Prompt Engineering for Finance

• Basic knowledge of finance and financial analysis
• Experience with data analytics and financial modeling
• Familiarity with AI and machine learning concepts (recommended)

Audience

• Financial analysts
• Risk managers
• Fintech developers

Prompt engineering is transforming financial decision-making by leveraging AI for risk assessment, automated financial reporting, and market analysis.

This instructor-led, live training (online or onsite) is aimed at intermediate-level finance professionals and fintech developers who wish to use AI-powered prompt engineering techniques to enhance financial analysis, risk management, and decision-making.

By the end of this training, participants will be able to:

• Understand the fundamentals of prompt engineering in financial applications.
• Leverage AI models for financial forecasting and market sentiment analysis.
• Automate financial reporting and data extraction using AI prompts.
• Develop AI-driven risk assessment models through optimized prompts.
• Ensure compliance and ethical considerations when using AI in finance.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Prompt Engineering in Finance

• Understanding prompt engineering and AI models
• Applications of AI-driven prompts in financial analysis
• Overview of AI tools and APIs for finance

Using AI for Financial Forecasting

• Generating financial projections using AI prompts
• Analyzing historical data for trend predictions
• Enhancing accuracy through prompt optimization

Market Sentiment Analysis with AI

• Extracting insights from financial news and reports
• Using NLP-powered prompts for sentiment classification
• Integrating AI-based sentiment analysis with financial models

Automating Financial Reporting

• Generating financial summaries using AI
• Automating data extraction from reports
• Ensuring consistency and compliance in AI-generated reports

Risk Assessment and Fraud Detection

• Developing AI-driven risk assessment models
• Optimizing AI prompts for fraud detection
• Case studies on AI-powered financial risk management

Enhancing Decision-Making with AI

• Leveraging AI for investment strategy optimization
• AI-driven scenario analysis and stress testing
• Best practices for AI-assisted financial decision-making

Ethical and Compliance Considerations in AI-Driven Finance

• Ensuring ethical use of AI in financial services
• AI bias and its impact on financial decision-making
• Regulatory considerations and AI compliance frameworks

Hands-On Labs and Real-World Applications

• Building financial forecast models using AI prompts
• Developing an AI-driven risk assessment tool
• Automating market sentiment analysis

Summary and Next Steps