In 2022, Standard Chartered, a leading cross-border bank, launched the Women’s International Network (SC WIN) to elevate women entrepreneurs as clients and strengthen its offerings for them globally. However, the bank quickly recognized a major challenge: it lacked the ability to identify women entrepreneurs within its client base, limiting its ability to understand and address their needs.
The team developed an approach to enable the bank to disaggregate its SME portfolio by sex on a current and continuing basis, with over 90% accuracy, without the collection of private personal data. Their SocialAI model uses an algorithm to predict and tag whether business owners are men or women by using the first name, country-adapted, and public and internal datasets. Its unique model is flexible enough to be deployed across its global banking network, and robust enough to inform other banks looking to do something similar. As part of its commitments as a global signatory to the WE Finance Code, Standard Chartered will make this model publicly available, enabling other Financial Service Providers to adopt and customize it to address their own data disaggregation challenges.
This case study, targeted to Financial Service Providers, provides an overview of the model Standard Chartered has deployed, including the rationale and processes for developing such a model, the challenges encountered, and potential business implications.
