Quant Insight, whose model analyses how macro factors affect asset prices, said the next step in big data will be ability to link increasing amounts of information to practical trading ideas.

Mahmood Noorani, founder of Quant Insight, told Markets Media that humans are not capable of monitoring financial markets due to the big increase in complexity. He said: “You used to be able to monitor just three or four factors but that has increased to 20 to 30.”

The QI framework was developed over six years to collect and cleanse independent data so that it statistically models the impact of a select number of  fundamental macreconomic drivers on the price of a range of assets. QI’s academic advisor is Professor Michael Hobson, Vice-Master of Trinity Hall and Professor of Astrophysics in the Cavendish Astrophysics Group at the University of Cambridge. As an example, Noorani said the QI model was never more than 70 points away from the market for the S&P 500 over the last five years.

“Asset classes have become increasingly correlated , there is more available data and processing power has become less expensive” he added. “The challenge is to be able to use all of this information in practice.”

Noorani  continued that one example of the data being used in practice was when the the Chinese government suddenly devalued its currency in August 2015. The QI model predicted that the biggest impact would be on European basic resources and Stoxx 50 and he said this was found to be correct.

“Last year developed market equities were negatively correlated to real rates,” he added. “In June 2016 our framework showed this had reversed, which was much earlier than other models.”

Huw Roberts, a former senior director in rates sales at Credit Suisse who joined QI this year, told Markets Media: “The first wave of fintech involving finding more data has already happened. We are the second wave which involves useful interpretation of that data.”

As an independent research provider, QI may benefit from MiFID II, the new regulations coming into force in the European Union at the start of next year. MiFID II requires unbundling of research payments from trading commissions. Fund managers can either pay for research themselves from their P&L or use a research payment account, where the budget has been agreed with the client.

“The danger with MiFID II is that smaller firms will be left behind,” added Roberts. “We are seeing huge demand for independent research which they can customise – we are democratising quant research.”

The number of QI subscribers has increased from 15 last year to 85 according to  Noorani.

Last month PwC said the asset and wealth management industry “is a digital technology laggard.” The report, Asset & Wealth Management Revolution: Embracing Exponential Change, said the industry has fundamentally remained the same since the last decade of the 20th century.

However, over the next ten years there will be major changes and technology experts and data scientists will become vital for success across the business

“Technology advances will drive quantum change across the value chain – including new client acquisition, customisation of investment advice, research and portfolio management, middle and back office processes, distribution and client engagement,” added PwC. “How well firms embrace technology will help to determine which prosper in the years ahead.”

For example, alternative intelligence-powered robotic processes will monitor and analyse every public company, as well as other financial and non-financial data. They can also process supply chain analysis and the other new forms of data.

“Already, some alternatives managers are successfully leveraging quantitative strategies and regard themselves first and foremost as technology companies,” added PwC. “We expect this trend to accelerate.”