Front Office Technology Transformation Projects Require a Specialized Project Management Approach

Technology transformation projects are inherently challenging – from determining how a specific firm compiles their data and technology, to innumerable decisions to be made, data files to validate, functionality to configure and test, to go-live events. When technology transformation projects impact front office teams, a highly specialized project management approach must be employed to minimize disruptions to uber time-sensitive front office revenue-generating productivity while keeping the project on schedule.
While the definition of ‘front office’ differs among organizations, here within the front office references a few distinct groups: Portfolio Management, Trading, Quantitative Analysts and Risk Managers. These front office groups fulfill critical roles involving time-sensitive initiatives. They represent investment management firms’ strategy and intellectual capital, and directly generate revenue for investment management firms. Their skills are the costliest; therefore, their time is at a premium. This paper shares the keys to executing this specialized, non-disruptive approach to managing front office technology transformation projects.

by Elizabeth M. Colebrooke, Principal

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The Investment Performance Technology Landscape, 2020

What are the key differences between investment performance measurement systems in the market? How are these tools evolving to better meet industry needs? These are important questions for firms considering significant investment in a new or upgraded toolset. Meradia has first-hand knowledge of many of the top systems in the market accrued from direct implementation efforts and have combined this knowledge with product strategy to provide insights on where the industry is progressing and to highlight disrupting themes. This is useful for investment performance professionals as a precursor to an RFP and/or an aid to firms considering a system change.

by Laurie J. Hesketh, CIPM, PMP, Managing Director

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Risk Statistics in Performance Calculators: Suitable and Scalable? – Part 2

Investment performance calculators have witnessed steady growth in functionality during the past couple of decades. Leveraging huge data management platforms that contain exception management and workflow capabilities, calculators provide upstream integration capabilities. By expanding calculation breadth to include attribution effects and risk statistics, they are knocking on front office doors. As vendor consolidation occurs and performance systems endeavor to deliver one-stop solutions, it is important to understand design mechanisms related to each functionality that drives system efficiencies. In this paper, we examine returns and ex-post risk statistics.

Refer to Part 1 of this two-part series which lists the subset of risk statistics with which we are concerned and the benefits of calculating these in a performance calculator.

This Part 2 delves into systemic factors that enable efficient computation of risk statistics and why conventional architectures encounter scaling issues.

by Jose R. Michaelraj, CIPM, Senior Consultant

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Risk Statistics in Performance Calculators: Suitable and Scalable? – Part 1

Investment performance calculators have witnessed steady growth in functionality during the past couple of decades. Leveraging huge data management platforms that contain exception management and workflow capabilities, calculators provide upstream integration capabilities. By expanding calculation breadth to include attribution effects and risk statistics, they are knocking on front office doors. As vendor consolidation occurs and performance systems endeavor to deliver one-stop solutions, it is important to understand design mechanisms related to each functionality that drives system efficiencies. In this paper, we examine returns and ex-post risk statistics.

This Part 1 of a two-part series lists the subset of risk statistics with which we are concerned and the benefits of calculating these in a performance calculator.

Stay tuned for Part 2 which delves into systemic factors that enable efficient computation of risk statistics and why conventional architectures encounter scaling issues.

by Jose R. Michaelraj, CIPM, Senior Consultant

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Design Thinking: How to Integrate Creativity into Data-Driven Business

The financial services industry has always been required to embrace change, whether it be driven internally to control cost and sustain growth or driven externally to address and leverage market conditions. Given the rapidly evolving technology environment, volatile markets and globalization; companies are searching for ways to more successfully innovate to meet these challenges and take advantage of this environment by offering new products and services. To do this effectively, an organization must be able to understand customer needs, identify viable business and operating models and ensure their offering is technically possible and deliverable within the parameters of their risk profile.

By integrating a design thinking approach, organizations can more effectively consider the outcomes for the end users of their systems and processes. What will their experience be like? How do the systems and processes provide value to them? How do the deliverables solve their pain points and/or business needs?

by Daniel G. Foley, Principal

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