Client Overview
KCB Group is one of East Africa’s largest financial services organizations, serving millions across Kenya, Uganda, Tanzania, Rwanda, Burundi, and South Sudan. With a vision to drive financial inclusion and customer-centric innovation, KCB sought to leverage advanced analytics to deepen customer relationships.
The Challenge
KCB was experiencing plateauing customer engagement on digital channels — particularly mobile and online banking platforms.
They faced challenges with:
Low activation rates among new customers
Increasing churn rates in younger customer segments
Limited personalization in offers and communication
Key question:
How can we predict customer behavior and proactively drive loyalty in a digital-first environment?
The Solution
KCB partnered with their internal Data & Analytics team to deploy a Predictive Customer Engagement Model, powered by machine learning.
Steps taken:
Aggregated customer transaction data, app usage data, CRM histories, and call center logs.
Built churn prediction models using Random Forest and Gradient Boosting techniques.
Segmented customers based on likelihood to churn, lifetime value (LTV), and product affinity.
Developed personalized marketing journeys based on predictive insights (e.g., offer mobile loan products to likely borrowers, send personalized savings tips to at-risk savers).
Integrated real-time model outputs into KCB’s marketing automation platform.
Implementation Highlights
Data Sources Integrated: Over 15 internal datasets, including mobile money transactions and credit card usage
Time to Launch: 4 months from project kickoff to model deployment
Collaboration: Joint squads with Data Scientists, CRM Managers, and IT teams
The Results
35% increase in mobile banking activity within 6 months
22% reduction in churn among newly onboarded customers
18% uplift in cross-sell conversion rates (customers accepting a second product)
Enhanced NPS (Net Promoter Score) by +12 points in digital channels