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

A-Team Insight Blogs

ReferenceDataFactory Unveils Bloomberg Adaptive Client

Subscribe to our newsletter

Data integration vendor ReferenceDataFactory (founded by a team of ex-FTI/GoldenSource people) has launched RDF Adaptive Client for Bloomberg Back Office. The service oriented architecture (SOA)-based solution for integration across Bloomberg Back Office and Per Security is designed to enable standards-based distribution of the data enterprise-wide. This Adaptive Client joins similar offerings for Reuters and Interactive Data sources within the ReferenceDataFactory stable. The vendor can also quickly create Adaptive Clients for sources on demand, due to the fact that there is a separation between the technology and the configuration of data, according to its managing director Andy Dilkes.

Dilkes says the ReferenceData-Factory technology is used by Accenture within its Managed Reference Data Service. Reference-DataFactory is also partnering with LakeFront Data Ventures, the consultancy founded by Dale Richards, formerly of SunGard, and recently bolstered by the hire of other ex-SunGard men Marc Odho and Rob Ord (Reference Data Review, February 2007). ReferenceDataFactory hopes to work with the large data vendors as well as financial institutions.

ReferenceDataFactory’s aim is “to enable the adaptive enterprise”, says Dilkes. “Our solution is a J2EE-based container, enabling you to plug in anything you like. Our intention is not to replace solutions like GoldenSource and Asset Control. We offer configurable adapters for existing databases – our technology could be used to get data into and out of databases like those. We can make an Asset Control or a GoldenSource behave like a service – or we could be implemented in conjunction with JRules from Ilog, for example.” The data management systems vendors are more focused on rules, internal data management and data centralisation than on integration with downstream systems, Dilkes adds. “Often they are built on proprietary technology bases, rather than on open platforms for data integration. The need for integration is obvious: the value comes with getting market and securities data out to downstream systems. Service oriented implementations are inevitable, and this space is ideal for them.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: The Data Office at a Crossroads — AI Governance, Organisational Design, and the Evolving Mandate of the CDO

Date: 28 July 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Who owns AI governance in a capital markets firm – and is the Data Office structured to bear that weight? These questions sit at the heart of A-Team Research’s latest findings, presented here for the first time: the combined...

BLOG

Why Private Markets Need Numbers They Can Defend

By Gareth Hewitt, Founder, LemonEdge. Private markets run on confidence. Performance still matters but investor trust increasingly depends on whether a general partner (GP) can defend the numbers behind it and whether a limited partner (LP) has enough transparency to test and reconcile those numbers for itself. A capital account balance, valuation movement, fee calculation...

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

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...