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

Rimes Employs Economic Framework to Calculate Benefits of Managed Data Services

Subscribe to our newsletter

Rimes Technologies has developed a framework to help potential customers discover the return on investment, payback time and benefits they can achieve by deploying the company’s cloud-based managed data services.

The framework results from a Economic Impact study commissioned by Rimes to evaluate the financial impact of the company’s benchmark, reference data and data governance managed services on a group of four Rimes customers. Headline figures from a composite organisation based on the companies studied by Economic show benefits of $4.8 million over three years versus implementation costs of $1.2 million, adding up to a net present value of $3.6 million and a 2.9 month payback period.

Steve Cheng, global head of data management solutions at Rimes, explains: “We commissioned the Economic study because we found prospects and the industry at large often lack the necessary insight to fully understand the total economic impact of data management. The buy-side tends to focus on the visible costs of data management, such as software and data vendor licence fees, but there are also significant invisible costs, such as the cost of many people touching data, perhaps rechecking or adding to it, consolidating disparate data sources, managing data quality issues, and failing to deliver data in a timely way.”

Economic looked at costs, benefits, flexibility and risks in its study of Rimes’ customers and included these elements in its construction of an Economic Impact framework for the company’s managed data services. Quantitative measures in the model cover aspects such as productivity, business and data growth without staff growth, improved profitability resulting from less time spent on data and more on new business, and a reduction in third-party service provider costs. Qualitative considerations include data quality, business agility and responsiveness, risk management and governance.

A vice president of investment data management at an investment management firm that was one of the four companies interviewed by Economic as part of the Rimes study, stated: “We chose Rimes because of their focus and what they were able to demonstrate for us – cost, delivery of quality, timeliness, and their ability to customise and construct what we need them to. They turned out to really be the best value on the market.”

A performance analyst at the investment management firm, added: “Rimes allows us to support newer and different products. It allows us to tap into areas where previously, we didn’t have any sort of data or perspective on that market segment.” And a vice president of market data services, adds: “Rimes gives us a lot more flexibility with comfort that we can deliver and freedom from operational concerns, so we can really focus on what the core values of the company are, which are managing money and getting people their data.”

With a framework based on Economic’s methodology in place, Rimes is ready to calculate the return on investment and payback timescale for investment management firms using, or planning to use, its managed data services. Cheng concludes: “Our aim at Rimes is to deliver fit-for-purpose data feeds requiring no additional data management. The framework created by Economic is helping us to have more business focused conversations with prospects and helping prospects to make the business case for managed data services.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Streamlining trading and investment processes with data standards and identifiers

Financial institutions are integrating not only greater volumes of data for use across their organisation but also more varieties of data. As well, that data is being applied to more use cases than ever before, especially regulatory compliance and ESG integration. Due to this increased complexity of institutions’ data needs, however, information often arrives into...

BLOG

Implementing and Understanding Modern Data Architectures: Webinar Preview

The evolution of data use by financial institutions has been accompanied by ever-changing challenges to its management. With technologies such as artificial intelligence enabling firms to prise greater value from their data and to subject it to greater utilisation, a new set of data management practices have emerged. These modern data architectures regard data as...

EVENT

Buy AND Build: The Future of Capital Markets Technology

Buy AND Build: The Future of Capital Markets Technology London examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

ESG Data Handbook 2022

The ESG landscape is changing faster than anyone could have imagined even five years ago. With tens of trillions of dollars expected to have been committed to sustainable assets by the end of the decade, it’s never been more important for financial institutions of all sizes to stay abreast of changes in the ESG data...