AI and Financial Services – How are things going to change?

by Heat Recruitment

by Mike Garrett

Artificial intelligence (AI) is set to change our society in radical and fundamental ways. The finance sector will experience massive disruption.

If you think this is overstating the case, take a look at the Harvard Business Review from July 2017, which confidently labelled AI as “the most important general-purpose technology of our era”.

A general-purpose technology is one which drives economic growth at the most extreme level. Previous examples have included electricity and the internal combustion engine. When you consider the enormous economic and societal changes those technologies have made, you may get an idea of what’s in store.

For the financial services sector the implications are huge. It has been suggested that AI could “fundamentally transform” banks’ finance departments within the next decade, perhaps even sooner.

It’s easy to see how technology could be used to process the large huge volumes of data which banks deal with to generate financial reports and satisfy regulators. These processes are often very formulaic, but currently involve large numbers of people performing low-value-added tasks, which makes them ideal for technology to take over.

But AI has the potential for much more sophisticated work too. Writing in Forbes, Steve Culp suggests, “AI will be used to transform the most central functions in financial services such as intercompany reconciliations and the quarterly ‘close’ and reporting of earnings, as well as engage in the more strategic functions such as financial analysis, asset allocation and forecasting.  AI provides speed and accuracy – the entire reporting and disclosure process, for example, can be undertaken in real (or nearly real) time”.

The advantages are clear – greater accuracy, greater speed, and less work for the finance department at the end of each reporting period.

One of the key differences between AI and the computers we’ve been used to for decades is ‘machine learning’ – instead of coding the system with all the imaginable scenarios it might face, machine-learning AI will learn for itself.

Don’t panic just yet though; the initial learning is generally done during a trial stage and under human guidance and supervision. Only when it’s ready is the AI allowed to operate on its own, for example as a ‘robo adviser’

It also requires an understanding of the individual investor, their preferences and tolerances of risk, for example – in order to develop an investment portfolio for them. The more it does, the more it learns – gaining experience, and remembering what went well, and what didn’t.

Sometimes known as ‘algorithmic trading’, this role seems a good fit for AI because it involves crunching numbers, and we know how good computers are at that.

It’s one of the three key ways Ben Dickson suggests AI is making the biggest inroads in the finance industry. The others are as banking chatbots and in fraud detection.

Chatbots are already being used to engage customers in conversations about finance, either by voice or on-screen message. Banks are starting to use them to handle enquiries or even to advise customers on ways to save money.

Meanwhile, online fraud has risen with the growth of e-commerce, but how to fight it remains a challenge. Declining transactions too readily creates its own problems, but AI can be used to quickly analyse various data points. And with its growing understanding of customer behaviour, it can easily detect whether a transaction is genuine.

The potential uses for AI in finance are only just being explored, but there’s no doubt it will present a range of different challenges – legal, ethical, economic and social. However, there is widespread consensus that it will be enormously significant in shaping the finance sector of the future.

Imagine a financial services sector without that other ‘general-purpose technology’, electricity, and you have an idea of the scale of change that could be in store.

 

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