The Symphony AyasdiAI team is truly global in nature, with employees spread across the US, the UK, India, and Ukraine. Our team is unhindered by distance, working collaboratively to provide products of the highest caliber. Ayasdi is led with transparency, by CEO Simon Moss, who updates the team on the good, the bad, and the ugly with honesty. While hard work is expected of every team member, it doesn’t go unrecognized and unrewarded, and our employees’ wellbeing, both mental and physical in nature, is a top priority for us.
At Ayasdi, we have been dedicated to helping our clients detect fraud for over 10 years, which has resulted in the accumulation of numerous awards. One of which was being named the #1 Artificial Intelligence Platform for Financial Services by Chartis in 2016. According to the report: “The market for AI in financial services is at a relatively early stage in terms of adoption. Chartis views this as a very important emerging sector, one in which Ayasdi – with its specific focus – is well placed to take advantage. Unlike many other AI in risk players, Ayasdi delivers proof points and practical use cases” (Click here to see the full report).
Our next-generation anti-money laundering applications use our sophisticated machine learning technology to supercharge our client’s transaction monitoring systems. Our AML has also helped global financial institutions, such as Citi Bank and HSBC, slash false positives while discovering new anomalies and cutting costs.
In the late 1990s, Gunnar Carlsson, at the time a professor of mathematics at Stanford, was teaching a branch of mathematics called topology, the study of shape. Gunnar pioneered the applied use of topology to solve complex real-world problems which led to $10 million in research grants from the National Science Foundation (NSF) and DARPA. This grant allowed Gunnar to further study the application of Topological Data Analysis (TDA) to problems of interest within the U.S. Government.
In 2008, based on the success of these efforts, Ayasdi was founded with the help of two other Stanford mathematicians, Gurjeet Singh and Harlan Sexton.
Thanks to the movies and the media, the public understands AI as having grand potential intermixed with enormous risk. The worst-case scenario is that AI takes over the world and either enslaves or kills off humans. It would be easy to dismiss this somewhat emotional sense of the risk of AI as being based mostly on the knowledge gap between
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The purpose of this article is to introduce topological data analysis (TDA) to non-practitioners of data science, which is an underserved population in the information marketplace. Ideally, these non-practitioners have some sort of tie into data science but aren’t practitioners. The motivation for this task stems from the fact that most
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The view of customer risk you have today is not reflective of the actual risk they pose to your firm. Bold? maybe, true? absolutely. Historically banks calculate the risk associated with their customers based on what they voluntarily declare when first opening an account: background, employment, location, money sources, counterparties, etc.
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