Nomura Digitises Wholesale Business
Jez Mohideen, global chief digital officer, wholesale at Nomura said that in five years time between 30% and 40% of the business will operate differently due to digitisation.
The Japanese bank set up the wholesale digital office about one ago. Mohideen told Markets Media that the main remit of the office is to improve the customer experience, increase efficiency, grow revenues and help the firm enter new businesses.
He said: “In the past nine months we have focussed on our data strategy, the use of artificial intelligence and machine learning in electronic trading, setting up labs and investigating digital assets.”
For its data strategy, Nomura has built a data lake as Mohideen explained that a data-centric approach provides the ideal platform to combine the best of humans and machines.
“The focus has been on fixed income in the front office and there have been some tangible benefits from proofs of concept that will go into production in the next six months,” he added. “We expect to expand to currencies and commodities and equities in the next 18 to 24 months.”
Mohideen continued that artificial intelligence has infiltrated trading and will have a strong impact on the wholesale customer experience. “We can use AI to better serve our customers and to analyse markets,” he said.
For example AI trading tools can improve pricing, allow a better understanding of the client base, determine the optimal liquidity venues in different market conditions and reduce slippage.
Last month Nomura announced an investment in AIM2, a venture established by hedge fund Brevan Howard Asset Management which specializes in building AI-powered products for the finance industry.
“Brevan Howard created a tool for the buy side and we have a different experience on the sell side,” added Mohideen. “The partnership allows us to leverage the different skill sets to deploy the technology more quickly.”
Before joining Nomura, Mohideen was a partner at Brevan Howard where he spent more than three years building a new AI and data science group. The hedge fund launched AIM2 in 2015 to use a combination of data science and machine learning to develop a range of alpha investment strategies.
Steve Ashley, global head of wholesale at Nomura, said in a statement: “The AIM2 team has a strong combination of data scientists and capital market experts, and has built an industry leading AI engine that we will use across all asset classes to enhance the client experience and increase market share in flow products. This solution will also form part of our plans to accelerate Nomura’s wholesale digital transformation.”
This week the Global Financial Markets Association and PwC published a report, Technology and Innovation in Global Capital Markets.
The study said four technologies have the potential to transform the banking industry and capital markets: data & analytics; cloud computing; artificial intelligence and distributed ledger technology with banks at varying levels of maturity for each of them. Data and analytics was identified as a priority.
The report said: “84% of survey respondents expected banks to have significantly advanced data & analytics capabilities embedded in five years’ time. These capabilities, alongside increased cloud computing adoption, were highlighted as the enabler for further technologies and operations developments.”
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Almost two thirds of respondents said AI will be increasingly embedded in banks within five years’ time, targeting capabilities such as natural language processing; optical character recognition and trading risk analytics and social networks analysis.
In addition, regulators are likely to begin using AI to monitor and process data from market participants, allowing them to react more quickly to market developments, and design regulation based on highly accurate market assessments.
Nearly all, 90%, of respondents said cost reduction and improving client service were their joint top factor for implementing new technology, with increasing revenue also an important consideration.
“However, one challenge that many banks face is that a large percentage of today’s cost is focused on developing and maintaining legacy technology to meet regulatory requirements,” added the report. “This, in turn, impacts the ability to invest in new technology and innovation; a very real conundrum as it is these same new technologies that are believed to offer alternative solutions which could address some of those increased costs.”
Mohideen said: “In five years time between 30% and 40% of our business may not operate as it does today, especially as non-banks take market share in the wholesale space. You need to adapt fast enough so that you will be in better shape to survive the disruption of the following 10 years.”
The bank can access data science, artificial intelligence and machine learning for new products.
AiPEX with Watson simulates a team of analysts and traders to identify potential investments.
Machine learning models systematically scan newly arriving, anonymized data to identify anomalies.
The Cobalt programme launched in 2018 to help fintechs collaborate with the asset manager.
Users with different skill levels will be able to undertake machine learning and advanced analytics.