Digitalization and Transformation Innovation Hub
Brought to you by WatersTechnology, this Innovation Hub provides in-depth insights on how financial firms are using cutting-edge technologies to make actionable investment and operational decisions, with focus on machine learning, AI, robotics, cognitive computing, automation, data analytics and much more.
Traders in Europe face rising data acquisition costs and increasing regulatory reporting pressures argue that a pan-European consolidated tape is long overdue.
Michael Bodson predicts technology will fundamentally change how the markets work.
By distributing stories prior to performing its full editing process, MT Newswires can give ICE clients several crucial minutes of exclusive advantage, compared to mechanical latency improvements that might deliver mere fractions of a second.
The initiative seeks to create common language around tokens to foster wider adoption among institutional investors.
VMware blockchain and Hyperledger Sawtooth begin support of DAML on their platforms.
The event specification module will allow for a common DAML library that references machine-executable trade lifecycle events.
Firms are pushing their university programs past the traditional internship structure, embedding students and researchers to work on current use cases to deliver solutions to real-life problems. Jamie Hyman reports.
Questions of price discovery and centralized infrastructure point to an asset class that may have to lose its rebellious luster to become more widely accepted.
Giancarlo lauds budget approval from Congress in swansong industry appearance.
The credit derivatives processing facility will go live on the distributed ledger platform by the end of the year.
Digital currency exchanges are using established market surveillance services in a move that steps closer to institutional-level infrastructure.
Introducing WatersTechnology, our new monthly magazine that brings together fintech and data journalism like no other.
Fabrice Silberzan is playing a key role in the transformation of BNP Paribas Asset Management. With his background working across different cultures and various roles, from IT to securities and HR, the opera-loving Frenchman has a lot of lessons to share…
The protocol, which aims to eliminate the need for private keys, will be baked into its new digital asset service.
Development of machine learning and natural-language processing is now turning to languages other than English to keep a better eye on traders and the market. But how easy is it to teach a machine a new tongue?
Lucena will provide a pre-packaged signal based on Wall Street Horizon's earnings dates revision data, for buy-side firms without the in-house resources to analyze the raw data themselves.
The funding will be used to open a research hub in London.
As interest in cryptocurrency trading refuses to wither, despite a bearish year, traders are increasingly calling for institutional-grade tooling from traditional markets to further develop the asset class.
Financial technology and engineering expert Jim Northey will lead the technical committee behind ISO 20022.
As strides are being made to encourage greater institutional participation in the trading of cryptocurrencies, Wei-Shen ponders whether the crypto space will end up looking exactly like the traditional financial ecosystem.
The bank is one-third of the way through a three-year project to re-engineer its data management processes to become a more data-driven business.
At the recent Waters USA event, experts discussed how firms can leverage technology innovation to guide the data digitization process, and where human intervention remains important.
Turning traditional assets into digitally traded data is one of the most commonly cited benefits of emerging technology, including distributed ledgers. But the reality is that the process is far more difficult than it seems.
The physical infrastructure will enable faster connectivity to global locations.
The network provider estimates the global cost of fund distribution could be reduced by as much as $4.35 billion.
WatersTechnology speaks with data specialists from all parts of the capital markets in an in-depth examination of deep learning's impact in finance.