DATA ANALYTICS IN ACCOUNTING

Available Dates & Locations

This course is offered exclusively as In-House or Virtual, with no public sessions currently available – please contact us for inquiries.

COURSE OVERVIEW

This course empowers accounting professionals with essential data analytics skills, including the latest advancements in artificial intelligence (AI) for financial analysis. Participants will gain hands-on experience with practical applications of data analytics and AI, focusing on key accounting processes such as accounts receivable, accounts payable, inventory, fixed assets, reconciliations, loans, and financial reporting. By integrating MS Excel analytics and AI-powered tools, attendees will learn to identify trends, uncover opportunities, automate analysis, and improve operational efficiency.

Course Pre-requisites: Familiarity with MS Excel

Course Level: Intermediate

COURSE OBJECTIVES

Understand the role of data analytics and AI in accounting decision-making.
Ensure financial data accuracy through effective preparation and validation.
Use Excel, Power Query, Power Pivot, and AI-powered tools for financial data analysis.
Optimize accounting processes like AR, AP, reconciliations, and fixed assets.
Detect trends and anomalies to improve efficiency.
Streamline workflows using practical analytics and AI techniques.
Design visualizations and reports to communicate findings.

TARGET COMPETENCIES

Data-Driven Accounting
Data Integrity
Analytical Tools & AI Proficiency
Accounting Workflow Optimization
Visualization and Reporting

This course is designed for corporate accounting professionals responsible for accounts receivable, accounts payable, reconciliations, fixed asset management, and financial reporting, seeking to enhance their data analytics and AI capabilities.

The course includes instructor-led training, hands-on workshops, and practical exercises, providing participants with an interactive learning experience to develop essential skills and apply knowledge effectively in real-world accounting, data analytics, and AI scenarios.

FOUNDATIONS OF DATA ANALYTICS IN ACCOUNTING

Introduction to Data Analytics in Accounting
- What is Data Analytics?
- Role and Importance of Analytics in Accounting
- Key challenges in data-driven accounting
Understanding Accounting Data Sources
- Overview of Accounting Data Sources
- Cleaning and Structuring Data
- Data Integrity and Validation
Data Classification and Categorization
- Data Cleaning and Preparation in Excel
- Removing Duplicates
- Using Conditional Formatting to Spot Errors and Inconsistencies
Restructuring Data for Analysis

TOOLS FOR ANALYTICS

Analyzing Patterns and Trends in AR and AP
- Identifying Anomalies in Financial Transactions
- Using Excel Functions for Financial Analysis
- Introduction to Power Pivot
Overview of Power Pivot for Data Modeling
- Creating Relationships between Data Tables
- Analyzing Accounting Data with Pivot Tables
- Building Pivot Tables for AR Aging Schedules and AP Reports
Using Calculated Fields and Measures for Financial Insights

WORKFLOW OPTIMIZATION

Analyzing Accounting Practices
AR Insights: Aging Schedules, Overdue Invoices
AP Insights: Vendor Analysis and Payment Optimization
Fixed Asset Analysis: Depreciation Schedules
Optimizing Accounting Workflows with Excel
Automating Repetitive Tasks Using Macros and Advanced Formulas

Anomalies Detection

Risk Identification in Accounting
Common Risks in AR, AP, and Fixed Assets
Early Warning Indicators for Risks
Anomalies Identification
Spotting Duplicate Transactions and Irregular Patterns
COUNTIFS, IFERROR for Anomaly Detection
Monitoring Inventory Risks Using Pivot Tables

AI in Financial Analysis, Visualization, and Reporting

Leveraging Artificial Intelligence in Financial Analysis
Introduction to AI and Machine Learning in Accounting
Real-world Applications: AI for Fraud Detection, Predictive Analytics, and Automated Reporting
Hands-on: Using AI-powered features in Excel
Creating Impactful Visualizations
Creating a Comprehensive Dashboard for Financial Reporting
Adding Filters, Slicers, and Summary Views for Stakeholders