A novel NLP application built on a Google transformer model can help predict ratings transitions
If the prototype is put into production, delivery of corporate actions data for dividends could be reduced from up to 24 hours to 15 to 30 minutes.
The data vendor has deployed machine learning across its ETF and fund screening datasets, and plans to interoperate with other big tech firms in the future.
Machine learning could help with loan decisions—but only if banks can explain how it works. And that’s not easy.
High-frequency data such as human mobility data and plastic shipments can help investment professionals understand the post-pandemic economic reopening.
Socially responsible investors are putting their money where their mouth is—in ever-increasing amounts. With insatiable demand for new datasets and analytics to support these strategies, it’s not surprising that every data vendor wants a slice of the ESG…
Wei-Shen and Tony discuss the trade-offs between privacy and remote working and some of the concerns app interoperability could bring about.
While some technology vendors say video communication surveillance can help monitor serious compliance breaches, others see such data as a source of additional contextual information.
A long-time AWS client, Finra is using a combination of AWS tools and its own knowledge graph to generate better search results.
While the Biden administration is already targeting environmental issues with early executive orders, Anthony says that it’s financial giants that will have the greatest effect on ESG investing in the near-term.
Companies like Ice are looking at ways to help municipal bond investors gain transparency into a historically opaque market.
The company is consulting with buy-side and sell-side clients on how its newly developed GK Research Bot can best solve their research and information overload woes.
Mary-Catherine Lader says that the asset manager is building out new modeling tools to help users better understand how the decisions a company makes today can affect their performance in the future.
WatersTechnology looks at how 10 different firms are embedding machine learning algorithms into their platforms and tools.
This year, natural language processing came to the fore in capital markets, helping firms of all kinds parse huge, unstructured datasets.
The deal reflects the broader trend of market participants pursuing scale to create true front-to-back trading and data environments, which may signal a trading platform acquisition in the future—though the IHS Markit acquisition may face regulatory…
The solutions are designed to allow firms to query data and build models more effectively without breaching global privacy rules.
The news sentiment and analysis specialist wants to help banks tap into the datasets they sit on every day, but don't yet possess the capabilities to use.
Instead of waiting for data quality to be sufficient to power AI models, those at the cutting edge are building models to bridge the gaps in the data, and apply it to more sophisticated use cases.
The asset manager is teaming with a vendor on the project, which will first be used for equities trading before moving to corporate bonds.
A summary of some of the past week’s financial technology news.
Officials say the new product will enable firms to aggregate and correlate the data required to fulfill trade reconstruction obligations within seconds.
IHS Markit uses Google’s transformer-based model BERT and a combination of classification and extraction techniques to determine what the documents mean and summarize them.
The managed services and consulting firm will look to roll out these new components to its CLM platform in August.