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Bank of New Zealand uses Intel AI to detect financial crime
Posted on 12-Oct-2017 15:39 | Filed under: News

Intel has launched the Intel Saffron Anti-Money Laundering (AML) Advisor, aimed at detecting financial crime through a transparent AI solution utilising associative memory. Today’s launch kicks off the first associative memory AI solution specifically tailored to the needs of financial services institutions and is optimised on Intel Xeon Scalable processors.

 

Intel also introduced the Intel Saffron Early Adopter Program (EAP). This program is designed for institutions whose ambition is to lead the pack on innovation
in financial services by taking advantage of the latest advancements in associative memory artificial intelligence. It allows its members to gain the first-mover advantage over the competition and define the future of associative memory AI in financial services. Expanding upon its existing relationship with Intel, Bank of New Zealand* (BNZ) has joined the Intel Saffron EAP.

“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” said David Bullock, director of Products and Technology at BNZ. “By staying at the forefront of AI, we can help ensure we have access to the latest, innovative technologies that enhance our business.”

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

 

Intel 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 solutions are designed to enhance decision-making in highly complex tasks, and early results indicate they can catch money launderers with unprecedented speed and efficiency.

Total financial crime is at all-time highs. According to the UN, the estimated amount of money laundered globally in one year is 2 to 5 percent of global GDP, or US$800 billion to $2 trillion.1 In addition, in 2016 alone, approximately 15.4 million consumers were victims of identity theft or fraud, resulting in $16 billion in losses.2

“Intel Saffron’s mission is to minimise the time and effort it takes to reach confident decisions,” said 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.”

 

Banks and financial organisations often have 50 or more applications that require use of the same personal financial data. Banks want a more efficient way to manage their data, putting an end to moving and replicating data, which is costly and increases risk. They also want visibility to the unified knowledge across multiple data sources to better serve customers. Intel Saffron AML Advisor uses associative memory AI to discover new insights for growing businesses, meeting compliance and regulatory requirements, as well as fighting financial crime.

 



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