Finance Analytics

The objective of this program is to provide participants with the analytical and financial modeling skills required to evaluate business performance, assess risks, and support strategic financial decision-making. The course focuses on understanding financial statements, ratio analysis, budgeting, forecasting, and investment evaluation. Participants will learn how to use data-driven techniques to interpret financial health, optimize cost structures, and improve profitability.

Category: Analytics

Description

1. Learning Outcomes

Understand key financial concepts including P&L, balance sheet, cash flow, and financial ratios.
Analyze business performance using metrics such as ROI, EBITDA, liquidity ratios, and profitability ratios.
Build financial forecasting and budgeting models using historical data.
Evaluate investment decisions through techniques like NPV, IRR, and break-even analysis.
Use tools like Excel, Power BI, or financial modeling software for financial analysis.
Develop dashboards and reports that communicate financial insights clearly.

2. Program Highlights & Key Features

Case studies based on real-world corporate financial scenarios.
Hands-on training in financial modeling and ratio analysis.
Practical sessions on budgeting, forecasting, and scenario planning.
Expert guidance on interpreting financial statements and investment performance.
Coverage of modern financial analytics trends, including automation and predictive finance.

Module 1: Introduction to Financial Data Analytics
Module 2: Financial Data Understanding and Preparation
Module 3: Exploratory Data Analysis (EDA) in Finance
Module 4: Financial Analysis Using Fundamentals
Module 5: Financial Statistics for Data Analysis
Module 6: Financial Securities Data Analysis
Module 7: Time Series Analysis in Finance
Module 8: Financial Data Analysis Use Cases

Introduction to Financial Data Analytics

What is Financial Analytics
Role of Data Analysis in Finance
Types of Financial Data
Importance of Financial Data Analysis
Applications in Finance
Tools Used for Financial Data Analysis
Conclusion and QnA

Financial Data Understanding and Preparation

Understanding Financial Datasets
Financial Data Dictionary
Data Types and Date-Based Data
Data Cleaning and Missing Values
Data Quality Issues
Conclusion and QnA

Exploratory Data Analysis (EDA) in Finance

Introduction to EDA
Revenue, Expense & Profit Trend Analysis
Asset Value Analysis
Descriptive Statistics
Identifying Patterns and Outliers
Visualization of Financial Data
Conclusion and QnA

Financial Analysis Using Fundamentals

Understanding Fundamental Financial Metrics
Relationship Between Revenue, Profit, and Stock Price
Correlation Analysis Using Financial Data
Data-Driven Investment Insights
Limitations of Fundamental Analysis
Conclusion and QnA

Financial Statistics for Data Analysis

Role of Statistics in Financial Analysis
Risk and Return Concepts
CAPM – Conceptual Understanding
Expected vs Actual Return Analysis
Visualizing Risk and Return
Conclusion and QnA

Financial Securities Data Analysis

Overview of Securities Data
Bond Yield and Maturity Analysis
Government vs Corporate Bonds
Stock and Bond Comparison
Data-Based Investment Decisions
Conclusion and QnA

Time Series Analysis in Finance

Time-Based Financial Data
Stock Price and Volume Trends
Seasonality and Pattern Identification
Basic Forecasting Using Historical Data
Business Use Cases
Conclusion and QnA

Financial Data Analysis Use Cases

Financial Decisions Using Data Analysis
Investment Analysis – Before vs After Analytics
Risk Identification Using Data
Communicating Financial Insights
Future Scope of Financial Data Analytics
Conclusion and QnA

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