At Thomson Reuters Text Metadata Services group, we are leading the industry in AI machine learning based metadata products, focusing on NLP and knowledge-graph solutions. Our products organize Thomson Reuters' and Clients own, unstructured content feeding customers with significant insights extracted programmatically from narrative text. We are looking for a talented and experienced Senior Big Data Engineer to add significant capability to our products, Thomson Reuters Intelligent Tagging (TRIT) and Knowledge Graph (TRKG). This position is full time and based at our Singapore office. This role sits within our Financial & Risk ("F&R") business.

New compliance technology such as AI and intelligent tagging has the power to change compliance. Our webinar which brought together in-house experts and external subject matter specialists has shed light on the latest cutting-edge technologies and how they can help solve the many day-to-day challenges faced by compliance professionals across the globe. In today's rapidly changing regulatory landscape, it is critically important for banks and financial institutions to respond to new regulations with agility, while ensuring that the customer experience does not suffer. These dual demands put pressure on compliance departments. Compliance technology in the form of end-to-end controls capable of mitigating a multitude of financial crime risks can help to alleviate this pressure.

AI and quant strategies are nothing without solid fundamentals. As quantamental investing continues to gain traction, Elsen founder and CEO Zac Sheffer considers why human intervention will always be necessary. Investments are continuing to flow into funds that use Artificial Intelligence (AI) to make trading decisions, but in the past few months we've seen just how important it is to still have human involvement and good fundamental reasoning behind these strategies. In February, hedge funds that use AI in their trading processes experienced their worst month ever -- or at least since Eurekahedge created its AI Index to track the market in 2011. Overall it was a poor month for returns with the broader Hedge Fund Research Index falling 2.4 percent.

As a bridge between humans and computers, the use of natural language processing in compliance demonstrates how this branch of AI is adding value across the financial services industry. Natural language processing (NLP) falls under the wider umbrella of artificial intelligence (AI) and essentially uses algorithms to help computers understand the everyday language of humans -- both spoken and written. As such, NLP is a fundamental bridge enabling interaction between computers and humans, and allowing machines to understand commands and input from humans in a seamless and streamlined manner. Once a machine can understand a human's everyday means of communication, the potential to add value becomes almost limitless. The Thomson Reuters Center for Cognitive Computing is constantly researching ways to perfect and advance different areas of AI, including machine perception, reasoning, knowledge management, and human-computer interfaces.

Quant funds are expected to account for US$1 trillion in assets this year. But when algorithms are managing this money, who manages the algorithms? Computer-powered, data-driven strategies have continued their spectacular march towards dominating the hedge fund industry. According to research by HFR, the amount of money being managed by quant hedge funds rose to more than $940 billion by the end of October 2017 and is on course to pass the $1 trillion at some point this year. This is an enormous amount of money being managed by machines.

Artificial intelligence (AI) and other disruptive technologies came under the spotlight in a series of thought-provoking sessions at our annual Financial & Risk Summit in Toronto. This year's event -- "Revving the Innovation Engine" -- brought together thought leaders and practitioners from across financial markets and risk and compliance communities for a full-day series of interactive discussions. It was also an opportunity to introduce members of our #TRFinRiskCanada40 list, which showcases Canada's top social media voices in finance, innovation, and risk. One of the highlights of the summit was the Reuters Newsmaker interview with Geoffrey Hinton, a vice-president with Alphabet Inc's Google, who is often referred to as "the godfather of deep learning." He discussed how artificial intelligence is being used today by internet companies such as Google and Facebook, and also in a wide variety of other industries, from financial services and healthcare, to automotive and manufacturing.

Finding trusted financial news, data and analytics on Thomson Reuters Eikon became even easier during 2017, thanks to a number of award-winning enhancements using AI and machine learning. For financial professionals seeking to profit from trading and investment opportunities, Thomson Reuters Eikon delivers a powerful combination of information, analytics and exclusive news on financial markets. At the core of the financial news offering is Reuters, the world's largest international multimedia news provider and known for independence and trust. Reuters goes beyond breaking news, offering unbiased insight and depth to drive better financial decisions. This powerful news-gathering operation includes more than 2,600 full-time journalists in 200 bureaus.

As wealth managers look to AI for cost or UX benefits, what do they need to know about robo-advice, behavioral analytics or the value of clean data? Artificial intelligence (AI) is increasingly being used in wealth management as the catch-all term for next generation capabilities to attract and retain customers. From personalized portfolio management to customer behavior analytics, the potential for significant UX enhancements and cost reduction is vast. But progress is only possible if there's clean, well-organized data to start with. We take a look at the technological initiatives behind AI and how they apply to the wealth management industry.

Virtual advisors are helping meet the demands of investors who want data-driven insight and a rich, personalized experience akin to Netflix. Cognitive software platforms, which provide the tools to analyze, organize, access, and provide advisory services based on a range of structured and unstructured data, are set to attract investment of nearly US$2.5 billion in this year alone. Additionally, spending on intelligent and cognitive applications is forecast by IDC to grow at an impressive 69 percent compound annual growth rate from 2017 to 2020. Driving this explosion is the fact that more data will be created in 2017 than in the last 5,000 years. And it's expected to increase three-fold from this year until 2021.

A few weeks ago, Jochen Leidner, Director of Research at Thomson Reuters, discussed and dissected artificial intelligence (AI). Leidner offered some case studies, conducted by his team, to demonstrate successful ways of building AI products. However, before getting into specifics, Leidner gave a very brief explanation of what AI is and what it does. "It automates things that we deemed, maybe, not automatable a couple of years ago – if it works, or to an extent." Dr. Leidner, who is also the Royal Academy of Engineering Visiting Professor of Data Analytics at the University of Sheffield, made the point very early on that AI is a tool to be utilized with other forms of intelligence.