“We are interested in what the industry sees as the role of the regulator in providing synthetic data, particularly in relation to our competition mandate, and the appetite of companies to engage with regulators and/or other organizations to generate synthetic data.”
The Financial Conduct Authority, the UK’s financial watchdog, has called for input from industry – academics, incumbents. start-ups. RegTechs and FinTechs, technology companies, regulators and decision-making bodies – with regard to “synthetic data”.
The regulator said it wanted to understand the current maturity of the “synthetic data” market in financial services and its potential to securely open up data sharing between companies, regulators and other public bodies.
Arguing that data, which drives valuable innovation in an increasingly digital financial services sector, must be protected and consumers’ right to privacy preserved, the government body explained its intentions.
“Increasingly, innovation in financial services is data-driven, requiring large volumes of high-quality data to develop and train accurate and efficient models and systems.
“However, financial data – such as records of consumer transactions, account payments or commercial data – is sensitive personal data subject to data protection obligations, in addition to often being commercially sensitive. “, said the agency, adding that this is where it believes synthetic. data can help.
“To ensure that our innovation services remain fit for the digital age, we seek your input. We want to better understand the perspectives of different market participants on how synthetic data can expand data access and data sharing opportunities in the market.
The FCA also assesses the maturity of the use of synthetic data in financial services and the extent to which regulated and unregulated firms use it.
“Finally, we are interested in what the industry sees as the role of the regulator in providing synthetic data, particularly in relation to our competition mandate, and the appetite of companies to engage with regulators and /or other organizations to generate synthetic data.”
The FCA, like many other large corporations and financial organizations, already uses synthetic data to create sophisticated fraud detection models to assess a customer’s level of financial vulnerability and make nuanced and accurate decisions based on in lending to SMEs.
While the main drivers are protecting privacy and acquiring enough quality data to test and train machine learning models, synthetic datasets have other compelling benefits as well.
A report by JP Morgan found that traditional machine learning techniques struggled to detect anomalies in the highly unbalanced “real world” datasets used to train fraud detection models. Generating synthetic data, on the other hand, allows companies to combat class imbalance in these datasets, leading to much more accurate results.