Qorus Banking Innovation Awards 2014 - Winner

Multibanked customer management

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08/09/2014 Banking Innovation

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This predictive statistics-driven model detects – through a wide set of indicators – multibanked customers and their ‘hidden value’, giving Intesa Sanpaolo relationship managers the chance to perform a root-cause analysis of their multibanked status and then develop the relationship with these customers through special offers and packages to increase their loyalty.

Innovation presentation

A recent customer satisfaction survey underlined that around one fifth of interviewed customers declared they had a relationship with multiple banks. As a result, Intesa Sanpaolo conceived the Multibanked Customer Management project with the aim of identifying these customers and then exploiting their ‘hidden value’.

To do this, the bank developed a model to better understand its customers and address their actual needs through ad hoc offers and marketing campaigns in order to improve their loyalty.

A key achievement has been the ability to predict and detect a customer’s status, and provide frontline workers with several levers to develop their relationship with customers. Intesa Sanpaolo worked on crafting ad hoc marketing campaigns, guiding its relationship managers along all the key steps to deepen consumer knowledge and create meaningful relationships, and delivering specific offer packages to drive customers towards a higher level of fidelity.

The project has been mainly led and orchestrated by the bank’s customer relationship management department and was rolled out in early 2014, with continuous fine tuning focused on improving the ability to detect multibanked customers with greater accuracy.

The analysis allowed the bank to understand that around 20% of its customer base had multiple relationships with banks, with more than half of them considering Intesa Sanpaolo as a secondary bank.

Uniqueness of the project

The project has allowed the bank to revolutionise the way it manages the multibanked customer, moving from traditional analysis to an approach based on predictive statistics, which gives it the ability to mine customer insights and identify actionable indicators, therefore helping its relationship managers better address the needs of this specific customer cluster. In parallel, the bank has defined specific offers and marketing campaigns for multibanked customers, which are tailored according to type/quality of current relationship with Intesa Sanpaolo (primary bank versus secondary bank, for example).

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