Book Image

The Future of Finance with ChatGPT and Power BI

By : James Bryant, Aloke Mukherjee
2.5 (4)
Book Image

The Future of Finance with ChatGPT and Power BI

2.5 (4)
By: James Bryant, Aloke Mukherjee

Overview of this book

In today's rapidly evolving economic landscape, the combination of finance, analytics, and artificial intelligence (AI) heralds a new era of decision-making. Finance and data analytics along with AI can no longer be seen as separate disciplines and professionals have to be comfortable in both in order to be successful. This book combines finance concepts, visualizations through Power BI and the application of AI and ChatGPT to provide a more holistic perspective. After a brief introduction to finance and Power BI, you will begin with Tesla's data-driven financial tactics before moving to John Deere's AgTech strides, all through the lens of AI. Salesforce's adaptation to the AI revolution offers profound insights, while Moderna's navigation through the biotech frontier during the pandemic showcases the agility of AI-focused companies. Learn from Silicon Valley Bank's demise, and prepare for CrowdStrike's defensive maneuvers against cyber threats. With each chapter, you'll gain mastery over new investing ideas, Power BI tools, and integrate ChatGPT into your workflows. This book is an indispensable ally for anyone looking to thrive in the financial sector. By the end of this book, you'll be able to transform your approach to investing and trading by blending AI-driven analysis, data visualization, and real-world applications.
Table of Contents (13 chapters)
Free Chapter
1
Part 1: From Financial Fundamentals to Frontier Tech: Navigating the New Paradigms of Data, EVs, and AgTech
6
Part 2: Pioneers and Protectors: AI Transformations in Software, Finance, Biotech, and Cybersecurity

Compromising real-world LLM-integrated applications with indirect prompt injection

Language models integrated into applications (LLMs), such as ChatGPT, are at the forefront of technological innovation, especially in finance, trading, and investment. However, they pose emerging risks, both ethical and security-related, that warrant immediate attention:

  1. Transformative applications in finance:

    LLMs have transformed various aspects of financial operations, from AI-based financial predictions to rendering personalized Power BI visualizations.

    Case study: Hedge fund profits A hedge fund leveraging ChatGPT for market sentiment analysis successfully navigated a volatile market, realizing a 20% increase in profits.

  2. Ethical maze:

    LLMs come with ethical baggage, from safety concerns to misinformation and regulatory challenges, affecting various platforms including Bing Chat and Microsoft 365 Copilot.

    Case study: Regulatory mishap An investment firm failed to comply with local regulations...