BNY Mellon Harnesses Google Cloud To Build Predictive Models

The Bank of New York Mellon Company (BNY Mellon) recently announced that it would be pairing up with Google Cloud to develop an innovative solution that will enable the bank’s clients to forecast 40% of daily settlement failures. Harnessing the capability of Google Cloud technologies, the AI-powered solutions aimed at settlement failures will improve overall market liquidity while underscoring BNY Mellon’s ongoing dedication to facilitating an open-architecture approach.

The use of Google Cloud will aid market participants in predicting the estimated billions of dollars in daily settlement failures, generating large capital and liquidity savings, and unlocking operational efficiencies. The project will harness Google Cloud’s data analytics, artificial intelligence, and machine learning technologies to build new collateral management and liquidity solutions built on the cloud. This falls in line with the bank’s devotion to delivering informed investment and wealth management services across 35 countries. Today, BNY Mellon has $41.1 trillion in assets under custody and/or administration, and $2.2 trillion in assets under management.

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Speaking on the collaboration, Brian Ruane, CEO of BNY Mellon Clearance and Collateral Management said, “We are excited to work with Google Cloud to develop a first-of-its-kind solution to help our clients predict approximately 40% of settlement failures in Fed-eligible securities with a 90% accuracy.”

Ruane furthered shared that “this prediction model could be a game-changer for market participants.” Settlement failures occur when buyers are unable to exchange cash and securities by end of business to meet the scheduled settlement date. With the U.S. Treasury market being the largest and most liquid in the world, facing 2% settlement failures daily, the ability to use Google Cloud technology is a huge innovation toward the future of banking. It was shared that the bank will also develop AI-powered solutions for securities lending, liquidity forecasting, dynamic controls for pricing, anomaly detection for transactions, and automated document processing.

The use of this technology to enable predictive models for anticipating cash flow and capital on hand will no doubt continue to improve outcomes for BNY Mellon’s clients, and will likely develop as a further trend across the banking industry.