The AI advantage: How artificial intelligence is revolutionising commercial finance

Bitcoin is the last major blockchain to use the energy intensive mining process that requires rows of energy-guzzing computers. — © AFP

Artificial intelligence (AI) is seemingly everywhere, and the financial services sector is no different. Banks and other financial firms like hedge funds were some of the first institutions to adopt artificial intelligence at a corporate level, while new technological advances and applications mean that AI usage is more widespread than ever.

These new applications promise a myriad of benefits for the firms that adopt AI and their customers, who are interacting with the technology in new ways and opening the door to further possibilities. But how exactly is AI being used to transform the world of commercial finance? Anglo Scottish Finance has provided an overview for Digital Journal.

In terms of important milestones:

Embracing the future?

For those working within financial services, the outlook on AI is mixed. Generative AI – forms of artificial intelligence capable of generating their own image, text or other forms of media – are typically viewed with caution. Here, 45 percent of people working in financial services view generative AI as a friend, though a further 40 percent view it as a foe.

Despite this mixed view, 77 percent of bankers believe that unlocking maximum value from AI technologies will be the difference between successful and unsuccessful banks. Its value cannot be understated.

There are concerns around employment: 73 percent of financial services executives believe that generative AI will take their jobs. Thankfully, those aged 25–34 – who will largely be driving AI adoption forward – feel markedly more positive about AI.

Those concerned about redundancies should not fear – for the present day, at least. At the moment, AI is best used as a supportive, augmentative tool, utilising human input to maximise the tool’s potential. 

Tackling financial crime

Banks spend nearly £219.7 billion each year on tackling financial crime. It is a difficult task, given the sheer number of transactions that must be monitored to weed out the fraudulent ones. International collaboration might be required, and bureaucracy raises further barriers to identifying and preventing these transactions in time.

AI’s ability to digest and analyse huge datasets means it can change the outlook for anti-fraud teams, who can now monitor more information than ever before. For example, high street bank TSB has been utilising machine learning to provide every individual transaction with a score based on how likely is to be fraudulent within milliseconds.

The bank estimates a 20 percent reduction in push payment fraud – where users are convinced to send money to people pretending to be someone else – as a result of the technology.

A human touch is needed here, for predictive AI might be able to identify spending patterns and catch fraudulent transactions before they happen, but a human understanding of why a transaction might have taken place in a certain way is necessary to interrogate individual payments on a case-by-case basis.