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AI+ Finance Practitioner™

Course code: NPAP220

Formerly known as AI+ Finance™

Maximize Returns with AI-Enhanced Financial Strategies

  • Finance Transformation: Explore AI applications in credit risk, fraud detection, and financial forecasting.
  • Smart Modelling: Apply predictive analytics and blockchain within financial strategies.
  • Practical AI Tools: Optimize operations and decision-making through hands-on training.
  • Strategic Readiness: Build financial resilience across complex economic ecosystems.
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI-Driven Financial Analysis

Learners will master the use of AI tools to enhance financial analysis, including credit assessments and fraud detection.

Strategic Implementation of AI in Finance

You will gain skills in strategically implementing AI technologies across various financial services, improving efficiency and accuracy.

Forecasting and Risk Management

Learners who will go through this course will have the ability to use AI for predictive analytics, such as stock market forecasting and risk assessment.

Understanding of Blockchain in Finance

Learners will develop an understanding of how blockchain technology can be integrated with AI to revolutionize financial systems and processes.

Course structure

Course Overview

Module 1: Foundations of AI in Modern Finance

  • 1.1 Understanding AI in Financial Services
  • 1.2 The AI Transformation of Finance
  • 1.3 Financial Data and AI Readiness
  • 1.4 AI Literacy for Finance Professionals
  • 1.5 Real World Case Studies

Module 2: AI-Assisted Financial Analysis and Decision Intelligence

  • 2.1 Financial Analysis with AI
  • 2.2 Generative AI for Finance Workflows
  • 2.3 Predictive and Decision Intelligence
  • 2.4 Retrieval-Augmented Generation (RAG) in Finance
  • 2.5 Real World Case Studies

Module 3: AI for Banking, Lending, Payments, and Customer Finance

  • 3.1 AI in Digital Banking and Financial Services
  • 3.2 Intelligent Lending and Credit Decisioning
  • 3.3 Payments, Embedded Finance, and Fintech Innovation
  • 3.4 Customer Experience and Financial Personalization

Module 4: AI for Risk, Fraud, Compliance, and Financial Crime

  • 4.1 Modern Financial Risk Management
  • 4.2 Fraud Detection and Financial Crime Analytics
  • 4.3 Regulatory AI and Compliance Automation
  • 4.4 Cybersecurity for AI in Finance

Module 5: Investment Intelligence, Markets, and AI Agents

  • 5.1 AI in Investment and Asset Management
  • 5.2 Alternative Data and Financial NLP
  • 5.3 AI Agents and Autonomous Finance Workflows
  • 5.4 Algorithmic and AI-Enhanced Trading

Module 6: Digital Assets, Tokenization, and Emerging Financial Infrastructure

  • 6.1 Blockchain and Digital Asset Foundations
  • 6.2 Tokenization and On-Chain Finance
  • 6.3 DeFi, Embedded Finance, and Next-Generation Financial Infrastructure
  • 6.4 Emerging Technologies Shaping Finance

Module 7: AI Governance, Model Risk, and Finance Transformation

  • 7.1 Responsible AI in Finance
  • 7.2 Model Risk Management
  • 7.3 AI Strategy and Finance Operating Models
  • 7.4 Building an AI-Enabled Finance Function
  • 7.5 Real-World Case Studies

Module 8: Capstone – AI Finance Transformation and Governance Project

  • 8.1 Select a Financial Use Case
  • 8.2 Design an AI Solution
  • 8.3 Build an AI Finance Governance Package
  • 8.4 Final Capstone Deliverable
  • 8.5 Review and Reflection
  • 8.6 Capstone 1: AI Finance Data Analyst
  • 8.7 Capstone 2: AI Finance Risk & Control Assistant

Optional Module: AI Agents for Finance Practitioner

  • 1.1 What Are AI Agents for Finance?
  • 1.2 Types of AI Agents in Finance
  • 1.3 Significance of AI Agents in Finance

Prerequisites

  • A basic understanding of finance fundamentals; no technical skills required.
  • An interest in AI’s influence on financial operations and openness to change.
  • Willingness to engage with ethical frameworks and apply AI tools effectively.

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