Synthesized launches AI-driven platform to detect and remove biases in data

Released as a freemium version, the offering incorporates AI research and techniques to enable financial organisations to identify potential biases within their data and immediately start to remediate these flaws.

The platform was designed by the UK-based firm to understand a wide array of regulatory and legal definitions regarding contextual bias. It can automatically identify bias across data attributes like gender, age, race, religion, sexual orientation, and more. 

Synthesized is making the capability available immediately, requiring no coding or deep technical expertise to get started. Financial users simply upload a structured data file, like a spreadsheet, to kick off the analysis process. The data platform could be used in finance to create fairer credit ratings.

Beyond this analysis and bias detection, the platform also offers another feature: to automatically remove the biases present in an entire dataset in a process called rebalancing. 

While there are a number of existing, limited techniques to rebalance biased data, Synthesized has developed a proprietary algorithm within its platform that is quicker and more accurate. The AI-driven platform has the ability to make randomised changes, at scale, to an original, biased dataset to construct a new, entirely synthetic dataset. With the generation of synthetic data, Synthesized’s platform gives its users the ability to equally distribute all attributes within a dataset to remove bias and rebalance the dataset completely. Users can also manually change singular data attributes within a dataset, such as gender, providing granular control of the rebalancing process. 

• Rebalancing: As mentioned, the final feature available in this process is the ability to automatically rebalance biased data.

The Community Edition is one part of Synthesized’s data platform. The complete platform uses AI to automate all stages of data provisioning; the process of making data available in an orderly and secure way. This level of automation enables organisations to generate synthesized datasets, allowing them to better test data for new products and tools, validate mathematical models, or train machine learning models.  

Synthesized was founded in 2017. Just two weeks before the UK went into lockdown in March 2020, the company closed a seed funding round of GBP 2.2 million. More recently it collaborated with the Financial Conduct Authority (FCA) to launch a collection of synthetic fraud datasets for secure third-party collaboration in the Digital Sandbox Pilot, jointly launched by the FCA and City of London Corporation.