Peter M.J. Gross

Peter M.J. Gross

May 11, 2022

Fast Company Recognizes How External Data Can Change the World

When external data is paired with machine learning, the results can change the world. The potential of such partnerships was recognized by Fast Company’s World Changing Ideas 2022 list, which honored Demyst and TruEra for their work using AI and data to empower positive change.

TruEra and Demyst worked together to develop a solution to mitigate bias in AI-based credit decisioning models, such as those used by financial services companies, demonstrating how external data can be a key part of driving new and effective machine learning use cases. This will improve applications that are based on machine learning models, which can be held back by model performance or bias issues, particularly in regulated industries.

Scott Albin, Chief Strategy Officer at Demyst, said, “We are proud to be recognized by Fast Company. It’s a clear demonstration that machine learning use cases can be both expanded and dramatically improved by the use of high quality, curated, and compliant external data.”

Collaboration between TruEra and Demyst previously showed how third-party data and AI quality management solutions can work together to improve the accuracy and fairness of credit decisioning models. Their project won the Global Veritas Challenge 2021 at the Singapore Fintech Festival, the world’s largest fintech event.

Demyst already accelerates the deployment of external data solutions for the world’s leading banks, insurers, and fintechs. The work with TruEra has developed a clear and straightforward process to show how software can improve model performance while achieving the goals of responsible, fair AI 

Fast Company’s list honors projects that harness the power of data to empower change. The collaboration with TruEra is a compelling example of external data unlocking innovation to drive business growth. And this growth can be accelerated by the Demyst platform, which eliminates the friction associated with external data procurement, testing, and deployment.

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