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The Evolution of AI in Finance

28th February 2022 |

‘Skynet begins to learn at a geometric rate. It becomes self-aware 2:14 AM, Eastern time, August 29th.’ 

So states the Terminator, the cyborg played by Arnold Schwarzenegger in James Cameron’s epic Terminator 2: Judgement Day, when explaining the rise of intelligent machines. Seeing humans as a threat, the machines fight back, attempting to wipe out mankind. 

In reality, robot assassins don’t roam the street, and the supposed ‘Judgement Day’ – the day the machines launched their nuclear attack on humanity – never materialised (it was in 2021 in the films). Rather, artificial intelligence has greatly benefitted our lives and the business world around us. 

The financial sector has been one of the quickest to adopt new technologies as the benefits to businesses and customers quickly become apparent, and there are no signs of this slowing down. Indeed, it’s estimated that global spending on AI in finance will grow from $50billion in 2020 to more than $110billion in 20241. 80 per cent of banks are highly aware of the potential benefits presented by AI2 and 70 per cent of financial firms are now using machine learning3. 

Machine learning – an application of AI that enable computers to learn from data – is the key to processing the estimated 2mb of data that is created every second, for every single person on earth4. That unfathomable amount of data is the reason we are increasingly relying on vastly wide-ranging systems that encompass everything from chatbot assistants to fraud detection. 

Countless companies are employing website chatbots to streamline their customer service and allow for 24/7 communication, while JP Morgan Chase (in the US) has strengthened its secure reputation by implementing a proprietary algorithm that examines credit card transactions. When a customer makes a credit card purchase, the details of this transaction are analysed by computers in Chase's data centres and are quickly deemed safe or fraudulent, based on customer spending patterns. American Express similarly uses fraud algorithms to monitor the $1.2 trillion of annual transactions by its card holders. 

Businesses, and not just their customers, stand to benefit considerably from these advancements with transformed business models, modernised systems and enhanced offerings. Depending which source you consult, the productivity gains and cost savings for financial services companies as a result of artificial intelligence could be close to $450billion by 20235, even $1trillion by 20306. 

With these potential savings as well as the scope to reduce financial risk, improve compliance, prevent fraud, predict cash flow, improve credit scoring, and much more, it’s no wonder that a radical transformation is occurring across the finance sector. These technologies are increasingly accessible and businesses stand to gain considerably from their implementation.

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