Nex-G Innovations

The objective of this AI in Fintech training program is to provide finance and technology professionals with a comprehensive understanding of how Artificial Intelligence is transforming financial services. The program focuses on key AI technologies such as machine learning, natural language processing, and computer vision, and their applications across payments, lending, wealth management, fraud detection, and regulatory compliance.

Participants will gain practical skills in identifying AI use cases, designing AI-driven financial solutions, and managing risk and governance aspects, preparing them to drive digital innovation in banks, fintech startups, and financial institutions.

Code: NES_SK_22849

Duration: 4 Weeks / 40 Hrs /Customized

Mode: Corporate (Instructor Led Online / Onsite), Individual (Instructor Led Online)

Certification: Certified Fintech AI Professional

+91-8826900551

• Fintech industry overview
• Why AI matters in fintech
• AI vs Traditional software in finance

Module 2: Key AI technologies powering fintech

• Introduction AI
• Machine Learning (ML) & Deep Learning (DL)
• Natural Language Processing (NLP)
• Computer Vision
• Generative AI (Chatbots, Report generation)
• Regulatory considerations (AI Ethics, Bias, Explainability)

Module 3: AI Applications in Payments & Digital Banking

• AI in fraud detection & prevention
• Credit scoring and lending automation
• Personal finance assistants (AI chatbots)
• Customer onboarding with biometric AI
• AI-driven personalized banking recommendations
• Case Study: AI fraud detection in card payments

Module 4: AI in Investment & Wealth Management

• Robo-advisors: How they work
• Algorithmic trading basics
• AI-powered portfolio management
• Sentiment analysis for investment decisions
• Predictive analytics for market forecasting
• Case Study: AI in WealthTech startups

Module 5: AI for Risk Management & Compliance (RegTech)

• Anti-Money Laundering (AML) using AI
• KYC Automation
• AI-driven regulatory reporting
• AI for risk scoring and portfolio risk analysis
• Explainable AI (XAI) in compliance
• Case Study: AI in insurance fraud detection

Module 6: Building AI Strategies for Fintech

• Building AI-enabled financial products
• Choosing the right AI models & data
• AI project roadmap for fintech firms
• Cloud vs On-prem AI solutions (AWS, Azure, GCP)
• Deployment & scaling of AI models in production
• Risk and governance frameworks for AI in fintech

Module 7 – Practical Use Cases

• AI fraud detection using Python ML libraries
• Building a basic chatbot for banking
• Customer segmentation using clustering techniques
• Predictive credit scoring model
• Interactive sessions on data visualization in fintech using Power BI/Tableau

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