1 Introduction to AI in Finance

 

This chapter covers

  • Defining AI in finance and its importance
  • Outlining core AI uses: credit, fraud, more
  • Exploring the 4-layer AI approach
  • Presenting a credit scoring workflow
  • Preparing tools and infra for AI solutions

In June 2024, Jamie Dimon, the CEO of JPMorgan Chase, made a striking admission: as the bank deepens its integration of AI, certain traditional roles may disappear. Yet at the same time, he emphasized that the company would be hiring more talent specialized in AI—reflecting a profound shift in the skills and expertise the financial sector now demands. Across Wall Street, this pattern repeats. Morgan Stanley, for example, has invested heavily in AI-powered research and advisory tools, enabling its analysts and advisors to deliver more personalized and data-driven insights than ever before.

These developments underscore a fundamental truth: AI is no longer a sideline curiosity in the world of finance. It has moved to the forefront, reshaping how credit decisions are made, how fraud is detected, and how investment strategies are formulated. The question is no longer whether to adopt AI, but how effectively to leverage its capabilities in a highly regulated, rapidly evolving environment.

1.1 AI in the Context of Finance

1.2 The New Imperative: Why AI is No Longer Optional

1.3 How AI is Transforming Finance

1.3.1 Managing risk and ensuring compliance

1.3.2 Extracting market intelligence for better investments

1.3.3 Enhancing customer experiences

1.3.4 Improving operational efficiency

1.4 Core Building Blocks of Financial AI Applications

1.4.1 Data Asset Layer

1.4.2 Modeling Layer

1.4.3 Strategy & Monitoring Layer

1.4.4 Application Layer

1.5 How the Layers Work Together: A Credit Scoring Example

1.5.1 The Data Asset Layer

1.5.2 The Modeling Layer

1.5.3 The Strategy & Monitoring Layer

1.5.4 The Application Layer

1.6 Tools, Data, and Infrastructure You’ll Need

1.6.1 Programming Language and Frameworks:

1.6.2 Data and Computing Environment:

1.6.3 Orchestration and Monitoring (Optional):

1.6.4 IDE and Code Access:

1.6.5 Costs, Licensing, and Flexibility:

1.7 Why This Book Matters and How We’ll Work Together

1.7.1 Hands-On Projects:

1.7.2 Multiple Scenarios, Common Principles:

1.7.3 Assumed Background:

1.8 Summary