Finance actually wants more regulation because of the rise of artificial intelligence fintech in the world's markets

 
Lynsey Barber
Follow Lynsey
Somerset House Opens Major Exhibition Big Bang Data
Source: Getty

The finance world is cautiously optimistic about the future of artificial intelligence and how it can be used, but, there is more work needed on regulating the technology when it comes to world markets.

“Financial institutions have been fined billions of dollars because of illegality and compliance breaches by traders. A logical response by banks is to automate as much decision-making as possible, hence the number of banks enthusiastically embracing AI and automation," said Baker and McKenzie head of financial services regulation Arun Srivastava.

"But while conduct risk may be reduced, the unknown risks inherent in aspects of AI have not been eliminated."

Where is AI most useful?

The law firm's research found more than 400 senior executives working in finance and fintech believe artificial intelligence (AI) will have the most impact on trading, financial analysis and IT over the next three years. More than half also said it will disrupt risk assessment, credit assessment and investment portfolio management.

Retail investment is already adapting to machine learning with the rise of robo-advisers. The UK regulator indicated in March that it felt the technology could be a cost effective way of giving advice and that more work was needed for the Financial Conduct Authority (FCA) to help firms work on it.

Read more: Britain's financial regulator is the first to launch a fintech accelerator

The implication is that machines will be able to spot something humans simply can not when it comes to trading, giving anyone using it an edge over the competition.

"It’s being able to go a couple of steps deeper than you could just by using, say, data in a spreadsheet," said BlackRock Scientific Active Equity Unit senior portfolio manager Paul Ebner.

Speed matters but it’s a different kind of speed than high-frequency trading. For us it’s being able to process a lot of data very quickly and coming up with the right answer that the markets will eventually discover

We’re applying tools to analyse data about companies and using that data to forecast the fundamentals, and then ultimately to forecast their stock returns and construct portfolios around that.

However, people are inherently weary of the risks associated with the unknown of technology, particularly where algorithms are concerned. “If there is a problem with the algorithm. the impact on the markets could be considerable,” said Investment Industry Regulatory Organisation of Canada's market regulation boss Victoria Pinnington.

Risky business

Nearly half of those surveyed were not confident that their organisations understood the legal risks associated with the new technology. Just under a third said they were confident. Despite this worry, six in 10 believe machine learning will enhance risk assessment.

"Data, and the various rules and processes which both enable and regulate access to and use of that data, stand at the heart of disruptive fintech businesses. Even the most advanced and intelligent algorithms and models are useless without efficient, secure and legal access to detailed, accurate and up-to-date data sets," said Baker and McKenzie's Adrian Lawrence.

Regulation

Institutions are seeking greater regulation to reduce their liabilities, but the majority don't believe the regulators are quite there yet when it comes to understanding technology themselves.

“Regulators are woefully under-skilled in AI and need to boost their understanding or risk being marginalised,” said one unnamed respondent to the survey. Almost two-thirds believe existing regulation needs to be improved because existing rules are insufficient.

Read more: These are the hottest 50 fintech companies (and half are from London)

Within 15 years, More than two thirds believe their own jobs will be "substantially changed" by the technology, however, traders and investment bankers are unlikely to become obsolete.

"You still need to use a modicum of market understanding and intuition when you use machine learning," said Saeed Amen, founder of financial consultancy The Thalesians.

It’s not the case that you just put in a system and leave it for ten years; you constantly want to be coming up with new ideas which are correlated as the market changes, and that still requires humans at the end of the day.

Related articles