Data Safeguard Uses AI and ML Technology to Address Data Privacy and Synthetic Fraud for Financial, Healthcare, Retail and Technology Corporations
Data Safeguard, Inc. has officially launched to enable corporations in the financial, healthcare, retail and technology industries prevent financial losses and adhere to data privacy compliance guidelines, such as the General Data Protection Regulation (GDPR), National Institute of Standards and technology (NIST) and California Consumer Privacy Act (CCPA).
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Synthetic fraud is the fastest growing cybercriminal activity that has become the nemesis of the financial industry, while data privacy and compliance has been mandated at global, federal and state levels. The company’s products use artificial intelligence (AI) and machine learning (ML) technology to help enterprises manage the Personally Identifiable Information (PII) collected throughout the customer lifecycle and identify Frankenstein Identities to mitigate financial losses.
“The number of data breaches in the U.S. has significantly skyrocketed within the past decade from a mere 662 in 2010 to over 1,000 in 20201,” said Sudhir Sahu, CEO, Data Safeguard. “Data privacy compliance mandates and synthetic fraud loss mitigation initiatives have created a significant need in the market for Data Safeguard. Our data privacy and synthetic Fraud products help enterprises meet compliance requirements and prevent financial losses. We’ve leveraged AI and ML technology to enable fast implementation in complex unstructured, semi-structured and structured data ecosystems, providing maximum return on investment for our customers.”
The Data Safeguard leadership team comprises Silicon Valley serial entrepreneurs and experienced business and technology executives with an extensive background in data privacy and synthetic fraud at some of the world’s top enterprise corporations.
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“Our diverse executive leadership team has known and worked together for two decades and have come together to build Data Safeguard to help enterprises with data privacy and synthetic fraud challenges,” said Sahu.
Data Safeguard’s data privacy products include ID-Mask and ID-Redact, which intelligently redact and mask sensitive data including unstructured, semi-structured and structured data in various environments. They also provide substitute sensitive information with realistic functional masked data to protect confidentiality while managing data lineage throughout the data lifecycle.
Synthetic fraud is addressed with Data Safeguard’s ID-AML and ID-Fraud products that feature AI and ML technology to intelligently detect and identify risk within a company’s data ecosystem. The product detects, identifies, confirms and tags real customers versus Frankenstein Identities that try to obtain a credit card or loan portfolios using fake PII. The company’s Data Science Lab can be custom configured for customers to manage their data from various business lines to make informed decisions.
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