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AI Use Case

Optimise retail network based on demand modelling

Optimise retail network locations based on multiple signals of demand (e.g., social data, footfall, transactions). This would - for example - help a retailer to plan their expansion in to a new market. Alternatuvely this might enable cost savings across a retail banking operation where it would likely cover both branches and ATMs - at the risk of medium to long term revenue loss and potential negative customer and press reaction.



Network Operations


Cost - Optimise geographic footprint ,Revenue - Better targeting,Operational - Network optimisation

Case Studies

Stanford University~Researchers at Stanford and Columbia predict restaurant affinity among lunch-goers in the Bay area using machine learning

Potential Vendors


Financial Services


Data Sets

Structured / Semi-structured,Time series,Text

AI Technologies

Traditional AI,Machine Learning (ML),ML Task - Action Selection - Reinforcement Learning

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