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

IBM Combines Algo Risk Service with Managed Data to Deliver Cloud Risk Analytics

Subscribe to our newsletter

IBM has combined its Algo Risk Service, a cloud-based risk offering acquired with Algorithmics in 2011, with cloud managed data services to deliver IBM Algo Risk Service on Cloud, a risk analytics solution that transforms upstream and downstream data to make it available for portfolio and enterprise risk modelling.

The service is offered as a multi-asset class managed risk service on cloud and can be deployed in a variety of ways to meet user requirements. For example, the software element of the service can be installed on premise and data management can be sourced from the IBM cloud. Alternatively, data management and product modelling, including simulation and valuation, could be put in the cloud, with data aggregation and risk modelling on premise.

Dr Andrew Aziz, director of research, financial engineering and on-cloud solutions at IBM Risk Analytics, explains: “Algo Risk Service on Cloud gives clients more transparency around risk modelling. Clients have a choice of market data vendors to use with the service, but with the inclusion of data management they have greater ability to drill down into the data. Full data transformation means they can use a hybrid model in terms of where the software and data reside, but still have an accurate and transparent view of risk across the enterprise.”

In addition to Algo Risk Service on Cloud, IBM has introduced Algo Risk Service Risk & Financial Engineering Workbench on Cloud, essentially a sandbox that allows users to drill down into the risk analytics and tell IBM how they would like it to change the production environment in the IBM cloud. On this, Aziz comments: “This hybrid solution provides a balance of cost of ownership and flexibility, allowing clients to use the cloud, but also the workbench, to specify their own production set up. About a quarter of Algo Risk Service on Cloud users are evaluating the workbench to achieve more transparency and flexibility.”

In terms of cloud solutions for risk reporting, and to give clients a range of options from static to customised reports, IBM has restructured existing cloud services to deliver Algo Risk Reports on Cloud. This allows users to submit portfolios for risk analysis using an IBM risk framework and for preconfigured reports to be returned. The reports are designed to meet regulatory, investor and investment manager requirements. IBM also offers customised risk reports and active investment reports providing risk information on demand.

Subscribe to our newsletter

Related content

WEBINAR

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

Date: 8 July 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes 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...

BLOG

Private Markets Growth Exposes Asset Servicing’s Infrastructure Gap

By Toby Glaysher, Chairman, FINBOURNE. Asset servicers face a paradox: winning business in the industry’s fastest-growing segment whilst discovering that growth erodes rather than enhances profitability. Private markets represent both strategic opportunity and operational crisis, exposing fundamental limitations in infrastructure built for a different era. When growth creates problems The expansion into private credit, infrastructure...

EVENT

Eagle Alpha Alternative Data Conference, Fall, New York, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

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...