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Bank of New Zealand joins Intel early adopter scheme for innovative AI in finance

Bank of New Zealand joins Intel early adopter scheme for innovative AI in finance

This bleeding edge technology will enable us to understand our customers far better than we ever have before and help them make smarter decisions, says David Bullock, director of products and technology at BNZ.

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The Bank of New Zealand is among the first adopters of Intel’s Saffron Anti-Money Laundering (AML) Advisor.

 “We’re excited to be working with Intel Saffron on truly bleeding edge technology that will enable us to understand our customers far better than we ever have before and help them make smarter decisions,” says David Bullock, director of products and technology at BNZ, in a statement

By staying at the forefront of AI, we can help ensure we have access to the latest, innovative technologies that enhance our business."

 "With today’s launch of Saffron, Intel is delivering the first associative memory AI solution specifically tailored to the needs of our financial services customers,” says Andrew Ridley, financial services industry manager at Intel.

He says Saffron systems allow BNZ to take advantage of its existing big data platform to glean increasingly sophisticated insights for innovative customer service.

"With the increased adoption of AI, banks will be much better able to uncover fraud, boost customer engagement and increase internal efficiencies," says Ridley. “Our customers who are part of the Intel Saffron AML Early Adopter Program have the opportunity to reap the benefits of this innovative technology while helping to define the future of associative memory AI in financial services.”

Intel says Saffron’s associative memory AI simulates a human’s natural ability to learn, remember and reason in real time. It mimics the associative memory of the human brain to surface similarities and anomalies hidden in dynamic, heterogeneous data sources, while accessing an infinitely larger data set than its human counterparts. 

The AML Advisor surfaces these patterns in a transparent way, paving the way for “white box AI” in enterprise applications. These systems are designed to enhance decision-making in highly complex tasks, and early results indicate they can catch money launderers with unprecedented speed and efficiency.

Intel notes that total financial crime is at all-time high, with a UN report stating money laundered globally in one year is 2 to 5 per cent of global GDP, or US$800 billion to $2 trillion.  Another report by the Javelin Strategy & Research  states that in 2016 alone, approximately 15.4 million consumers were victims of identity theft or fraud, resulting in US$16 billion in losses.

“Intel Saffron’s mission is to minimise the time and effort it takes to reach confident decisions,” says Gayle Sheppard, vice president and general manager of Saffron AI Group at Intel.

“We accelerate the path to decision by surfacing and explaining patterns in data with speed, precision and accuracy. The amount of data that banks and insurers collect is growing at massive scale, doubling every two years.

“While the quantity of data is growing, so are the types and sources of data, which means today much of the data isn’t queried for insights because it’s simply not accessible with traditional tools at scale.

“Investigators and analysts will depend on transparent AI solutions to meet the ever-growing demands of consistency and efficiency from a business, regulatory and compliance perspective.”

Related reading: The outliers’ roadmap for building the data-driven enterprise | Insights from Katarina Kolich and David Thomas of Bank of New Zealand

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