With fast-moving changes in regulations, aggressive cost reductions and rapid advancements in data technology that have been further accelerated by covid-19, the private equity sector is reassessing the returns on portfolio investments and the viability of planned exit timelines. But companies could be missing a trick on deriving additional value if they do not optimize portfolios’ existing business modeling, cash management and tax structures.
Private equity firms already have to collect a wealth of data for tax purposes – data that could be harnessed to also generate value. Far from only ensuring compliance with various local regulations, meeting regulatory obligations can present new opportunities for value creation.
Historically, collecting and analyzing this data has been both challenging and time-consuming. But developments in data technology mean this is no longer the case.
It’s now possible to automate data extraction from enterprise resource planning (ERP) systems, ensuring quick data collection and accurate mapping to localized tax codes. Machine-learning tools can then be deployed to process huge amounts of data in seconds, rapidly analyzing transactional records at line-item level to propose tax determination.
The resultant data consistency and reduction in errors allows more time for focusing on value-add activities such as strategic planning and business partnering. Insights could also be gained to further optimize the internal data-gathering process itself.
Data analytics can not only examine past events, but predict the future and generate actionable business insights. Key data from PE firms’ ERP systems can be enriched with external sources such as news media. Deploying artificial intelligence could provide insights into the performance of business fundamentals, both quantitative (sales, net income, costs, working capital, cashflow projections, liquidity risks) and qualitative (external trends on trust analytics, sustainability, competitor analysis).
Employing data analytics can help with better forecasting and group cash management, as well as identifying any missed incentives or reliefs. This can be found in multi-jurisdictional corporate income tax return submissions on areas such as operating income, tax losses, tax payments, effective tax rates and book-to-tax adjustments.
Cash and withholding tax analysis provide insights on structural inefficiencies or tax leakages and identify opportunities around alternate transaction flows or holding structures. Analysis of global temporary and permanent differences could highlight tax non-deductions, and the underlying reasons for their existence, to establish if further analysis is required.
Indirect tax return preparation can be automated, alongside contemporaneous data analytics to identify anomalies in tax treatment applied to transactions and any potential VAT savings/refunds or adjustments needed. Ultimately, effective data analysis can improve working capital.
Fiscal authorities around the world are also using data analytics to drive systematic changes, which is why it is imperative to focus on this area.
Tax authorities are increasingly sharing information and launching more tax audits across jurisdictions. PE firms need to stay on top of this, producing consistent audit responses by putting in place and utilizing tax audit approaches. Data technology can provide real-time, centralized visibility of tax audit controversy status, identify trends and wider areas of tax risk, and allow the right support to be implemented earlier to reduce costs and risks.
The need for real-time data and insight is now acute. Its value has increasingly provided a significant competitive advantage for PE firms that wish to safeguard their portfolios’ successful exits. It is time for PE firms to act to get ahead of the game by driving greater value from their compliance data.
Jen Hwang is a partner in the compliance and reporting department at EY UK and Ireland