The past year has taught the world to expect the unexpected. Private equity managers have learnt to be adaptable and nimble in the face of challenging circumstances. However, although no one can predict the future, data analytics and tools are evolving to help managers map potential future risks and outcomes. New functionality is also being considered in view of the growing appetite for private credit investments.
The past year has taught the world to expect the unexpected. Private Capital managers and investors have learnt to be adaptable and nimble in the face of challenging circumstances. However, although no one can predict the future, data analytics and tools are evolving to help managers map potential future risks and outcomes. New functionality is also being considered in view of the growing appetite for private credit investments
Marcus Pietz, Head of Analytics, AssetMetrix, comments: “We are focusing on providing managers and investors with the potential for interactivity within our data analytics function. These solutions will see our clients go from just accepting and receiving the data to being able to interact with and manipulate it in different ways. The refinement of these tools is a key objective for our firm at present.”
These interactive solutions will enable clients to engage with the data they input into the system. They will not only be able to filter it and work with pre-existing calculations; they could also have the ability to add new information into the applications. Pietz notes: “This means the models will react and calculate new outputs on the fly.”
These additional interactive capabilities will enhance Private Capital actors’ capacity to plan ahead. “Through these tools, market participants will be able to be more proactive. They will not only be able to assess their portfolios from a current or past perspective but will be able to consider future planning as well. They can think about components they may want to add to their portfolio and calculate the impact these could have on their investments as a whole,” says Pietz.
Single common methodology
One example is the potential to anticipate future cashflows in light of new deals. The tool can make these calculations based on certain assumptions regarding multiples and time horizons. Although managers and investors were able to make such calculations in the past, the models they used, to date, have been rather ad-hoc and generally required manual set-up and changes before each use.
The aim of a firm like AssetMetrix is to take that potential element of human error out of the equation. Pietz underscores: “We’re trying to industrialise the process around forward-looking analysis, to raise standards and inject a certain level of automation. This also means the models, and therefore the outputs, are more predictable because they are based on a single, common methodology.”
Having these analytical tools hosted on a single platform is also efficient from an operational perspective. “We always take data from one common source. This ensures the same dataset goes into all reporting channels being used by our clients. Further, the resulting output is stored centrally and users can refer back to it with ease if they need to,” Pietz highlights.
The credit question
AssetMetrix is working with several development partners to further enhance the functionality and capability of the tools it offers clients. Pietz outlines the specific work being done: “We are going into a phase of designing the user interface and the functionalities we would like to offer. Another thing we discussed, from an operational perspective, is the ability for users to collaborate and communicate within the tools itself. This means one expert can work on a dataset and have a colleague continue working from a chosen point. This notion is a function which is highly relevant in this new world of virtual collaboration.”
The past years have also seen private debt rise in appeal among institutional investors. The firm is looking to help support this development. “The asset class is growing in popularity as investors are drawn to risk/return profiles which are hard to find in traditional spheres,” Pietz observes, “We are currently developing an interactive tool which allows analysis of credit portfolios. This would include simulating external influences on portfolios and stress tests. The tool would allow its users to see how changes in interest rates would impact their portfolio. They will also be able to visualise the number of defaults a portfolio would face under various circumstances and how cashflows would react.”
This functionality is still in development but Pietz is confident clients with private debt investments will be particularly satisfied once this module is rolled out. Although Private Capital professionals are highly competent and capable of building these models themselves, using an outsourced service can save time: “It is a bit trickier to model this internally on a case-by-case basis because credit instruments can be complex. There may be some simple cases but some structures can include options or other special features,” Pietz highlights, “Putting this into one framework that can do everything makes it easier from a quality control dimension as well because it’s a centralised functionality and they don’t need to worry about these calculations anymore.”
Other asset classes like infrastructure and real estate are also part of AssetMetrix’s mid-term roadmap. “These are more specialist areas and our goal is to further expand into these spaces and offer more tailored solutions and tools to cater for managers and investors in these fields,” Pietz stresses.
Data standardisation
The tools the firm plans to launch will save clients manual work and minimise operational burdens. This is aligned with the firm’s overall objective.
Pietz highlights how AssetMetrix aims to keep data requirements low: “Clients who are just starting to use analytics often may not have data collection and management set up in a way that is coherent. Therefore, from our end, we try to keep data requirements sensible. Our tools and models are robust and they don’t necessarily take a lot of effort on the data input side.”
This is particularly relevant in the private capital space where data tends to be scarce. “Our challenge lies in getting the right data and building sensible models to help managers and investors generate analysis and insight which will be useful to their strategy,” Pietz says.
Industry trends have also been supporting this objective. Standardisation of data has been growing over the years. This development at an even greater scale is what will lead to greater penetration of data analytics among Private Capital firms. Pietz advises: “Industry participants should promote this kind of standardisation when it comes to data sourcing as it would benefit the industry as a whole.”
Marcus Pietz, CFA, Head of Analytics, AssetMetrix
Marcus Pietz is Head of Analytics and has been with AssetMetrix since 2018. Having been involved with Private Capital already during his studies and internships, Marcus started his career in the area of credit risk modelling in 2013. At AssetMetrix, he is applying his more than seven years of professional experience in data analysis, modelling, and programming to the suite of analytical models developed in-house. Marcus earned his master’s degree in Finance, Accounting, and Taxation at University of Bayreuth and is a CFA charterholder. Together with his team, he is currently focusing on introducing interactivity to the analytical solutions offered to AssetMetrix’s clients.
