Asset owners are increasingly turning to taking asset management functions in house as a way to improve control and decrease costs. But when you insource, you create unique needs. Managing and making sense of the mountain of available data is a significant challenge.
With the right mix of technology and talent, however, asset owners can better understand their data and the performance, risk and other factors that go into managing their investments.
Technological advances can help resolve some of these challenges. For example, multi-purpose systems that combine the functionality of both OMS and EMS can make data management easier. In other cases, they may need in-house talent that can bring disparate data sources together.
In addition, innovation in areas such as artificial intelligence (AI) and machine learning (ML) can help asset owners understand the data they have and free up time to focus on more value-added tasks. These kinds of technologies help asset owners to do more in-house to help align data sources.
While technology is part of the solution, funds—particularly those based outside major cities—also face the challenge of recruiting talent with varied data science, IT and business skills. Add to this the complexity of certain asset classes, such as private equity and real estate, that require more investment and operational expertise to manage.
Insourcing makes data optimization a high priority. Working with third parties and external systems can help funds gain the additional expertise they need in areas ranging from regulatory management to investment management in niche asset classes.