Intel says the launch of Saffron kicks off the first associative memory AI solution specifically tailored to the needs of financial services institutions and is optimised on its Xeon scalable processors.
Gayle Sheppard, vice-president and general manager of Saffron AI Group at Intel, says Saffron’s associative memory AI simulates a human’s natural ability to learn, remember and reason in real time, mimicking 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.
“Intel Saffron’s mission is to minimise the time and effort it takes to reach confident decisions,” Sheppard says.
“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.”
Intel cites reports that total financial crime is at all-time highs and says, according to the UN, the estimated amount of money laundered globally in one year is 2% to 5% of global GDP, or US$800 billion to US$2 trillion.
And, in addition, in 2016 alone, approximately 15.4 million consumers were victims of identity theft or fraud, resulting in US$16 billion in losses.
According to Sheppard, banks and financial organisations often have 50 or more applications that require use of the same personal financial data, and they want a more efficient way to manage their data, “putting an end to moving and replicating data, which is costly and increases risk”.
Sheppard says banks also want visibility to the unified knowledge across multiple data sources to better serve customers.
Intel says Saffron uses associative memory AI to discover new insights for growing businesses, meeting compliance and regulatory requirements, and fighting financial crime with a suite of features, including:
- Knowledge index: Unifying structured and unstructured data linked into a 360-degree view at the individual entity level, to make sense of the patterns found across boundaries wherever the data is stored. This derives knowledge that is hard to gain with vendor and database proliferation of point solutions.
- Continuous learning: Unlike traditional machine learning methods, Intel Saffron AML Advisor doesn’t require domain specific models nor training and retraining, resulting in improving the time to insight. The financial services industry faces the challenge of “What will be important tomorrow?” In this dynamic landscape, actionable insights realised in hours or days rather than weeks or months is an imperative.
- Work augmentation: Intel Saffron AML Advisor reduces the human cognitive burden through automation thought processes that work with and for the investigator allowing them to focus on higher value activities.
- Compliance validation: Banks collect the data necessary to comply with various regulations, but often must pay non-compliance fines in the billions due to human error or missed deadlines. Intel Saffron AML Advisor explains the rationale behind the recommendations to help banks meet compliance, mitigate fines and reduce countless hours reworking reports.
Intel also announced it had introduced the Saffron Early Adopter Program (EAP) 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”.