Why Financial Institutions Must Adopt Artificial Intelligence

Why Financial Institutions Must Adopt Artificial Intelligence

Why Financial Institutions Must Adopt Artificial Intelligence 2560 1920 AMA Team

Why Financial Institutions Must Adopt Artificial Intelligence

In the last decade – and especially in the previous couple of years – our world has undergone a rapid digital transformation and is now more technologically enabled than ever.

One of the most disruptive technologies has been Artificial Intelligence (AI) which has been used in countless industries to improve the efficiency, accuracy and productivity of various processes.

Though hurdles are slowing its adoption among many institutions, one sector set to be transformed by AI is the financial sector. As outlined in a recent report by McKinsey, it’s estimated that AI could provide $1 trillion of value to financial institutions each year

With adjacent industries like big tech dipping into the world of financial services – and digitally native generations such as millennials quickly becoming a dominant market force – traditional financial institutions (FIs) will have to adopt AI technologies to compete.

With this in mind, here are 4 significant ways AI will enhance financial institutions and their future services.

AI can reduce financial crime.

Compared to human beings, artificial intelligence is incredible at detecting irregularities in data, which it does instantly and accurately.

AI can detect unusual transactions and banking activity indicative of fraud in banking. From this point, the cards for that particular bank account can be frozen, and the account owner is contacted about the potentially fraudulent activity, preventing money from being stolen.

Moreover, banking AI can use deep learning to trawl customers’ data and identify possible illicit activities such as money laundering. According to Insider Intelligence, U.S. Bank has implemented AI for this purpose and doubled its output in detecting financial criminals.

AI can automate repetitive tasks.

Across myriad industries, one of AI’s most common use cases is the automation of repetitive, time-consuming, computer-based tasks using Robotic Process Automation (RPA) and similar AI-powered methods.

 

AI is trained to perform tasks ordinarily done by a person – by observing the process and learning the steps needed to complete each task – so that the FI’s workforce can spend time on more valuable work that only people can do, such as client-facing roles. 

In financial institutions, this will result in huge savings, mainly in the wages spent paying people to accomplish tasks that would be more efficiently (and accurately) completed by AI. In the future, we can expect that many “middle-office” tasks will be undertaken by artificial intelligence.

AI can personalise financial services.

When offering financial services to their customers, traditional financial institutions can utilise AI to provide a more personalised banking experience – a feature that has become increasingly important to customers.

For example, based on customers’ spending habits, AI may be able to provide relevant spending or saving recommendations, depending on the customer’s goals. Financial institutions may also be able to offer personalised savings or investment recommendations based on customers’ behaviour and financial goals.

Or, they can alert the customer to any unusual financial activity associated with their account or even detect when there has been a price increase for a regular outgoing cost – such as a subscription – and let the customer know. 

AI-powered chatbots can also be programmed to give round-the-clock financial advice, using natural language processing to determine customers’ needs and respond accordingly.

AI can accurately determine loan risks.

The Harvard Business Review stated that using AI to support the loan approval process may “make bank loans fairer”.

This is because, unlike people, artificial intelligence doesn’t contain internalised bias or prejudice towards certain groups of people – the characteristics of whom shouldn’t affect the kind of loan they’re afforded.

In contrast, AI makes judgements on data relating to a person’s financial history and current financial health to determine the cost of the loan they should be given – and if they should be given a loan.

A study by UC Berkley found that AI-supported loans cost minorities 40% less on average than the rate charged by lenders. 

In the future, we can expect AI to become an integral part of the loan approval and underwriting process to eliminate human bias from the process and distribute loans more fairly.

Though hurdles have prevented traditional financial institutions from widespread AI adoption thus far, FIs must integrate artificial intelligence into their systems and processes.

As we advance, financial institutions must implement a clear strategy for AI adoption, focusing on the comprehensive – rather than episodic – use of AI for specific tasks and processes and updating their systems, adapting to AI collaboration if they want to avoid being left behind by tech companies and tech-forward financial bodies such as digital banks.

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