Global information and insights company and Hong Kong’s leading consumer credit reference agency, TransUnion (NYSE: TRU), has partnered with federated learning platform Openhive to launch Hong Kong’s first enterprise grade federated learning data network (FLDN). The move opens a new chapter in how data partners across industry sectors can collaborate to create value while maintaining privacy and security.
Federated learning is a machine learning technology that allows organizations to collaborate in building and training artificial intelligence (AI) models while keeping their respective proprietary data at source to safeguard data privacy.
Data collaboration will be conducted over the Openhive Federated Learning Platform using world-leading and proven privacy-preserving AI technology. This TransUnion-Openhive FLDN is the first federated learning network deployed in Hong Kong to enable data collaboration between different data requesters and data providers, enabling new business insights using machine learning.
The FLDN future-proofs data-driven analytics by enabling privacy-preserved data collaboration, machine learning and scoring in an end-to-end platform. This opens up tremendous opportunities for data partners as the FLDN helps them to create business value from their data, and leverage TransUnion’s credit data and analytics expertise to serve different industries and wider economies, including the Greater Bay Area (GBA).
“Our partnership with Openhive is a great example of how we pursue innovation to constantly enhance our customer solutions and strengthen our technological leadership,” said Jerry Ying, Chief Product Officer, TransUnion Asia Pacific. “The launch of this federated learning platform is a significant milestone for Hong Kong. Collaboration by different parties on the platform opens the door to creating many more as yet unrealized data-driven solutions across more industry sectors.”
The partnership expands TransUnion’s established strengths in data analytics and insights, with its data being part of the FLDN for collaboration with data partners from diverse industry sectors. The TransUnion-Openhive FLDN is data agnostic, where data from any industry sector can be included in the network with data privacy being preserved to create insights that allow more informed decisions to be made.
Federated learning applications such as this fall under the Hong Kong Monetary Authority’s Regtech promotion roadmap to build new data infrastructure and encourage Regtech adoption, particularly in providing alternative credit risk assessment solutions for small and medium sized enterprises (SMEs). Using the TransUnion-Openhive FLDN, TransUnion will be able to take data analytics to a new level using a broader range of conventional and alternative data, such as rent and utility payments to offer lenders more accurate credit assessments for consumers and businesses. This will particularly help individuals and small and medium-sized businesses that have limited credit histories to get better access to the credit they need to achieve their financial goals in Hong Kong and across the Greater Bay Area. Ultimately, as well as helping businesses better manage risk and be more competitive, it will also help increase financial inclusion.
“The TransUnion-Openhive FLDN enables financial institutions to benefit from the synergy of data collaboration with TransUnion as well as other representative data providers. In compliance with data privacy and security, financial institutions can now model with alternative data on the FLDN to get more accurate predictive insights and risk assessments, which are crucial for managing businesses in the dynamic economic environment nowadays,” said Juni Yan, MD, Openhive.