What is Artificial Intelligence in Finance?

Have you ever had the experience of being called by your bank to check the validity of a credit card transaction? Did you ever stop to wonder how this happened? Is a human responsible for manually reviewing all your transactions, or is there some kind of technology at play?

Artificial Intelligence (AI) is the technology that powers these fraud detection and security check capability. In fact, AI can analyse millions of customer transactions 24/7, identifying patterns and anomalies that indicate suspicious activity that warrant a security check. This is just one great example of AI being used it the financial services and banking sector. Adoption of AI is rising rapidly and will be a transformative force and fraud detection and prevention is just the beginning. This article will focus on exploring what is AI in the context of finance.

What is finance?

To understand AI in finance, let’s first focus on the term finance which describes a broad set of activities relating to banking, debt and lending, capital markets: basically the process of raising funds or capital for any kind of expenditure. In essence, the term finance encapsulates money and asset management.

To the general public, our understanding of finance is mostly as a part of our everyday lives such as:

· Financial activities: Financial activities involve the inflow or outflow of money. Examples include receiving wages for labour, buying and selling products (or assets), issuing stocks or taking out loans.

· Financial services: Financial services which involve the acquisition of goods during which financial activities take place. An example is the financial service offered by credit card companies when it accepts and transfers funds between payers and recipients.

Financial activities and services are what create the world of finance and therefore money, which is what makes the world go around.

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is an intelligent machine that has the ability to work independently and perform tasks that we normally consider would require human intelligence.  An AI system undergoes a period of learning which involves analysing huge amounts of data. The idea of AI is to let the machine “learn” the best approach to solving a certain problem rather than prescribing the rules that it must follow, as is the case with traditional software. In many cases, a high-performing AI system can make decisions faster and more accurately than a human expert. There are different kinds of AI algorithms and domains that excel at performing different types of tasks. For example, machine learning driven algorithm can quickly quote optimal prices for customers seeking insurance, while reducing cost; Artificial Intelligence could also aid in hiring process by predicting what distinguishing features of applicants are more related to future success. This article will not explore these in depth, but if you’re interested in learning more please visit the Brainpool website and Brainpool blog for various articles about Artificial Intelligence.

Why finance needs AI.

To put it simply “money never sleeps”. The world of finance is constantly moving. Money and wealth are always being created, lost or moving at every second of every day all around the world.  According to Forbes, the world's total net wealth has hit $431 trillion as of June 2021. This figure is growing faster than ever, and we can soon expect the world’s wealth to exceed 1 quadrillion (1 quadrillion = 1000 trillion). With all the money people around the world hold, the amount of money circulating the world could be as much as 40 trillion US dollars.

With that much money circulating in the world, it makes sense to deal with all these transactions as data. Finance has become mostly digitalized and so financial transactions are mostly represented as data. Before AI, analysis of financial data was mainly processed by human eyes and prescriptive, rule-based systems. However, digitalization brought with it an explosion in the amount of data that had to be managed – often referred to as ‘big data’ - and the challenges that come with it: understanding the trends and patterns within data, identifying opportunities to create value and making timely, smarter data driven decisions.” With the amount of data in the financial sector continually growing, the need for increasingly smarter and sophisticated tools to keep pace and derive value became more urgent. This led to recognition of the opportunities and benefits presented by AI:

· Improved efficiency. Latest AI algorithms can fire up to one billion times per second, meaning it can run through information several orders of magnitude faster than human, and with ten-thousandth of the amount of energy used by a human. This means AI driven algorithms could process far bigger data than human with a better precision.

· Reduced costs. AI could free up human labor that was previously devoted to repetitive work. According to a recent study, it is expected that AI can save banks up to US$ 447 billions by 2023. What’s more, AI can save resources wasted on fixing human errors due to its better precision.

· Better service to customers. AI could help improve customer service through many ways like 24/7 chat bot service line, automated financial manager, etc. Customers no longer need to wait for the bank’s opening hours to solve emergencies, and usual wait time on the phone or at the bank queueing could be drastically reduced too.

· More secured banking. Financial organisations could use AI to go through each transaction that customers’ accounts make and keeping all customers’ money safer.

· AI opens up human opportunities. AI excels at repetitive work, freeing up financial professionals to spend less time on administrative tasks and more time on value-added responsibilities.

Let’s revisit the fraud detection and prevention examples and take a closer look at how it works.

Nowadays, particularly in many developed economies around the world, most people have abandoned cash and instead turned to credit cards and online banking. This offers undeniable flexibility and convenience, with the side effect of making finance more vulnerable to cyber security attacks and sophisticated fraud. To combat this, AI technologies have been employed to analyse massive swathes of data and detect irregularities in transactions that may indicate fraudulent activity and prevent them from happening. The time that it takes for a transaction to occur, be assessed as fraudulent and to make the decision whether to approve or decline it happens in a fraction of a second. Humans can’t possibly process and make decision in that time. But AI can – and quite successfully. According to NatWest, they have prevented £7 million worth of false payments by using a machine learning system.

Conclusion

The abundance of data in the financial sector is a core part of what makes AI the perfect partner to drive better services, experiences and value. Artificial Intelligence is a powerful tool and has great potential to transform business models and markets for trading, credit and blockchain-based finance, generate efficiencies, reduce friction and personalize product and services to individuals. AI has given the financial a way to meet the demands of customers who want smarter, more convenient, safer ways to access, spend, save and invest their money.

Written by: Clayton Black and Alex Shen