Client | A Well Known UK Bank.
TASK | Retail Banking Attrition Prediction
Customer retention and support is a necessary feature of any bank, with customer attrition being a particularly key aspect. Customers who go on to leave the bank not only remove capital but, may also spread negative sentiment about the retail bank. To avoid this extensive customer support, monitoring, and outreach efforts are needed.
By monitoring complaint logs timely intervention can stop customer attrition, however this is time and skill intensive, requiring competent operators working full- time. To ameliorate this issue the client company, sought to develop a scalable solution that could predict which customers were likely to leave via the ingestion of customer data.
Working on behalf of the client, we constructed and supervised-AI approach that ingested customer complaint data in order to predict which customers would leave and highlight them for intervention.
This required a system capable of ingesting inconsistent and sometimes erroneous fields from a variety of sources, all while maintaining data security and avoiding outside exposure. These systems are a core feature of our business and are designed to be repeatable and fast.
Project is still in-progress, with the aim to be completed in late 2021.
Client was left with a fully functional system that could fulfil all the requirements of the NGO mandate, as well as additional features such as the ability to detect water, electrical coverage, and vegetation.
Client continued our contract for further work in processing unique data-sets for a series of hedge funds.