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

A-Team Insight Blogs

Bloomberg Eases Data Access and Reduces Costs with Enterprise Access Point

Subscribe to our newsletter

Bloomberg has responded to customer calls for easier access to data with Enterprise Access Point, an online platform that provides normalised reference, pricing, regulatory and historical datasets to Bloomberg data license holders. Following the launch of the platform last week, we caught up with Gerard Francis, global head of enterprise data at Bloomberg, to find out more about the service and its potential going forward.

He says: “Enterprise Access Point responds to customer challenges of understanding what data they have already licensed and what data would be useful to them, and normalising the data – we do that for them. The platform also makes data directly programmable for developers and data scientists.”

Francis describes Enterprise Access Point as a managed service and notes that it makes no changes to the company’s data license model. It uses open technology standards to encourage adoption, covers all data except real-time data, and is based on the Bloomberg cloud, allowing clients who are permissioned to pull data directly from the platform’s website. Francis comments: “For existing clients, data is easier to access and integration and normalisation costs are reduced, if not completely eliminated. For new clients, the platform makes data very accessible very quickly.” Qualifying cost reduction, he says the industry norm is that every dollar spent on data requires a further $5 to $7 dollars to make the data ready to consume. Enterprise Access Point reduces that cost.

By pre-preparing data, the platform allows users to browse quality data online, examine the metadata, trial sample datasets prior to acquisition, and immediately put them to use. If a user is not licensed to use particular data, the top 10 rows of the data can be accessed to give the user a feel for whether it could be useful and whether to subscribe for the data.

For business users, access to the data is provided by a RESTful API. Francis suggests use cases including improved risk management.

For developers and data scientists, data from Enterprise Access Point is available as CSV data frames and supports multiple technologies including Jupyter and Python Pandas. For professionals leveraging artificial intelligence (AI), the data is also available in a graph format. Web developers using the service can benefits from Bloomberg’s RESTful Hypermedia API, which allows URL consistent data to feed directly into an enterprise’s software components, including machine learning tools.

With historical datasets covering the past 10 years, Francis notes potential use of the platform by not only data scientists, but also quants and compliance teams working on Fundamental Review of the Trading Book (FRTB) regulation.

Matthew Rawlings, chief data officer in Bloomberg’s enterprise data department, says: “Having access to deep data history is critical for any investing or business governance strategy based on data science insights. By providing consistent data feeds along with history through API protocols, Enterprise Access Point allows scientists to apply data models with greater confidence and efficiency.”

Enterprise Access Point initially offers Bloomberg data, including some alternative datasets, but this is expected to change over time as more and different data is added to the platform.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: How to organise, integrate and structure data for successful AI

25 September 2025 11:00am ET | 3:00pm London | 4:00pm CET Duration: 50 Minutes Artificial intelligence (AI) is increasingly being rolled out across financial institutions, being put to work in applications that are transforming everything from back-office data management to front-office trading platforms. The potential for AI to bring further cost-savings and operational gains are...

BLOG

Survey Highlights Challenges in Investment Research Data Amid Rising Demand for Systematic Strategies

The growing adoption of quantitative and AI/Machine Learning (ML) techniques, alongside the rise of systematic investment strategies, has elevated the importance of investment research data, according to a recent Bloomberg survey of over 150 quants, research analysts, and data scientists. The survey, conducted during a global series of client workshops, identified data coverage, timeliness, and...

EVENT

Data Management Summit New York City

Now in its 15th year the Data Management Summit NYC brings together the North American data management community to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...