The latest big idea in machine learning is to automate the drudge work in model-building for quants
The bank has a number of projects using emerging technologies, one of which optimizes the process of detecting price anomalies.
As part of its automation move, Charles River will also offer MarketAxess’ automated fixed-income execution capability.
The already-developed bot is now awaiting incremental testing before it goes into production within six months.
The Japanese bank has already automated handwritten form processing and is experimenting with AI to make use of its unstructured data.
Confluence provides asset manager clients with automation capabilities for financial and regulatory reporting amid growing pressure and shrinking industry-wide headcount.
The first rollout of the offering is geared toward smaller and new brokers looking to outsource their back-office tech.
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These new models sidestep Black-Scholes and could slash hedging costs for some derivatives by up to 80%.
The company is leveraging AI to make investment suggestions and dig out sentiment from spoken announcements.
As global banks seek to promote trade finance as an investable asset class to the buy side, the sector’s lack of technology and data infrastructure have come to light.
The firm is developing machine learning models internally to optimize the reconciliation process and detect price anomalies.
The RFQ model is part of a growing trend towards electrification in the repo markets.
ISDA's Common Domain Model (CDM. 2.0) aims to standarize regulatory reporting and bring greater automation to derivatives trading.
A failed ballot for a Bloomberg-backed identifier reveals the enormous consequences of industry tendencies toward complacency and cost-cutting.
Bond.One is aiming to introduce distributed-ledger tech to solve issues associated with fragmented fixed-income markets.
Traders in Europe face rising data acquisition costs and increasing regulatory reporting pressures argue that a pan-European consolidated tape is long overdue.
Assuming that automated artificial intelligence holds the key to unlocking fragmented datasets, the absence of standardized models coupled with regulatory concerns remain barriers to adoption.
The combination of the two technologies is bearing fruit for firms struggling with legacy architectures, but education and talent remain tough obstacles to overcome.
The event specification module will allow for a common DAML library that references machine-executable trade lifecycle events.
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Using the DTCC’s central trade manager platform, Bangkok Capital Asset Management can automate its post-trade process with almost 2,000 counterparties in 52 countries.
Bloomberg users can now access Bombay Stock Exchange data via a faster and more accessible format.