Evaluating utility in synthetic banking microdata applications
This work addresses the challenge for financial regulators in accessing and sharing sensitive banking data, though it is incremental as it builds on existing synthetic data methods with a new evaluation focus.
The authors tackled the problem of restricted access to banking microdata by developing a framework to evaluate utility and privacy in synthetic data generation, applying it to financial indices, yield curves, and transition matrices using data from the Central Bank of Paraguay, with results showing that frequency-based applications and marginal-based inference outperform GAN models.
Financial regulators such as central banks collect vast amounts of data, but access to the resulting fine-grained banking microdata is severely restricted by banking secrecy laws. Recent developments have resulted in mechanisms that generate faithful synthetic data, but current evaluation frameworks lack a focus on the specific challenges of banking institutions and microdata. We develop a framework that considers the utility and privacy requirements of regulators, and apply this to financial usage indices, term deposit yield curves, and credit card transition matrices. Using the Central Bank of Paraguay's data, we provide the first implementation of synthetic banking microdata using a central bank's collected information, with the resulting synthetic datasets for all three domain applications being publicly available and featuring information not yet released in statistical disclosure. We find that applications less susceptible to post-processing information loss, which are based on frequency tables, are particularly suited for this approach, and that marginal-based inference mechanisms to outperform generative adversarial network models for these applications. Our results demonstrate that synthetic data generation is a promising privacy-enhancing technology for financial regulators seeking to complement their statistical disclosure, while highlighting the crucial role of evaluating such endeavors in terms of utility and privacy requirements.