- Chief Compliance Officer and VP of Legal Affairs, Arrow Electronics
By 
Aaron Nicodemus2023-06-27T22:58:00
Google Cloud launched a new anti-money laundering product for financial institutions that utilizes artificial intelligence (AI) and machine learning (ML) to replace the manually defined rules most existing AML detection programs use to spot suspicious transactions.
The company announced the product in a June 21 press release, touting in initial tests by HSBC it detected two to four times more true positive risk of money laundering activity in the U.K. bank’s transactions while reducing alert volumes by 60 percent.
Google Cloud’s AML AI generates a customer risk score using ML. The risk score is “based on the bank’s data, including transactional patterns, network behavior, and know your customer (KYC) data, to identify instances and groups of high-risk retail and commercial customers,” according to the company’s release. “The product can adapt to changes in underlying data, delivering more accurate results, which increases overall program effectiveness and improves operational efficiency.”
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Alphabet, the parent company of technology giant Google, agreed to pay $350 million in a preliminary settlement with shareholders over alleged data privacy violations and materially false and misleading statements linked to now-defunct social media site Google+.
ABN AMRO, ING, Rabobank, Triodos Bank, and de Volksbank are each participating in a first-of-its-kind collaboration to shine light on the estimated €16 billion worth of illicit funds coursing through the Netherlands’ banking system every year.
Technology companies including Google, Meta, and OpenAI agreed to a series of voluntary commitments they’ll make regarding their management of risks when developing artificial intelligence systems.
Data governance has become a key concern for companies, especially when the EU AI Act and General Data Protection Regulation have put a premium on handling data responsibly and ensuring that artificial intelligence does not cause harm.
The era of artificial intelligence adoption is testing the old ways of doing compliance, underscoring the need for continuous monitoring. Compliance isn’t a one-and-done activity, but sometimes organizational incentives and goals fail to prioritize the importance of this.
While companies are exploring and building artificial intelligence technology, lawmakers and regulators are trying to identify what ground rules they need to set. These guardrails are what companies and governments alike believe are essential parts of ensuring safe and responsible use of the technology.
