Most banks manage to nip 90% of credit fraud in the bud. However, the challenge for them lies elsewhere: firstly, to tackle the 10% of residual fraud, that small figure that costs a lot in terms of turnover, resources and reputation; and secondly, to adapt to the acceleration of fraud, boosted by the digitalization of uses and new technologies.
Carrefour Banque began examining the issue with fresh eyes back in 2017, taking a close look at the role of Artificial Intelligence (AI) and Machine Learning (ML) in the fight against fraud: since digital transformation intensified threats and professionalized fraud, the systems for fighting it had to evolve as well. But where should Carrefour start, using which tools and with which partner?
The secrets to success? A step-by-step process in collaboration with an expert partner to bring out the right tools, in the right place, at the right time, with the right mix of pragmatism and ambition.
Carrefour Banque's journey is unique and emblematic of the steps and best practices to follow in order to effectively integrate AI/ML into your existing solutions and better thwart credit fraud.
Let's take a look behind the scenes at this successful transition, which is based on a 3-phase model: injection, connection, and improvement.
"The benefits of the solution became apparent very quickly. Everything was done in 10 months, and from the very beginning, we were already able to stop fraud. The businesses saw ROI quickly, and easily became accustomed to the solution. And all the while, the model continued to train and adapt to our needs as it was used. A true virtuous circle."
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