Creating an AI Agent for Financial Report Analysis
Resources (including link to code along notebook): https://bit.ly/41cgavS
AI agents are transforming industries by automating complex processes and delivering insights at scale. In financial services, AI agents can streamline decision-making, reduce manual effort, and improve the accuracy of report analysis can informs various downstream tasks like market research, credit scoring, report generation, etc. Designing and building such agents requires a strong understanding of their architecture, the data they rely on, and how to use AI to automate repetitive tasks effectively.
In this hands-on code-along session, Jayeeta Putatunda, a Lead Data Scientist & Director at Fitch Group, guides you through creating an AI agent tailored for financial report analysis. You’ll learn how to design and architect AI agents, explore their applications in finance, and identify the key data needed for these systems. The session will also cover how AI agents can automate repetitive tasks to enhance efficiency. This webinar is ideal for data scientists and machine learning scientists looking to build practical AI solutions for financial applications.
00:00 Introduction & Welcome
00:21 Why AI Agents for Financial Reporting?
01:44 Guest Introduction – Jayta from Fitch Group
03:27 Understanding AI Agents vs. Agentic AI
05:56 Identifying Valuable Use Cases for AI Agents
07:44 Key Components of an AI Agent
10:58 Choosing the Right AI Agent Approach
12:19 AI in Financial Services – Real-World Applications
13:55 Today's Use Case: Financial Report Analysis
16:05 Setting Up the AI Agent Workflow
18:34 Required Tools & API Setup (Grok & Agonal)
22:06 Agent 1: Web Search-Based Research Agent
26:14 Running the Research Agent – Example Queries
31:51 Agent 2: Retrieval-Augmented Generation (RAG)
35:16 Setting Up Vector Database for RAG
38:53 Loading & Processing Financial Documents
42:30 Running Queries Against the Knowledge Base
44:27 Agent 3: AI-Driven Stock Market Analysis
47:40 Running Market Co
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Playlist
Uploads from DataCamp · DataCamp · 0 of 60
← Previous
Next →
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
SQL Server Tutorial: Date manipulation
DataCamp
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
R Tutorial: Adding aesthetics to represent a variable
DataCamp
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
Python Tutorial: Preparation for modeling
DataCamp
Python Tutorial: Machine Learning modeling steps
DataCamp
R Tutorial: The prior model
DataCamp
R Tutorial: Data & the likelihood
DataCamp
R Tutorial: The posterior model
DataCamp
R Tutorial: An Introduction to plotly
DataCamp
R Tutorial: Plotting a single variable
DataCamp
R Tutorial: Bivariate graphics
DataCamp
Python Tutorial: Customer Segmentation in Python
DataCamp
Python Tutorial: Time cohorts
DataCamp
Python Tutorial: Calculate cohort metrics
DataCamp
Python Tutorial: Cohort analysis visualization
DataCamp
R Tutorial: Building Dashboards with flexdashboard
DataCamp
R Tutorial: Anatomy of a flexdashboard
DataCamp
R Tutorial: Layout basics
DataCamp
R Tutorial: Advanced layouts
DataCamp
Python Tutorial: Time Series Analysis in Python
DataCamp
Python Tutorial: Correlation of Two Time Series
DataCamp
Python Tutorial: Simple Linear Regressions
DataCamp
Python Tutorial: Autocorrelation
DataCamp
R Tutorial: The gapminder dataset
DataCamp
R Tutorial: The filter verb
DataCamp
R Tutorial: The arrange verb
DataCamp
R Tutorial: The mutate verb
DataCamp
R Tutorial: What is cluster analysis?
DataCamp
R Tutorial: Distance between two observations
DataCamp
R Tutorial: The importance of scale
DataCamp
R Tutorial: Measuring distance for categorical data
DataCamp
Python Tutorial: Plotting multiple graphs
DataCamp
Python Tutorial: Customizing axes
DataCamp
Python Tutorial: Legends, annotations, & styles
DataCamp
Python Tutorial: Introduction to iterators
DataCamp
Python Tutorial: Playing with iterators
DataCamp
Python Tutorial: Using iterators to load large files into memory
DataCamp
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
SQL Tutorial: Tables: At the core of every database
DataCamp
SQL Tutorial: Update your database as the structure changes
DataCamp
Python Tutorial: Classification-Tree Learning
DataCamp
Python Tutorial: Decision-Tree for Classification
DataCamp
Python Tutorial: Decision-Tree for Regression
DataCamp
Python Tutorial: Census Subject Tables
DataCamp
Python Tutorial: Census Geography
DataCamp
Python Tutorial: Using the Census API
DataCamp
R Tutorial: A/B Testing in R
DataCamp
R Tutorial: Baseline Conversion Rates
DataCamp
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
R Tutorial: Introduction to qualitative data
DataCamp
R Tutorial: Understanding your qualitative variables
DataCamp
R Tutorial: Making Better Plots
DataCamp
SQL Tutorial: OLTP and OLAP
DataCamp
SQL Tutorial: Storing data
DataCamp
SQL Tutorial: Database design
DataCamp
Python Tutorial: Introduction to spaCy
DataCamp
Python Tutorial: Statistical Models
DataCamp
Python Tutorial: Rule-based Matching
DataCamp
More on: Agent Foundations
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
Roblox Data Engineering Interview Questions: Full DE Prep Guide
Dev.to · Gowtham Potureddi
Tesla Data Engineering Interview Questions: Full DE Prep Guide
Dev.to · Gowtham Potureddi
Exodus Point Data Engineering Interview Questions: Full DE Prep Guide
Dev.to · Gowtham Potureddi
What I learned scraping Website Contact: schema, gotchas and the tooling that worked
Dev.to · Can Yılmaz
Chapters (19)
Introduction & Welcome
0:21
Why AI Agents for Financial Reporting?
1:44
Guest Introduction – Jayta from Fitch Group
3:27
Understanding AI Agents vs. Agentic AI
5:56
Identifying Valuable Use Cases for AI Agents
7:44
Key Components of an AI Agent
10:58
Choosing the Right AI Agent Approach
12:19
AI in Financial Services – Real-World Applications
13:55
Today's Use Case: Financial Report Analysis
16:05
Setting Up the AI Agent Workflow
18:34
Required Tools & API Setup (Grok & Agonal)
22:06
Agent 1: Web Search-Based Research Agent
26:14
Running the Research Agent – Example Queries
31:51
Agent 2: Retrieval-Augmented Generation (RAG)
35:16
Setting Up Vector Database for RAG
38:53
Loading & Processing Financial Documents
42:30
Running Queries Against the Knowledge Base
44:27
Agent 3: AI-Driven Stock Market Analysis
47:40
Running Market Co
🎓
Tutor Explanation
DeepCamp AI