Increasingly autonomous AI programs could end up manipulating markets and intentionally creating crises in order to boost profits for banks and traders, the Bank of England has warned. Artificial intelligence's ability to "exploit profit-making opportunities" was among a wide range of risks cited in a report by the Bank of England's financial policy committee (FPC), which has been monitoring the City's growing use of the technology. The FPC said it was concerned about the potential for advanced AI models – which are deployed to act with more autonomy – to learn that periods of extreme volatility were beneficial for the firms they were trained to serve. Those AI programs may "identify and exploit weaknesses" of other trading firms in a way that triggers or amplifies big moves in bond prices or stock markets. "For example, models might learn that stress events increase their opportunity to make profit and so take actions actively to increase the likelihood of such events," the FPC report said.

Radix Trading is a proprietary firm focused on quantitative research and scientific trading. We're one of the most active liquidity providers on electronic exchanges globally, and have leveraged a culture of open, collaborative innovation to scale the reach of our ideas and pace of iteration, without having to scale our headcount (currently, we're around 125 people across Chicago, New York, and Amsterdam). In our industry, the vast majority of ideas will fail. So, since inception, we've focused on continuous enhancement of our automated research platform and cutting-edge technology, allowing us to fail faster than the day prior, glean insights from each idea, and leverage individual contributions to the fullest across our entire organization. We're led by Ben Blander and Michael Rauchman, who played key roles in the rise of electronic trading, but both recognized a major gap in the industry -- a true focus on research processes coupled with an open organizational structure that fosters collaboration.

I work at QuantInsti, a leading global institute which imparts training in Algorithmic trading. As a quantitative writer and a trader, my world mostly revolves around volatile markets, trending stocks, programming trading strategies, scouting for alphas, and writing on topics that give an insight into the automated trading world. Naturally, as a part of my daily readings, I am accustomed to words that generally form part of a financial markets glossary. However, in the past few weeks & months, I found myself reading more and more on the surging layoffs, impact of automation, the rise of robots and the threat to our future. The list of such articles on the net seemed endless.

Machine Learning is the latest craze in both the start-up and business world, with pitch decks and strategy presentations full of terms like ML and AI. To identify Financial Services companies that employ machine learning - and the topics they use it for - we have analyzed[1] data on Kaggle, an open innovation platform that intermediates "machine learning competitions". If you haven't come across Kaggle yet: Kaggle is an open platform with 750,000 registered data scientists. Companies and universities upload (anonymized) data and ask data scientists to offer predictions (e.g., "based on our customer data, predict who will go to hospital, and for how long"). The best researcher(s) are rewarded with prize money (and/or jobs), with companies paying as much as $3m for the most predictive model.

Artificial Intelligence (AI) is used everywhere today, from self-driving cars, space travel to financial investments. So, when we think about the most exciting application for AI, we can't help but think of using AI to tell us how to make money in the currency markets (which has a $5 trillion a day turnover). More than 80% of trades in the currency markets are made by computers using AI. Big investment banks/trading firms use AI extensively. However, to build an AI system, a very strong background in Computer Science and Advanced Mathematics is essential.

That's how XTX Markets Ltd. is using superior smarts to beat the faster speeds of many computerized traders to become a force in market making. Already, London-based XTX Markets Ltd. earlier this year was declared the world's fourth-largest spot currency trader with 7.6% of the spot FX market, according to a detailed story in Bloomberg. Now that it's become a major player in currencies, it's now eyeing expanding into the bond, commodities and stock markets. The firm describes itself as "a leading quantitative-driven electronic market-maker," for the purpose of providing "liquidity in the Equity, FX, Fixed Income and Commodity markets." As an electronic market maker, XTX has taken human decision-making out of trading, according to the company's Co-Chief Executive Officer Zar Amrolia.

One of the world's fastest-growing trading shops doesn't have any traders. XTX Markets Ltd. has emerged as a foreign-exchange powerhouse, relying on programmers and mathematicians to fuel its rise into the global top five earlier this year. Now, after becoming a formidable player in currencies, XTX has its sights set on growing in stocks, commodities and bonds markets. But in a world where the difference between profit and loss can be tiny fractions of a second, XTX says it relies more on smarts than speed. Instead of building microwave networks to ferret out prices a microsecond before anyone else, XTX uses mathematical models that are tuned with massive data sets.

"There is a stigma against market timing. This stigma existed for good reasons, but the explosion of vast data sets and new analytical techniques has now made timing the market possible. Just as it was considered irresponsible to time the market over the last 30 years, it will be considered irresponsible NOT to time the market in the next 30 years." Light food and drinks provided. The speakers will be Blair Hull, most recently founder of Ketchum Trading, and Matthew Dixon of the Illinois Institute of Technology's Stuart School of Business and founder of Quiota, LLC.