Introduction

Banking Analytics with Power BI Training Course is designed to equip banking professionals, analysts, finance experts, and data-driven decision makers with advanced skills in Business Intelligence (BI), Data Analytics, Financial Reporting, Risk Analytics, Customer Insights, and Dashboard Automation. The course focuses on transforming complex banking data into meaningful insights using Microsoft Power BI, Data Visualization, Predictive Analytics, KPI Monitoring, and Interactive Executive Dashboards. Participants will learn how to leverage analytics for credit risk management, fraud detection, customer segmentation, loan portfolio analysis, and regulatory reporting in modern digital banking environments.

With the rapid adoption of Artificial Intelligence (AI), Machine Learning (ML), FinTech innovation, cloud analytics, and data-driven banking strategies, financial institutions require professionals who can convert data into strategic business decisions. This training provides hands-on experience through real-world banking datasets, industry case studies, and practical Power BI projects covering retail banking analytics, corporate banking performance, digital banking metrics, compliance analytics, and financial risk intelligence.

Programme Curriculum

Banking Analytics with Power BI Training Course

Introduction

Course Duration

5 days

Course Objectives

By completing this Banking Analytics with Power BI Training, participants will be able to:

Develop advanced banking dashboards and interactive financial reports using Power BI.
Analyze banking performance using Business Intelligence and Data Analytics frameworks.
Build automated financial KPI dashboards for executive decision-making.
Perform customer segmentation and behavioral analytics for banking growth strategies.
Apply Power BI techniques for credit risk assessment and loan portfolio analytics.
Create fraud monitoring solutions using banking fraud analytics and anomaly detection insights.
Design regulatory reporting dashboards supporting financial compliance and governance.
Integrate banking data sources using ETL processes, Power Query, and data modeling techniques.
Apply DAX calculations and advanced analytics functions for financial intelligence.
Analyze profitability through customer lifetime value and revenue analytics.
Implement data visualization best practices for executive banking reporting.
Understand emerging trends in AI-powered banking analytics and digital transformation.
Develop industry-ready analytical solutions using Power BI banking case studies and real-world scenarios.

Target Audience

Banking analysts and financial analysts
Business intelligence professionals
Data analysts working in financial services
Banking managers and decision makers
Risk management professionals
Credit analysts and loan officers
Finance and accounting professionals
FinTech professionals and aspiring data specialists

Course Modules

Module 1: Introduction to Banking Analytics & Power BI

Fundamentals of banking data analytics and financial intelligence
Overview of Power BI ecosystem and banking applications
Understanding banking KPIs, metrics, and performance indicators
Data-driven decision-making in modern financial institutions
Introduction to banking analytics case studies
Case Study: Analyzing retail bank performance using customer accounts, deposits, and transaction datasets.

Module 2: Banking Data Preparation Using Power Query

Importing banking datasets from multiple data sources
Data cleansing and transformation techniques
Handling missing values and inconsistent financial records
Creating automated data preparation workflows
Building reliable banking analytics data pipelines
Case Study: Preparing customer transaction data for a digital banking analytics dashboard.

Module 3: Data Modeling for Financial Analytics

Designing banking data models using Power BI
Creating relationships between customer, account, and transaction tables
Implementing star schema architecture
Optimizing banking analytics data models
Managing large-scale financial datasets
Case Study: Developing a banking customer 360-degree analytics model.

Module 4: DAX for Banking Intelligence

Creating calculated measures using DAX
Developing financial calculations and KPIs
Performing time intelligence analysis
Building profitability and revenue measures
Advanced DAX techniques for banking dashboards
Case Study: Calculating loan growth, customer profitability, and monthly banking performance trends.

Module 5: Banking Performance Dashboards

Designing executive banking dashboards
Creating interactive charts and financial visualizations
Tracking deposits, loans, revenue, and customer growth
Developing management reporting solutions
Applying dashboard storytelling techniques
Case Study: Building an executive dashboard for branch performance monitoring.

Module 6: Risk Analytics and Fraud Detection

Understanding credit risk analytics concepts
Developing loan portfolio monitoring dashboards
Identifying fraud patterns through analytics
Creating risk scoring reports
Supporting compliance and regulatory analytics
Case Study: Fraud detection dashboard analyzing suspicious transactions and customer behavior.

Module 7: Customer Analytics and Digital Banking Insights

Customer segmentation using analytics techniques
Analyzing customer behavior and engagement
Measuring digital banking adoption
Creating customer retention dashboards
Improving banking services through insights
Case Study: Customer churn analysis for improving digital banking customer retention.

Module 8: Advanced Banking Analytics & Future Trends

Applying AI and machine learning concepts in banking analytics
Exploring predictive analytics applications
Understanding cloud-based banking intelligence
Implementing automation in financial reporting
Building industry-ready Power BI banking projects
Case Study: Predicting customer loan risks using advanced analytics approaches.

Training Methodology

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Power BI Dashboarding Data Visualization Banking KPI Analysis DAX & Data Modeling

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 26 2026

26 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $1,000