PARTNER CONTENT
By AssetMetrix
While significant effort is put into managing the digital strategies of their portfolio companies, private equity managers should not forget about managing their internal processes and data flows. Significant value can be created by focusing on data management across the investment life-cycle.
Here are specific examples of current data handling challenges encountered by asset managers in private markets, creating duplication and unnecessary reconciliation effort, as along with quality issues with investor reports and investment analysis:
Data sourcing complexity – Data is sourced from a variety of sources and origins
Inconsistent presentation and calculation formats – Diversity of presentation and calculation formats – lack of uniformity in how performance, risk or other KPIs are calculated and presented
Reference misalignment – The absence of alignment on key references, such as investment IDs and Fund IDs, adds complexity to consolidating information from different sources.
Unstructured data formats – Data is often stored in unstructured formats like PDF documents and spreadsheets which makes data extraction and analysis very difficult and time-consuming.
Data, in its raw form, may not necessarily afford significant value. Overcoming these obstacles often proves to be both arduous and costly. Therefore, it’s crucial to reflect: is the effort truly justified? What advantages, and tangible benefits can arise from implementing effective internal data management practices?
Gaining process efficiencies – By working from a single and validated point of reference, thereby avoiding duplications and requirements to reconcile data in different spreadsheets, which frees up resources in the investment teams
Improving output quality – Consistent output information if reports/analysis is created from a reconciled and consistent source; ESG reports align to financial reports; values in investor and regulatory reports can be traced back to fund accounting numbers and are calculated consistently
Generating new insights by data analysis – Using the data to identify patterns; enhance the data with external sources … employ ML-based applications to further analyse the data
Consistency and stability of the process, specifically for eg risk management and regulatory reporting, where reliable data sources are key for regulatory and contractual compliance
Nonetheless, the initial investments and continuous efforts required to unlock these advantages should not be underestimated, potentially imposing significant overburden on the capabilities and resources of smaller and mid-sized General Partners (GPs). A prerequisite requires an initial investment in developing processes and tools that facilitate the establishment of a comprehensive data store. This includes the provision of data capture and reporting tools, along with the implementation of an effective process management environment.
In addition to setting up the infrastructure, it is crucial to gather data from various sources, extract relevant data components, and consistently input potentially reformatted data into the data store. A simpler and quicker way to create these benefits is to partner with AssetMetrix, an experienced partner, that has ample experience in creating and operating such a platform consisting of the following components:
Data warehouse – a centralised data repository that captures data from various sources in a granular and consistent way – between data deliveries and across the layers of the investment structure
Consistent calculation and reporting standards – reliable definitions of how values are calculated, agreed and standardised presentations
Data extraction and capturing services – efficient data collection, extraction and capturing through the use of RPA tools, machine-enabled data extraction from documents and low-code a applications for data transformation or data delivery interfaces
Data governance processes – defined standards for data handling, reference data values, and data access, including compliance and regulatory reporting requirements
Data Quality Assurance – to ensure data quality through input validation and reconciliation procedures between data sources and across the investment structure
Application Processing Interface (API) layer – for providing data from the data store and making it consumable by process management applications, reporting & analysis tools, or an integrated investor portal application
Data reporting and analysis toolsets – Make the data sourced from the data store digestible by multiple end users in a way specifically relevant to them.
Integration of ESG data collection and reporting tools – As one example to enhance the data collection with other external data which may be required to support investment decisions.
Take advantage of this collaboration through reduced implementation and operational expenses, accelerated time-to-market, and the expertise of seasoned implementation teams. Furthermore, leverage the capability to customise essential services to precisely align with your distinct requirements and specifications.
In the words of one of our valued clients: “AssetMetrix has created a data platform as a single source of truth for us, which has become an integral part of our value chain. Dealing with an expert who not only understands the complexities of the private capital market but at the same time is flexible and solution-oriented has made this partnership a success. An indispensable offering giving us the data quality and operational flexibility which we require!”
