Alternative data holds great promise as a leading indicator of alpha. But in response to firms struggling with the data science aspects of integrating the data, various industry participants are pursuing new initiatives to make it more accessible,…
The combination of the two technologies is bearing fruit for firms struggling with legacy architectures, but education and talent remain tough obstacles to overcome.
As asset managers seek to incorporate ESG factors into their portfolios, they are facing challenges—particularly around data consistency. Some say custodians could offer solutions.
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.
For the final issue of Inside Data Management, Max Bowie summarizes some of the key changes of the past 15 years in market and reference data management.
In February, UK and EU regulators made announcements expected to shed light on the future of data sharing and alleviate some uncertainty post-Brexit, but industry experts say the latest statements fall short of lifting the real burden on affected firms.
As alternative data companies battle for capital and a coveted spot in investment managers’ portfolio strategies, they are turning to bespoke marketing and partnerships to stand out in an industry where firms still struggle with data science resources.
Outsourcing reporting could create technological dependencies that could add to firms’ problems in the future.
The integrated offering will enable Nordic institutions to automate KYC and customer onboarding processes more effectively.
Amelia Axelsen investigates how buy-side cynicism of Mifid II's systematic internalizer regime could be cured through education.
WatersTechnology recaps some of year’s top EU stories.
Processing corporate actions is usually the last workflow to be automated, mainly due to the complexities involved and the weakness of underlying data. Wei-Shen Wong explains how this has changed over the last few years and what challenges remain.
In conversation with Duco CEO Christian Nentwich and Waters editor in chief Victor Anderson, Citi's global head of operations and technology Don Callahan describes his efforts to influence the bank's approaches to managing data quality.
Nearly one year on from the fundamental changes to Europe’s trading rulebook brought about by Mifid II, its overall impact is still unclear. Although experts talk of greater transparency in the markets, it’s had its share of issues, some of which are…
The working group has presented several new methods deploying data analytics specifically to combat money-laundering and terrorism financing activities.
Troubles still plague reported data and transparency objectives, say fixed-income execs.
Equity Kinetics provides an overview of the US equities market for buy-side and sell-side trading and investment decision support operations.
Data experts testify that right now, the financial services industry is uniquely positioned for semantics breakthroughs that will revolutionize the way data is managed, leading to unprecedented payoffs.
With the alternative data industry projected to be worth over $350 million by 2020, it's time to consider whether financial services is on the brink of its own Cambridge Analytica moment or if it is simply time for an alt data ethics evaluation.
AMF chairman Robert Ophèle says data quality and completeness pose problems for regulatory evaluations of Mifid II transparency requirements, and that regulators will review frameworks following Brexit.
Whether through an industry initiative or a delegated acts, a consolidated tape provider will be established in Europe, and the industry could lose out if the regulators dictate the terms.
As they deploy automation to solve regulatory problems, Asian firms are paying closer attention to data’s journey.
Recent studies reveal the prevalence of poor-quality data, exacerbated by increased use of machine learning that allows users to dredge far bigger datasets and identify spurious correlations.