models), Kafka for event streaming and real-time alerts.
• Data Storage: All transaction data, spending patterns, and card details are stored in PostgreSQL, encrypted at rest and in transit.
• Tech Stack: PostgreSQL, with data encryption handled by AES-256.
• Notifications Sent: The user is notified in real-time via push notifications about the transaction status and any potential issues (fraud alerts, declines).
• Tech Stack: Firebase for push notifications, Spring Boot services trigger alerts based on transaction results.

?? Phases of Development

?? Phase 1: Discovery & Planning (Sprints 1-2)

• Sprint Goal: Finalize project scope, design high-level architecture, and define the product backlog.
• Key Activities: Requirements gathering, defining user stories, setting up CI/CD pipelines.
• Tech Stack: Use JIRA for sprint planning, Jenkins for CI/CD setup.

?? Phase 2: Debit Card Issuance and Processing (Sprints 3-5)

• Sprint Goal: Develop the system for virtual and physical debit card issuance and integrate with payment networks.
• Key Activities: Backend development for card issuance, API integration with Visa/Mastercard, and security implementation.
• Tech Stack: Spring Boot for backend, PostgreSQL for card data, Visa/Mastercard APIs.

?? Phase 3: Credit Card Issuance and AI Integration (Sprints 6-7)

• Sprint Goal: Build credit card functionalities, including real-time credit scoring and dynamic interest rate calculation.
• Key Activities: Develop backend logic for credit card transactions, integrate AI models for credit scoring, and build credit management features.
• Tech Stack: Python (TensorFlow, Scikit-learn) for AI, Spring Boot for backend services.

?? Phase 4: Fraud Detection and Security (Sprints 8-9)

• Sprint Goal: Implement AI-powered fraud detection, ensuring that real-time transaction monitoring is in place.
• Key Activities: Build fraud detection algorithms, set up real-time alerts, and conduct penetration testing to ensure system security.
• Tech Stack: Python (fraud detection), Kafka for real-time data processing, PostgreSQL for transaction storage.

?? Phase 5: Final Testing and Deployment (Sprint 10-12)

• Sprint Goal: Execute UAT, finalize PCI DSS compliance, and deploy the card system into production.
• Key Activities: Conduct regression and performance testing, ensure full compliance, and deploy using blue-green deployment strategy for minimal downtime.
• Tech Stack: Jenkins for deployment automation, AWS CloudWatch for post-deployment monitoring.

?? Sprint Planning (Sprints 1-12)

• Sprint 1-2: Backlog creation, architecture design, and initial infrastructure setup.
• Tech Stack: JIRA for task management, Jenkins for infrastructure setup.
• Sprint 3-5: Development of debit card functionalities, card issuance, and integration with Visa/Mastercard.
• Tech Stack: Spring Boot, PostgreSQL, Visa/Mastercard APIs.
• Sprint 6-7: Credit card features and AI-based credit scoring implementation.
• Tech Stack: Python (AI models), Spring Boot for backend logic.
• Sprint 8-9: Fraud detection, spending controls, and testing phases.
• Tech Stack: Python, Kafka, PostgreSQL.
• Sprint 10-12: UAT, PCI DSS compliance checks, and final deployment to production.
• Tech Stack: Jenkins for CI/CD, AWS CloudWatch for monitoring.

?? UAT with Stress and Penetration Testing

• UAT (User Acceptance Testing): Engage a select group of customers and SMEs to validate the real-world functionality of debit and credit cards.
• Stress Testing: Simulate high transactional volumes to ensure the system can handle peak activity without performance degradation.
• Penetration Testing: Ensure the platform complies with the highest standards of security, with a focus on cardholder data protection and transaction safety.
• Tech Stack: Use OWASP ZAP and Burp Suite for penetration testing.

?? Regression Testing

• Tools Used: Selenium, JUnit, and TestNG integrated into the Jenkins CI pipeline for automated regression tests.
• Objective: Ensure that new updates do not negatively impact existing functionalities, preserving system stability after each release.

?? QA and Deployment

• Quality Assurance: Ongoing QA throughout the project, with a focus on functionality, security, and regulatory compliance.
• Deployment Strategy: Use a blue-green deployment approach to reduce downtime and ensure seamless rollout.
• Post-Deployment Monitoring: Use Datadog and AWS CloudWatch to monitor system performance, transaction processing, and security events.

This detailed Neo-Banking Debit and Credit Card Development Project for DS Digital Solutions delivers a comprehensive platform for real-time card management, fraud detection, and seamless integration with payment networks. The project plan ensures a scalable, secure, and high-performing solution for both SMEs and retail customers, with full compliance with regulatory standards like PCI DSS.