About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Alveo DIY Data Modelling Supports Faster Onboarding of New Data Sources

Subscribe to our newsletter

Alveo has responded to market demand for reduced cost of change and faster turnaround when onboarding and operationalising new content in areas such as pricing, security master, ESG, and corporate actions, with new data modelling and onboarding capabilities in its Ops360 platform.

The capabilities allow data analysts to graphically model, onboard and maintain new data sources directly from within Alveo’s Ops360 user interface, enabling them to achieve operational efficiencies. Ops360 was initially released in March 2020 with a focus on enabling business and operations users to easily browse, process and validate financial data.

Neil Sandle, Chief Product Officer at Alveo, says: “The new capabilities enable end users to more rapidly onboard and more easily maintain integration with data sets, which cuts time to production and cost of maintenance. Most changes in data vendor offerings come down to additional attributes and these can be easily handled by data analysts without the need for a data processing engineer. New loaders and new versions of data loaders require loading of only metadata changes.”

The new capabilities in Ops360 are powered by Alveo’s underlying Business Domain Model Service and built on Alveo’s microservices architecture and containerisation that was released last year. Alveo is also using the capabilities in its customer operations to accelerate change management, improve data governance, and as the basis for an intelligent exception handling process.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The ROI of Data Trust: Quantifying the Business Value of Data Observability

Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...

BLOG

EU AI Act Puts AI’s Underlying Data Problems In The Spotlight

By Sarva Srinivasan, Global Head of Strategies at NeoXam Americas Another important part of the EU AI Act has come into play – with Article 50 introducing transparency obligations for certain AI systems, requiring organisations to disclose when users are interacting with AI. Now much of the discussion around these requirements has tended to focus...

EVENT

RegTech Summit New York

Now in its 10th year, the RegTech Summit in New York will bring together the RegTech ecosystem to explore how the North American capital markets financial industry can leverage technology to drive innovation, cut costs and support regulatory change.

GUIDE

Regulatory Data Handbook 2026 – Fourteenth Edition

Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...