Your models know who is likely to default, churn or buy. So why is a person still deciding what to do about it?
South African banks are competing harder than ever for the customers who define long-term value: the primary salary account, the growing household, the first-time borrower. Digital-first challengers, tighter margins and rising pressure on the cost of credit have made “good enough” offers and one-size-fits-all credit rules expensive.
Most banks have invested heavily in predictive models. Far fewer have closed the gap between a prediction and the right decision for each individual customer. That gap is where lifetime value is won or lost.
In this session, Matthew Hubbard shows how leading banks turn analytics into action. You’ll see practical decision strategies across the customer lifecycle and what it takes to run them at scale.
- The four levers that grow customer lifetime value: acquire the right customers, deepen the relationship, keep customers longer, and lower cost to serve and risk
- How value-based onboarding, next-best-product offers and life-event triggers help you win the salary account and cross-sell at the right moment
- Why two customers with the same default risk can warrant very different credit limits
- How early-warning strategies spot customers heading for trouble before they miss a payment
- The shift from predictive to prescriptive: how optimisation engines work within the goals and constraints your people set
- The data, real-time decisioning and governance foundations required, and why you can start with one use case and scale
