Nasdaq To Produce More Actionable Intelligence
Nasdaq said that over the next year the exchange operator will be pulling in more datasets and turning them into actionable intelligence that can be used in investigative processes and strategic decision making.
In a report covering seven advanced technologies, FinTech Trends 2018: How Technology is Rewriting the Capital Markets, Nasdaq said it believes that it is one of the early adopters in leveraging behavioral science methods. For example, its Behavioral Insights Platform uses both human factors and cognitive analysis to capture and program certain features into machine learning and AI algorithms which fund managers can use to review portfolio managers’ performance, setting a baseline for normal behavior which can then be monitored for compliance purposes.
Brad Peterson, executive vice president and chief technology and information officer, and Lars Ottersgård, executive vice president and head of market technology, said in the report: “Behavioral science, machine learning and artificial intelligence is a powerful combination. Over the next year, we are looking forward to pulling in more datasets and turning them into actionable intelligence that that can be used in various investigative processes, as well as strategic decision making.”
Ottersgård told Markets Media In February that Nasdaq is focussed on new technologies including the cloud, distributed ledger technology and machine intelligence.
Nasdaq has deployed machine learning technology for surveillance across its Nordic markets. The exchanges in Stockholm, Copenhagen, Helsinki and Iceland implemented machine learning within Nasdaq’s Smarts surveillance technology to analyze data and spot abnormal events, particularly during busy periods such as the market open and close. Last year Nasdaq acquired Sybenetix, a UK that combines behavioral analytics and cognitive computing to provide surveillance for asset managers.
The report said machine intelligence is permanently reshaping the capital markets. For example, 80% of the world’s data is unstructured and machine intelligence technology is expanding the types of datasets that can be used for making trading decisions.
“Given the nature of the reviews performed and the vast data sets that must be digested for proper analysis, the technology allows illicit activities to be detected more effectively than classical, rules-based engines can do alone,” added the report.
Nasdaq expects the use of machine intelligence in the financial services industry to grow as firms invest and explore specific use cases. In addition, cloud technology is maturing, and being embraced by even the largest financial firms.
“In fact, they realize that if they do not invest in it, they are going to be left behind by startups,” said the report. “In addition, the cloud providers are working with the authorities and firms to remove regulatory roadblocks and improve performance to meet financial industry needs.”
Nasdaq continued that the U.S. is leading in cloud adoption, but other regions will likely catch up in two or three years.
The exchange’s technology platform and the services it offers clients via the Nasdaq Financial Framework will be cloud-enabled. The Nasdaq Financial Framework was launched in 2016 so clients can easily integrate business applications, such as settlement, with new technologies.
Cloud providers are beginning to make quantum computing facilities commercially available as part of their service offerings.
“These offerings use a hybrid model allowing certain pieces of a problem to be addressed by classical computers while others that are best served by quantum computing algorithms can be handled by quantum computers,” added Nasdaq. “It is very early days for this technology, but Nasdaq will continue exploring the opportunities it presents and work with our partners to find potential applications.”
The report continued that quantum computing could completely change the trading landscape, but the timeframe is uncertain.
It will also take time for blockchain to reach the end goal of commercial networks or consortia sharing infrastructure. Last year several financial services firms moved from the proof of concept phase into pilots and building of commercial applications.
For example, last year the SIX Swiss Exchange and Nasdaq, together with technology partner Chain, said they will be testing DLT for the Swiss venue’s over-the-counter structured products. Nordic financial services group SEB and Nasdaq have announced a joint project to test a developed prototype for a mutual fund trading platform based on blockchain technology.
“We expect that progression to continue during 2018, with use cases of various sizes put into production with the objective to scale their solutions over the coming years,” added the report.
Nasdaq also expects more activity in cryptoassets as regulated exchanges launch futures and other instruments.
“New ventures are already using initial coin offerings (ICOs) and token issuances for fundraising and for launching new crypto assets,” said the report. “Moreover, it may be possible to develop a settlement coin that can be transferred via a blockchain.”
With Eugene Kanevsky, James Redbourn, and Joanna Wong, CLSA
AI/ML on the buy-side trading desk is a long-term program with short- and mid-term deliverables.
Aiden uses the computational power of deep reinforcement learning to improve trading results and insights.
BondDroid’s AI-generated prices are integrated directly into LTX’s pre-trade analytical tools.
Fintech firm has partnered with Jim Toffey, founder of Tradeweb Markets, to create LTX.