A Latin American bank was experiencing relatively low usage—along with high rates of attrition—in its credit card business. The client turned to Accenture, the bank’s analytical reference partner, for customer analytics.

Strategy and solution

We developed an analytics-based decision system to recommend the next best card action (NBCA) for each cardholder.

Two components combined to deliver personal recommendations:

  • Predictive models estimated the probability and profitability of various behaviors, such as reactivation, growth in number and amounts of transactions through installment purchases and cash advances.
  • Multiple segmentations revealed the needs satisfied with the card. The first looked at transactional or financing needs and another detailed the revolving installment in cash advances. Further segmentation revealed the types of shops in which the client used the card and typical paths of engagement with merchants.

We implemented the models in the client’s analytical-probes platform. With each update of the source data, the system produces recommendations, suggesting actions and best ways (e.g., favored stimuli for higher rates of commercial effectiveness) to achieve the desired outcomes.


Through NBCA, the bank can conduct sharply targeted promotions that improve management of the client lifecycle and boost business outcomes. Based on experience in similar customer-analytics projects, we forecast results will grow by millions over the first year of system usage. Additional revenues are likely as the active customer base increases and the system gains sophistication.

Multiple Accenture assets allowed for fast development and enabled smooth integration into the client’s processes. The solution was built from a predefined data model, with analytical-model accelerators and predefined decision architecture. Built on an open platform, the solution is ready to be enriched with further predictive models designed for high performance.

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