Case Study: Clovis Point Capital
Case Study: Clovis Point Capital
The application of data analytics technologies such as artificial intelligence and machine learning hold great promise for private equity firms. They can be vital for accelerating portfolio company exit timing and returns.
90% of private equity firms believe that advanced technologies such as AI will transform the industry.
We agree, wholeheartedly!!!
We worked with Clovis Point Capital to provide a web-based, machine learning recommendation engine that assists them with deal sourcing and due diligence after sourcing a deal.
Business Challenge
Enable an analyst or associate at a private equity firm to use the same data sources to both source prospective deals and to carry out the due diligence process faster, without compromising accuracy.
Transformation
Results
A more comprehensive list of prospective deals in a fraction of the time, with due diligence assistance
Producing a promising set of deals in the private equity business is not an easy task.
Fitting the investment criteria just isn’t enough, in many cases.
Carrying out due diligence without automation is not an easy process, either.
Epochal is using the immense computing power of Machine Learning (ML) to extend the effectiveness of human endeavors in the private equity business without supplanting the judgment of business development professionals. Our recommendation engine produces a list that analysts and associates may then use as a solid foundation for their deal-sourcing and due diligence processes.
Role of Data Science in PE Life Cycle
Take the next step
Schedule a call to learn more about how Epochal Technologies can help you benefit from AI, ML, and data analytics solutions.