Data Science in Private Equity
Data science technology has rapidly grown exponentially throughout recent years with many industries utilizing it lucratively.
The Private Equity (PE) field is no exception as major investment funds and asset managers are already beginning to obtain and make use of every bit of predictive insight from the data they may collect. In fact, private equity firms utilize data science through 4 major methods that we’ll be discussing in this article.
How do PE Firms Leverage Data Science?
Investment Outcome Prediction → Many major investment firms utilize their large historical track record of deals and investments to create a central company dataset. This dataset is then used by an analytical machine that is able to provide accurate forecasts on the performance of certain portfolios and investments. However, this strategy may be enhanced exponentially through the analysis of a combination of data from several firms to allow for a more accurate prediction.
Anomaly Detection for Investment Screening → Due diligence and screening is absolutely essential in the creation of a PE firm’s portfolio. In fact, before a company can be considered in a portfolio, PE firms utilize both traditional methods of screening investments and newer data science-based techniques. Such data science techniques include anomaly detection algorithms that enable firms to spot both outlier opportunities and red flags by spotting irregularities in their distribution of investments.
Conveying Compelling Stories → Customers are the most important part of a PE firm’s business. Understandably, however, many potential buyers ask many questions in the diligence process. In order to make this process go much more smoothly on both ends, PE firms utilize data and analytics to demonstrate security and instill trust for buyers by conveying a data-driven plan.
Data-Driven Decisions on Exit Strategies → Divesting in a company is a necessary decision a PE firm must make in order to yield returns. Thus, by utilizing data analytics, firms are able to better maximize the potential of a sale with the simplification of relevant data and a focus on real-time insights to identify areas that need immediate attention.
Conclusion:
Each private equity firm manages an assortment of companies within their portfolios. Thus, in order to adapt to specific circumstances pertaining to each company, PE firms must make use of new approaches with data and analytics to provide the necessary tools to address challenges and remain profitable and ahead of the competition.
