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Duration 14 hours
Course Outline
Overview of Generative AI in Finance
- Exploring the fundamentals of generative AI and its significance to the financial industry.
- Reviewing real-world examples of AI-driven strategies in risk management, fraud prevention, and client interaction.
- Examining the primary advantages and potential hurdles of adopting generative AI in finance.
Preparing the Technical Environment
- An introduction to the OpenAI API and Google Cloud Platform.
- Creating accounts and gaining access to necessary AI utilities.
- Performing basic configurations and initial system setup.
Building AI Models for Risk Assessment
- Defining the function of generative AI in evaluating risk.
- Constructing AI models focused on credit scoring and loan decisioning.
- Evaluating risk variables and forecasting financial results.
Advanced Fraud Detection using Generative AI
- Understanding the complexities of detecting and preventing fraud.
- Applying generative AI for identifying anomalies and recognizing patterns.
- Developing AI frameworks to pinpoint fraudulent transactions.
Improving Customer Experience with AI
- Achieving personalization and customization in financial offerings.
- Designing AI-driven chatbots for effective customer support and engagement.
- Elevating user satisfaction through AI-generated recommendations and insights.
Embedding Generative AI into Financial Infrastructure
- Managing API connections and ensuring data interoperability.
- Rolling out AI models within production environments.
- Scaling AI capabilities to process high volumes of financial data.
Assessing AI Performance and Clarity
- Utilizing key metrics and benchmarks to gauge AI effectiveness.
- Interpreting the insights and suggestions generated by AI models.
- Maintaining transparency and responsibility in AI-driven decisions.
Ethical Frameworks in Financial AI
- Guaranteeing equity and preventing bias in AI algorithms.
- Tackling privacy issues and safeguarding data.
- Aligning with regulatory mandates and sector-specific standards.
Recap and Future Directions
Requirements
- Foundational knowledge of financial principles.
- A background in AI and machine learning basics is advantageous, though not mandatory.
Target Audience
- Finance industry professionals.
- Fintech developers.
- AI specialists.
Testimonials (3)
Comprehensiveness about the backround; how to do a prompt.
Olaf Kannt - Helios Klinikum Krefeld
Course - Generative AI and Prompt Engineering in Healthcare
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
