FinTech CTO: Eradicating Fraud with Next-Gen Detection Strategies

ByVamsi Kiran Chemitiganti

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FinTech CTO: Eradicating Fraud with Next-Gen Detection Strategies

Overview
Curriculum
Instructor

This session delves deep into financial fraud, covering its various forms, detection methods, and latest technologies for building robust prevention systems. Part 1 introduces financial fraud types and the interconnectedness of AML, fraud, and cybercrime prevention efforts, along with legacy fraud detection platform limitations and workflows. Part 2 emphasizes data management’s crucial role in fraud detection, featuring case studies, data analytics techniques, and network analytics. Part 3 explores advanced detection techniques, geolocation data usage, and architectural considerations for modern fraud detection platforms. Attendees will gain essential knowledge and tools for combating financial fraud, crucial for CTOs, security professionals, and financial institution stakeholders.

Requirements

You need no more than a desire to learn and take action by purchasing a course right away! That’s all it takes to excel with us.

What You’ll Learn From This Course

A Technologists Introduction to Banking Financial Services

Welcome and Course Introduction: Begin the session with introductions, a course overview, and a roadmap for the module on Financial Fraud.
Financial Fraud: Overview and Types: Introduce the concept of financial fraud and the different types of fraud schemes that target banks and their customers.
Efforts in AML, Fraud, and Cybercrime Platforms: Highlight the interconnectedness of AML (Anti-Money Laundering), fraud, and cybercrime prevention efforts.
Exploring Legacy Fraud Detection Platforms: Discuss the limitations of traditional fraud detection systems.
Exploring Legacy Fraud Detection Platforms: Discuss the limitations of traditional fraud detection systems.
Exploring Legacy Fraud Detection Platforms : Discuss the limitations of traditional fraud detection systems.
Fraud Detection Case Study : Explore a real-world case study to illustrate how data analysis helped identify and prevent fraud.
Data Analytics in Fraud Detection: Discuss the application of data analytics techniques for fraud detection.
Network Analytics in Fraud Detection: Introduce the concept of network analytics and its role in uncovering fraudulent activity.
Key Strategies for Fraud Prevention : Discuss key strategies that banks can adopt to prevent fraud proactively.
Advanced Detection Techniques
Exploring Detailed Fraud Detection Use Cases : Analyze various use cases where advanced fraud detection techniques can be applied.
Geolocation Data for Risk Assessment: Explore how geolocation data can be leveraged for fraud risk assessment.
Fraud Detection Platform Reference Architecture : Discuss the architectural considerations for building modern fraud detection platforms.
Fraud Detection Platform Reference Architecture: Discuss the architectural considerations for building modern fraud detection platforms.

Curriculum

1 Section
15 Lessons
1 Hour

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Introduction, Course Overview, and Module Content
15

Vamsi Kiran Chemitiganti

Vamsi works as an Industry GM at a hyperscaler and has two plus decades of experience on Financial Services, Telco, Edge Computing, Retail and other industry verticals.