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Global bank HSBC has taken its first pilot machine learning projects with Google Cloud Platform (GCP) into production and is now looking to ramp up the porting of applications and data workloads onto the vendor’s cloud infrastructure, once Google provides more granular encryption key controls in August.

HSBC is a much-vaunted Google Cloud Platform customer and a key account in Google’s attempts to court the financial services industry, with global HSBC CIO Darryl West speaking on stage at the Google Cloud Next event last year. In terms of scale, HSBC says it will have 100PBs of data on GCP by 2018.

The first two machine learning use cases the bank has put into production focus on country-by-country liquidity reporting and anti-money laundering.

West, speaking on stage during Google Cloud Next in San Francisco this week, said that the live liquidity reporting algorithm gives HSBC a country-by-country view in “minutes not hours”, providing the bank with a massive productivity boost in this area.

HSBC is also using a Google BigQuery data warehouse for real time anti-money laundering analytics, and is running a machine learning model on top of time series data to identify potential cases faster and more accurately. This is particularly important following the hugely damaging Mexican case of money laundering the bank was fined $1.9 billion for in 2012.

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