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NatWest bank is using artificial intelligence (AI) and data sets to predict what might happen in the sectors it operates within.
The bank is working with Microsoft and AI supplier DreamQuark on projects to simulate potential behaviour in the future in markets such as mortgages and small to medium-sized enterprise (SME) loans.
Using analytics and machine learning technology, NatWest will be able to identify potential risks as well as opportunities.
The capability is being tested against the methods the bank currently uses to predict what might happen in a market in the future.
Kevin Hanley, director of innovation at NatWest, said: “By allowing us to better predict future outcomes, risks and trends, the implementation of this technology could be of significant value to our customers and shareholders over the coming years.
“For the first time we’ll be able to deliver an aggregated, forward-looking view of the world around us, ultimately helping us to build a stronger, safer bank.”
This is the second project that the bank has announced with Microsoft in 2019. Earlier in the year, the bank’s standalone digital lender, Esme Loans, signed a agreement with Microsoft to create a data warehouse combined with AI to support quick decision making on loans. It will also use the resource as part of the development of an AI-driven chatbot which will answer customer questions on the website.
DreamQuark said it offers zero-code (no code) machine learning platforms that consumers and businesspeople can use to create applications without writing any code.
Cindy Rose, CEO at Microsoft UK, said: “AI is the engine of the fourth industrial revolution. It has the potential to fundamentally transform how entire industries operate, delivering greater value to organisations, employees, customers and society as a whole.
“NatWest’s ambition to harness this technology to deliver more sophisticated insights, boost performance and reduce risk is an excellent example of the transformative powers that AI offers.”
Banks operate in a high-risk sector and AI can help to harness huge data sets to make predictions about the future, which can help in decision-making. AI can make predictions more accurate because it can analyse larger data sets. This can also be done at a lower cost than using traditional manual methods.
Investment banks are particularly interested in technology that can improve the accuracy of predictions and help them to make better decisions for the future.
A report from financial services management consultancy Opimas said finance firms in the investment sector spent $1.5bn on AI technologies in 2017, and predicted this would increase by 75% to $2.8bn in 2021.
Opimas also said technologies such as machine learning, deep learning and cognitive analytics will replace 230,000 jobs in investment banking by 2025. The asset management sector will be hardest hit, with 90,000 people being replaced, it said.
This is an opinion shared by the former CEO of investment banking giant Deutsche Bank, John Cryan. In September 2017, he said a “big number of staff at Deutsche Bank will eventually be replaced by robots”.
“In our banks, we have people behaving like robots doing mechanical things. Tomorrow, we’re going to have robots behaving like people,” he added.
Read more about artificial intelligence in banking
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