Finance increasingly relies on data & energy-intensive tech
Published: 01 Nov 2022
Author: FINTECH Circle
As Europe experiences its worst drought in over 500 years, the physical impacts of climate change and the need to reduce the emissions that create it have never been more apparent.
At the same time, the price of oil and gas has skyrocketed, emphasising the importance of energy efficiency and shifting rapidly to renewable energy sources.
In this new landscape, financial service and technology companies are joining the growing list of businesses making net zero emissions pledges.
While on the surface these industries seem low impact compared to sectors like manufacturing or transportation, their growing use of high-performance computing and rising data-intensity are increasing their energy use – and therefore emissions.
Artificial intelligence (AI) is one such data-intensive technology which is now being used extensively.
It is utilised to streamline and optimise processes across financial institutions, such as quantitative trading and financial risk management.
It has provided new ways to meet customer expectations for smarter, safer and more convenient ways to access, spend, save and invest money, for example by analysing data to make better product recommendations and powering chatbots to interact with and guide customers online.
According to the survey in The Data Barometer Report 2022, two thirds of respondents said AI is the technology that will be most vital to their future growth, with ML the second most selected at 42%.
“AI and machine learning have hugely impacted our data and storage needs. We now need expensive hardware to store hundreds of terabytes of replicated data.”
Simon Weston, CEO, ICON
Richo Strydom, CTO of Crown Agents Bank, a UK-regulated wholesale bank focused on payments and FX, uses AI in three ways.
“The first is transaction screening, and there it has made a big difference in the manual interventions that we need to be involved in. The second area is transaction monitoring, so fraud monitoring, etc. And finally, we use it for the automation of manual processes using robotics. These are tools that we will be heavily investing in the next few years to automate more of the manual processes that we have today.”
According to Forbes, 70% of financial firms are using ML to predict cash flow events, adjust credit scores and detect fraud2, as demonstrated by PayU, a payment service provider to online merchants.
“We increasingly use artificial intelligence and machine learning, most heavily in our credit business where our credit decision models are fully data-driven and AI-enabled,” said Simon Gotsch, Chief Risk Officer at PayU. “But we’re also using them more and more in payments, for fraud prevention and other optimisation challenges.”
Blockchain, selected by 30% of survey respondents as being vital for their future growth, is also used to increase security and efficiency.
By digitising the entire lifecycle of transactions, it makes governance more transparent and reduces the risk of fraud, decreasing processing times and cutting the risk of human error.
This diminishes overall counterparty risk and therefore lowers capital requirements.
The benefits for financial institutions can be huge. According to Jupiter Research, blockchain will enable banks to realise savings on cross-border settlement transactions of up to $27 billion by the end of 2030, reducing costs by more than 11%.
The increased use of these technologies has resulted in an exponential growth in data processing and storage requirements.
In the next three years, over a third of survey respondents predict an increase of at least two times, with half of that group expecting an increase of more than five times.
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