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Data Science at a Global Retail Bank

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Background


A global retail bank wanted us to identify the impact introductory offers applied to their products had on putting customers into financial difficulty.

What We Are Doing


  • Using predictive analytics to identify gaps in the design, approval and maintenance of financial products that could put customers at risk
  • Pre-empt and identify customers in financial difficulty appropriately and identify failure to meet regulatory post-sale service 
  • Support the modelling design using data warehouses
  • Aggregating and consolidating information from multiple sources
  • Cleansing and processing data so it’s ready for visualisation
  • Cost-efficient approach to using 100% of the population data to provide detailed risk insights and assurance not achievable through traditional monitoring approaches, or without the investment of significant resource 
  • The outcome being a repeatable model that can be deployed across separate business lines and geographical regions

Get in touch

Send us your Brief or Requirements

We understand that projects, cultures, budgets, engagement models and expectations vary.  Tell us how we can help you deliver on your requirements.  

                                 

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