AI is more likely to “augment” human jobs than to replace them, an industry expert has claimed.
But how exactly could the banking sector be affected by the development and advancement of AI?
Specialist Banking asked industry professionals what key innovations they predicted could take place as a result of AI and whether this could lead to huge job losses for the banking sector as a consequence.
How will AI change the banking industry?
“The capabilities of AI have the potential to radically change the way banks operate,” said Paul Clark, CTO at Tandem.
“The data a customer generates from their day-to-day banking activity can [be] used by algorithms to determine what a customer is planning or how they interact with their finances and the [algorithms] can offer personalised help.
“You could say we’re heading back to an era of personalised, proactive banking where you never need to check your balance and you can trust that you have a financial adviser who you can trust [to keep] an eye on your finances and offer fair, proactive help.”
Alex Park, digital director at Metro Bank, believed that the principal strength of true AI was pattern recognition.
“One area where we will see this have an impact in the next five to 10 years is likely to be in smart authentication – for example, responsive authentication strength based on real-time risk assessment – and pre-emptive fraud detection.
“In addition, AI is likely to have an outsized benefit in back-end operations.
“For example, it could start to help identify order in unstructured data and lead to better customer outcomes [such as] speech parsing to route customers to the right specialist, pulling payments request details out of emails and effecting the payment.”
Ryan Lester, director of customer engagement technologies at LogMeIn, commented: “Over the next few years, areas that seem novel today, like chatbots, will soon become mainstream.
“Much of the highly repetitive work will be shifted to AI and human-based interactions will be focused much more on high-value consultative services.
“Those services will also become more reliant on AI, where they can become more specialised and personalised to that customer.”
“Modern machine-learning techniques can help banks minimise loss and predict trends with increasing accuracy,” according to Xavier Fernandes, analytics director at Metapraxis.
“For example, in the lending market, machine learning can help banks to spot deviations in expected behaviour of the loans on their books of business far earlier.
“By flagging deviations sooner, firms are able to take the actions necessary to price for risk appropriately and minimise credit loss of badly performing credit products.”
Meanwhile, Carlos Somohano, big data evangelist at WHISHWORKS, mentioned that fraud prevention was one of the main areas in which banks were investing.
“Machine learning (ML) and deep learning (DL) – both offsprings of artificial intelligence – are being used to improve security by using algorithms to compare vast amounts of data from many different sources and assess the likelihood of a transaction being fraudulent.”
“Credit and insurance underwriting will be impacted, as lenders and insurers are using machine learning to process credit lending and insurance applications faster, and in a cost-effective manner, without diluting risk assessment standards,” added Rahul Singh, president of financial services at HCL Technologies.
“The key here is accuracy, scale and speed, with machine intelligence proving to be far superior to humans in analysing massive volumes of consumer data.”
How will AI affect jobs in the banking industry?
“…I believe that AI is more likely to augment human jobs than to replace them,” commented John Everhard, director at Pegasystems.
“For example, workers can be slowed down by schedules overloaded with low-value work.
“In response to this, businesses are turning to AI and robotic automation software to reduce costs and increase efficiencies by automating high-volume and repetitive tasks.
“Employees are freed up to focus on adding greater value and delivering better, more authentic services.”
Samantha Seaton, CEO at Moneyhub, believed there would be bumps along the way when it came to AI adoption in the banking industry.
“…The key is rigorous testing, learning from mistakes, and making sure that consumers are properly protected.
“As AI becomes more widely adopted, this will free up staff to offer their specialist services to more people than previously possible because of the high expenses involved – a win-win for all involved.”
“[AI] will lead to some roles being replaced with newer ones in an organisation,” added Vincent Powell, data and AI MU lead at Avanade UK.
“Most jobs in the industry will change, job tasks which are primarily responsible for handling and processing data in every form will ultimately be replaced by automation (failure to do this will be a major competitive disadvantage).”
Stathis Vafeias, head of machine learning at AimBrain, concluded: “As with any new technological breakthrough, there is an amount of negative speculation about AI taking jobs and creating mass unemployment.
“But this is not necessarily the case.
“Technology – even advanced technology, such as deep learning and artificial intelligence – requires human vision and creativity.
“They rely on past data, but cannot assess and prepare for the impact of macro factors as, say, changes to political climates or economic or social flux.
“So, while the simpler tasks may be automated, there opens up a huge opportunity for people to become the architects of change using AI.”
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