Product: LeapYear platform
LeapYear, a global software services provider, enhanced its data-sharing capabilities to help financial institutions securely share data across business lines, international borders and third-party sites. The technology platform's efficacy and privacy protections have been validated by experts in a variety of disciplines, stated Garrett Long, vice president of marketing at LeapYear.
"Traditional methods to protect data mask too much data, trap value and protect privacy in a non-rigorous, unprovable way," Long said. "LeapYear provides transparent and interpretable privacy for the world's most sensitive information, helping our customers extract maximum value from their data while setting a new standard for provable privacy."
Describing the LeapYear platform as an enterprise software layer that installs on customers' systems, Long noted the LeapYear platform can be deployed on-premises, in the cloud and in hybrid configurations.
The LeapYear platform is a core technology that enables customers to share and analyze sensitive data, Long noted, adding that the platform provides customers with a new capability that enables them to share and analyze sensitive data with transparent and interpretable privacy. In addition to ensuring that no data can be seen, reverse-engineered or extracted by analysts, data residing on the platform never has to be moved or modified, Long pointed out. A transparent, interpretable level of privacy protects all data sets, he stated, enabling users to derive maximum value from each analysis without needing to mask or remove information.
Long additionally noted that LeapYear end-users have found the platform helps them manage data while meeting regulatory requirements, contractual obligations and customer expectations. ISOs and channel partners have reported that the platform helped expand projects in their opportunity pipelines through secure, efficient data sharing, he added.
LeapYear commissioned Aite-Novarica Group to survey market participants about use cases for sharing data inside a firm. The report, New Edges: How to Make the Most of Trading Flow Data, based on a survey conducted between September and December 2021, cited best practices for data sharing.
Survey respondents recommended choosing data sharing techniques based on goals and deciding whether to share data in real time, near real time or by batching. Masking techniques included combining data sets with similar attributes to obscure individual identifying information and substituting data elements with random characters to obscure sensitive data.
Respondents also suggested using pseudonyms and machine learning to disguise real data sets. They additionally proposed using multi-party computation and cryptography to help parties with limited trust share and analyze data without revealing underlying data sets. A copy of the report is available at https://leapyear.io/new-edges-how-to-make-the-most-of-trading-flow-data/.
Long mentioned that LeapYear is a leading software company in the growing space of privacy enhancing technologies (PETs). "Our solutions are based on differential privacy, a mathematical approach to providing privacy while analyzing data sets," he said. "Differential privacy has been adopted by large corporations (such as Apple and Google) to protect sensitive user information. LeapYear is the first commercially available platform that achieves differentially private standards across a broad spectrum of data analysis workflows."
The world's largest institutions use the LeapYear software platform to safely unlock the full value of their data, Long stated, adding that leading companies in financial services and healthcare have deployed LeapYear to transcend boundaries set by conventional data strategy, build new data partnerships, offer new data products and reach new levels of profitability, all while keeping their data fully protected.
Companies that want to compete in an AI and data-driven economy must put all their data into play and do so with the highest standard of data protection, and LeapYear is poised to embed privacy and trust into the future of data, Long said.
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