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Cape Privacy Forges Partnership with Snowflake

Regulation and Compliance ManagmentFinancial ServicesNews
By AIT News Desk On Nov 19, 2021
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Innovative Application of Secret Sharing and Secure Multiparty Computation Means Firms Can Extract Vital Decision Intelligence from Encrypted, Private Information

Cape Privacy has joined the Snowflake Partner Network to partner with Snowflake, the Data Cloud company. As a Snowflake partner, Cape Privacy enables the unique ability for financial services firms to run predictive machine learning models on encrypted data in Snowflake, while protecting privacy by default.

PREDICTIONS-SERIES-2022

In financial services there has traditionally been friction between the collection and use of personally identifiable information (PII) and payment card information (PCI) because of the risk of exposure and abuse. Regulatory restrictions have kept financial services firms from putting that valuable data to work, and the steps required to protect sensitive data create conflict with its use for generating valuable decision intelligence.

Recommended AI News: TCS Study Finds More Than 50% Of Global Senior Financial Leaders Get Short-Term Forecasts Wrong

Encryption is the cornerstone of any data protection and compliance program, but encrypted data is difficult to work with for creating decision intelligence. Cape Privacy enables businesses to run predictive models on previously inaccessible encrypted data in Snowflake–without decryption.

Cape’s platform uses secret sharing and secure multiparty computation (MPC) to operationalize the data securely, avoiding a single point of failure and enabling computations on data that was previously inaccessible. Instead, encrypted data can now be transferred to Snowflake, along with whatever models the user chooses, and run predictions using the encrypted data. Because the data is never decrypted, privacy and security compliance are assured.

Recommended AI News: Dash Integrated With TRM Labs To Expand Anti-Financial Crime Monitoring Capability

Here’s how it works:

  • Data is client-side encrypted and uploaded to Snowflake;
  • A user submits a query to Snowflake;
  • Cape Privacy securely processes a prediction on the encrypted data; and,
  • The prediction results are shared back with the user though Snowflake.

“Financial services firms that collect sensitive, private data have struggled with the dilemma of choosing between keeping data secure, and using it to its fullest potential. With Cape Privacy’s secure, multiparty computational platform, our customers are able to leverage encrypted data to gain a more granular understanding of their customers, better identify market trends, and improve product performance and business outcomes while maintaining respect for the privacy of their own customers,” said Tarik Dwiek, Head of Technology Alliances at Snowflake.

The Cape Privacy partnership complements Snowflake’s powerful, secure data sharing and multi-party permissioning capabilities by allowing customers to fully utilize the broad array of AI and data modeling tools available in Snowflake. Now, private, encrypted data is sent to the Cape Privacy platform within Snowflake, along with the user organization’s chosen data model.

“Our partnership allows Snowflake customers to maximize the value of the private data they have in the Snowflake data cloud because they can secure it with strong encryption, move it into Snowflake, and run their models in Snowflake and with the tools available in Snowflake, taking advantage of the full richness of the data to extract high-value decision intelligence without ever having to decrypt the data,” said Cape Privacy CEO, Ché Wijesinghe.

The benefits and capabilities of Cape’s platform are available immediately to Snowflake customers.

Recommended AI News: Crypto Platform Gemini Raises $400 Million In Growth Equity Funding Valuing it at $7.1 Billion

[To share your insights with us, please write to sghosh@martechseries.com]

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AIT News Desk is a trained group of web journalists and reporters who collect news from all over the technology landscape. The technical space includes advanced technologies related to AI, ML, ITops, Cloud Security, Privacy and Security, Cyberthreat intelligence, Space, Big data and Analytics, Blockchain and Crypto.
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