Bairong Inc., a China-based AI-powered tech platform, has reportedly announced the launch of Indra, a computing platform for multiple parties that fulfill key needs of privacy protection in the data development process.

Bairong primarily focuses on privacy protection and data security with its dedication to the exploration of applications based on big data and AI. Bairong’s AI team of experts engineered Indra and integrated industry-leading tech for privacy protection and data collection to perceive a creative solution compliant to multiple scenarios of the financial application.

Indra provides an efficient and safe mode of data cooperation for financial institutions and partners. This enables them to explore the potential of data with an assurance of data usage policy compliance and prevention of data leakage.

Shaofeng Zhang, Chief Executive Officer & Founder of Bairong, commented that Indra is the result of Bairong’s years of experience in analyzing data for financial enterprises. The company created the platform based on Federated Learning and secure computing of multi-parties. It also customized its features particularly to the requirements of applications based on big data in the finance industry.

Zhang added that the company has developed a breakthrough AI-powered platform for risk control that assures both privacy and data availability for all involved parties.

Indra is utilized for multiple financial scenarios of big data applications, which includes matching blacklists for banks. The platform comprises a consolidated display of blacklists and multi-platform loan lists from different partners. Financial institutions can choose from these lists and match them against their own list.

Indra uses Federal Learning to support highly accurate online prediction models based on powerful cryptography methods like private set intersection (PSI). This feature is useful in calculating the results of corresponding financial models by matching user IDs from various parties without disclosing personal details. In addition, the technology uses data sets from different parties that allow secure joint modeling.

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