Banking Payment Analytics Training Course

Banking Payment Analytics Training Course

Introduction

Banking Payment Analytics Training Course is designed to equip banking professionals with the knowledge and practical skills required to analyze, optimize, and secure modern payment ecosystems. As financial institutions rapidly adopt Digital Payments, Real-Time Payments, Open Banking, ISO 20022, AI-driven Analytics, Fraud Detection, Payment Intelligence, Data Analytics, Financial Crime Compliance, Customer Journey Analytics, Embedded Finance, and Predictive Analytics, professionals must develop advanced analytical capabilities to improve operational efficiency, regulatory compliance, customer experience, and profitability. This program provides practical exposure to payment data analysis, transaction monitoring, payment risk management, KPI dashboards, and strategic decision-making using real banking scenarios.

The course combines Artificial Intelligence (AI), Machine Learning (ML), Business Intelligence (BI), Big Data Analytics, Payment Risk Analytics, AML Analytics, Customer Behavior Analytics, Digital Banking Transformation, Cloud Analytics, API Banking, FinTech Innovation, Blockchain Payments, and Data Visualization to help participants understand evolving payment infrastructures. Through hands-on exercises, banking case studies, interactive workshops, dashboards, and real-world projects, participants will gain the expertise needed to support digital transformation initiatives, improve payment performance, strengthen fraud prevention strategies, and deliver data-driven business insights that align with global banking best practices.

Course Duration

10 days

Course Objectives

By the end of this training, participants will be able to:

1. Understand modern Digital Payment Analytics frameworks and banking payment ecosystems. 
2. Analyze Real-Time Payment transaction data for operational excellence. 
3. Apply AI and Machine Learning techniques for payment analytics. 
4. Develop Fraud Detection Analytics models using transaction intelligence. 
5. Implement ISO 20022 Payment Analytics for payment modernization. 
6. Build Interactive Banking Dashboards using Business Intelligence tools. 
7. Measure and optimize Payment KPIs and Performance Metrics. 
8. Perform Customer Payment Behavior Analytics for personalized banking. 
9. Utilize Predictive Analytics for payment forecasting and demand planning. 
10. Strengthen AML, KYC, and Financial Crime Analytics capabilities. 
11. Leverage Open Banking APIs and payment data integration. 
12. Improve Operational Risk Analytics across payment channels. 
13. Design a Data-Driven Payment Strategy aligned with digital banking transformation. 

Target Audience

• Banking Executives and Senior Managers 
• Payment Operations Professionals 
• Digital Banking Teams 
• Risk Management and Compliance Officers 
• Fraud Investigation and AML Analysts 
• Business Intelligence and Data Analytics Professionals 
• FinTech and Payment Solution Specialists 
• IT, Technology, and Digital Transformation Managers 

Course Modules

Module 1: Banking Payment Ecosystem

• Evolution of payment systems 
• Domestic and cross-border payments 
• Payment rails and infrastructure 
• Payment stakeholders 
• Case Study: Digital payment transformation in a commercial bank 

Module 2: Digital Payment Analytics

• Digital payment trends 
• Payment transaction lifecycle 
• Payment data sources 
• Digital banking KPIs 
• Case Study: Measuring digital payment growth 

Module 3: Payment Data Management

• Banking data architecture 
• Data quality management 
• Master data governance 
• Data integration techniques 
• Case Study: Building a payment data repository 

Module 4: Payment Performance Analytics

• Payment success rate analysis 
• Transaction monitoring 
• Customer payment analytics 
• Operational performance metrics 
• Case Study: Improving payment processing efficiency 

Module 5: Fraud Detection Analytics

• Fraud indicators 
• AI-based fraud detection 
• Behavioral analytics 
• Fraud risk scoring 
• Case Study: Detecting card payment fraud using analytics 

Module 6: AML & Financial Crime Analytics

• AML transaction monitoring 
• Sanctions analytics 
• Suspicious activity detection 
• Risk segmentation 
• Case Study: AML analytics implementation in retail banking 

Module 7: ISO 20022 Analytics

• ISO 20022 message standards 
• Payment data enrichment 
• Structured payment reporting 
• Migration analytics 
• Case Study: ISO 20022 migration dashboard 

Module 8: Open Banking & API Analytics

• API banking fundamentals 
• Open Banking ecosystem 
• API performance metrics 
• Third-party payment analytics 
• Case Study: API payment monitoring 

Module 9: AI & Machine Learning in Payments

• Predictive analytics 
• Machine learning models 
• Payment forecasting 
• Intelligent automation 
• Case Study: AI-based payment anomaly detection 

Module 10: Customer Payment Analytics

• Customer segmentation 
• Payment behavior analysis 
• Customer lifetime value 
• Personalization strategies 
• Case Study: Customer payment preference analysis 

Module 11: Risk Analytics

• Operational risk analytics 
• Credit risk in payments 
• Liquidity analytics 
• Enterprise risk dashboards 
• Case Study: Payment operational risk assessment 

Module 12: Business Intelligence & Visualization

• Power BI dashboards 
• Tableau analytics 
• KPI visualization 
• Executive reporting 
• Case Study: Executive payment analytics dashboard 

Module 13: Cross-Border Payment Analytics

• SWIFT analytics 
• Cross-border payment monitoring 
• FX payment analytics 
• Correspondent banking 
• Case Study: International payment optimization 

Module 14: Emerging Payment Technologies

• Blockchain payments 
• CBDC analytics 
• Embedded finance 
• Digital wallets 
• Case Study: Blockchain payment analytics framework 

Module 15: Banking Payment Analytics Capstone

• End-to-end payment analytics project 
• Dashboard development 
• Executive presentation 
• Performance improvement strategy 
• Case Study: Enterprise banking payment analytics implementation 

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@datastatresearch.org or call +254724527104 

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 DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.