Everyone has heard about Artificial Intelligence (AI), whether in terms of robots taking over the world in your favourite sci-fi movie, driverless cars transporting you from A to B or even something as ‘simple’ as using Apple’s Siri function. Whilst most people think mass adoption of AI is a way off from now, it’s already had a huge impact in many different ways, most of which the average person is oblivious to.

Dan Hooper, CEO of Piccadilly Group

One such place is the finance industry, which has been investing a huge amount of finance and resource in technology for a while, as it tries to fend off the challenge from FinTech businesses across the world. In banking specifically, the majority of uses for AI are in mid-level, rather than customer facing or operational roles which is why people can be forgiven for not seeing the impact it has had,  however it’s safe to say that this will change over time as AI becomes more “customer facing”, and ultimately more consumer orientated.

Changing role of middle management

One of the biggest areas of growth for AI in the banking sector is the use of “bots” which use natural language processing to integrate with legacy or external systems, collating and presenting data based on the user’s role and context, and even talking to multiple humans to ensure actions are completed.  Some people may already be well accustomed to the use of chat bots, and we’ll see them take more prevalence to replace the need for administrators and middle management roles.

As chat bots advance, they’ll start to be exposed directly in a ‘face-to-face’ role with customers. In call centers for example, people are being directly replaced by the implementation of chat bots. A recent Forrester report suggests UK banks will start implementing these bots over the next 2 years and is a clear indication of how AI will start compete with jobs.

We will begin to see AI replacing the process of having low level work completed by high paid personnel using similar techniques like chat bots.  By 2020, Piccadilly Group aims to replace mid-management level roles in some banking IT roles using AI.  By using AI for human-to-human mid-level management roles, senior management is then able to focus on the more complex strategic problems.

 

Automated trading

Another change we’ll see in banks is the use of Autonomous agents. These are algorithms which act on behalf of a human and are the most well publicised use of AI in the banking industry today.  In the form of algorithmic trading, banks are using AI to track market patterns and to quickly and reliably react to them. This could mean huge cost savings (and gains) for banks getting it right.  A recent report by Thomson Reuters estimates that algorithmic trading systems now handle 75 percent of the volume of global trades worldwide and this figure is predicted, by those in the industry, to grow steadily.

For autonomous agents to be successful in the banking world, they need to have the ability to perceive the world as it pertains to their area of responsibility, to be able to predict the outcome of actions with some success, and to be able to take actions independently.  Their ability to learn also relies upon their ability to observe the actual outcomes from actions they have undertaken.

One of the drivers for all the attention around AI in the banking sector at the moment is its ability to increase transparency, accessibility and standardisation of data.  For instance when analysing data about publicly traded assets, “training data” is widely available and in a standard format.  This makes it possible to build and train an algorithm which can make predictions as a human, execute transactions, observe results and learn over time.

Other examples of AI exist in the systems banks use to provide an objective and unbiased view, for instance monitoring natural language communications between staff to ensure compliance, or detecting fraud from transaction data.

 

What about consumers?

At the moment however, all of the current focus is very much on the enterprise and the benefits AI can bring to banks.  From a consumer perspective however, change is definitely still coming.  Currently it would be hard to implement an autonomous agent that could manage your personal day to day finances with a large range of financial bodies.  This is because the autonomous agent has to understand how to talk to each bank separately (and the bank has to spend money to make the data available).

The implementation of the CMA Open Banking decision last year can change all of this, allowing tech firms to access your old data and make transactions on your behalf. This will completely change the financial industry and increase competition across the world in an unprecedented way. By using AI, autonomous agents will be able to study your behavior and offer advice and personalised experience.

Whilst we are a way off this yet, it’s clear to see that AI is set to make huge waves in the banking industry, and whilst most consumers can’t see the changes being made already, it’s only time before a more customer facing revolution occurs.