BenaData/The-Rise-of-Digital-Payments-in-Kenya

End-to-end analysis of Kenya's mobile money and card payments ecosystem using 18 years of Central Bank of Kenya data (2007–2026). Python· Tableau. # The Rise of Digital Payments in Kenya ### An End-to-End Data Analysis of Mobile Money & Card Transactions (2007–2026) **Author:** Benard Musyoka Mwinzi  |  **Date:** March 2026  |  **Data Source:** Central Bank of Kenya (CBK) --- ## 📌 Table of Contents 1. Business Problem 2. Project Objectives 3. Datasets 4. Tools & Technologies 5. Part 1 —Data Cleaning & Feature Engineering 6. Part 2 — Exploratory Data Analysis 7. Part 3 — Tableau Dashboard 8. Key Findings & Insights --- ## 1. Business Problem Kenya is one of the world's most closely studied success stories in financial inclusion. The launch of M-Pesa in 2007 fundamentally transformed how millions of Kenyans access financial services. M-Pesa enables peer-to-peer transfers, bill payments, and savings through a basic mobile phone. However, despite this transformation, there had been **no consolidated analytical view** of how the two dominant digital payment channels, mobile money and card transactions, have evolved together over nearly two decades. Specifically, the following questions remained unanswered: - How fast has Kenya's mobile money ecosystem actually grown, and what is its current scale? - Are card transactions growing too, or is mobile money cannibalising card usage? - How did COVID-19 and the CBK fee waiver affect each payment channel differently? - Is Kenya genuinely moving away from cash, or are ATM withdrawals still dominant? - Which months drive peak payment volumes, and how consistent is the seasonality? Answering these questions can have direct implications for financial institutions, payment infrastructure providers, regulators, and any business that needs to understand where and how Kenyan consumers transact. --- ## 2. Project Objectives This project delivers an end-to-end analysis that: 1. **Cleans and consolidates** 18+ years of CBK payments data into a single analysis-ready dataset 2. **Uncovers trends and patterns** across mobile money and card transact …