As sovereign wealth and pension funds get bigger, more complex and more competitive, their ability to harness technology is key. The quality, accessibility and analysis of data are taking center stage, helping funds make better investment choices in today's fast-moving global environment.
Anything that makes funds better at picking the best investments among hundreds of opportunities is a huge competitive advantage. This is where data comes in. Some of the leading funds we work with are using data and analytics techniques to:
From what we see in practice, these strategically advanced ways of using data are only possible after asset managers have invested in improving their data's integrity, standardization and accessibility. In fact, these improvements often rise out of companies' responses to changes in tax and regulatory requirements.
Around the world, we're seeing tax authorities in many countries, including Australia, Canada and Denmark, invest in technology to help them assess risk and boost collections. With digitalization, governments can now tax economic activity at the level of distinct transactions. Tax authorities are automating their processes to extract data directly from source documents, such as invoices. They are also considering new forms of taxation of activity in the digital domain.
Looking ahead, we predict tax policy will increasingly favor taxation based on transactional data, such as value added taxes, over taxes on income, which is more difficult to measure.
As tax authorities focus their digitalization toward data and analysis, institutional investors are increasingly looking for technology solutions that can ensure the quality of their compliance data. And for many tax functions, the quality and visibility of tax data is dramatically improving their accuracy and efficiency.
But better tax compliance is only the beginning. As compliance work becomes increasingly automated, tax teams are freed to focus on improving their technology and analytic skills so they can deliver ever more strategic value. And as institutional investors gain control of the data within their walls and confidence in their ability to draw insights from it, they can combine their data with data from external sources, such as market trend analyses and benchmarking studies, and multiply the predictive benefits.
Among other areas, advanced data and analytics has become a crucial component of institutional investors' due diligence practices. As compliance-driven automation and standardization enables richer data and more powerful analytic results, due diligence teams can break down and examine a target's tax affairs more extensively and quickly. This can significantly shorten the deal-making process and enable better decisions.
Data and analytics can also ease post-acquisition planning and integration. At a time of significant tax change and uncertainty internationally, planning the tax-related details and clauses of legal agreements in advance is crucial to mitigate tax consequences, especially for clauses referring to price, contingent prices, liabilities, indemnification and warranties.
Data and analytics are also driving new approaches toward operational due diligence. With these assessments, teams can examine a broad range of investment strategies, including hedge fund, infrastructure, private equity and traditional asset managers. The purpose is to allow investors to understand and challenge key aspects of the target's asset manager, including tone at the top, compliance culture and risk management.
In addition to targets, we see more and more funds using data strategically to create value within their existing portfolios, and to detect opportunities for expanding into new territories or lines of business. By extrapolating trends in a company's transactions, funds can now look beyond investments in single companies to determine how target assets could work others to boost their value across the board. This allows funds to identify and take advantage of opportunities across entire ecosystems.
For example, in analyzing an infrastructure asset like a highway, funds can now consider a host of external data, such as local gasoline sales, time-of-use road tolls and traffic light patterns. This can allow asset managers to spot trends in usage and increases in density, and to see where additional investments in the highway's ecosystem may create even more value -- from road construction and maintenance through filling and repair stations to truck stops, coffee shops, commercial real estate, and other retail or service ventures. In this way, data and analytics can offer much wider view of the entire range of complementary opportunities that are available.
But the quality of these insights is only as good as the quality of the institutional investor's data, so they need to ensure the accuracy, reliability and timeliness of their data throughout the organization. Seizing control of your organization's data is the first step toward harnessing its strategic value. The end goal is an end-to-end data management system that allows funds to extract the right information from their systems, combine it with other sources, establish consistent data policies and leverage user-friendly analytics to reveal opportunities.
In the years to come, we expect it will become increasingly imperative for institutional investors to have a data and technology strategy that provides full transparency and timely access to data across the organization. With an end-to-end strategy in place, funds can boost confidence in their ability to meet their tax, data security and other regulatory compliance obligations, and free their time to focus on more value-added activity in supporting the business.