How The M&A Compass Uses Predictive Analytics to Forecast M&A Trends

Being able to predict market interest, and forecast merger & acquisition (M&A) trends would redefine how M&A professionals gather market intelligence, and one entrepreneur from Singapore is creating a platform to do just that.

Massimo Bellino used his domain expertise in analytical M&A research to create The M&A Compass, a platform which utilizes predictive models to produce unique insights for M&A professionals.

Massimo, co-founder and CEO of The M&A Compass, started the business to provide a breadth and depth of analytics that he wished he had access to earlier for the duration of his 20 year career in M&A

The M&A Compass offers a forward looking perspective by using historical M&A activity data and predictive models. The data solution predicts industry themes, niches and technologies a company will likely acquire or divest in the future.

Needless to say, access to this information will provide a strong competitive edge.

Current Challenges

Manual M&A research methodologies are time-consuming and tedious, requiring individual analysis of companies one-by-one.

Having read books on the use of data science in business, Massimo knew that machine learning (ML) algorithms could replicate manual analysis, speeding up the process to take seconds instead of hours.

Additionally, the use of ML improved the accuracy of the research, as all companies across the market could be analysed in one fell swoop, something not possible manually.

Equipped with M&A domain expertise, and a minimum knowledge of data science, Massimo needed a way to develop his ML models to produce the predictive analytics for The M&A Compass.

"The ideal way to find value is to have in-depth domain expertise and a minimum understanding of what you can do with these new technologies. In my case, I developed a machine learning model to produce predictive analytics for M&A"

- Massimo Bellino, co-founder and CEO of The M&A Compass

The machine learning solution

Massimo had two options to develop the predictive ML models needed for The M&A Compass.

The first of which was to hire a freelance data scientist to develop the models for him, but found it to be too expensive for his proof of concept..

The second option he had was to develop the models himself using an AutoML platform. He considered, but ultimately disregarded a number of options, again due to the prohibitive cost.

That was until he heard about PI.EXCHANGE and The AI & Analytics Engine via word of mouth at a conference he was attending.

"The Engine offers a good value for the asking price and will enable our start-up to develop machine-learning models without the need of hiring a data scientist."

Massimo reached out to PI.EXCHANGE, and with some assistance from PI.EXCHANGE’s in-house data science team, successfully used the Engine to train two ML models on his propriety set of company and M&A data to predict the industry themes a company will likely acquire or divest in.

 "The team was beneficial in understanding what we wanted to achieve and selecting the correct model with the data at hand."

Results and benefits

The two prototype models developed had prediction qualities of 87.59% and 86.37% respectively, as defined by area under the ROC curve metric.

Massimo was happy with these results, as they confirmed the implied prediction ability of his proprietary dataset.

Massimo commented on the easy-to-use UI of the Engine and noted the prediction explanation feature as particularly valuable, allowing him to view the top features that impact the probability result.

"Using the Engine was great, straightforward, and easy to use and navigate."

Wrapping up

Massimo was able to incorporate a unique feature into the M&A Compass, separating it from any other M&A research platform, with some help from the AI & Analytics Engine.

If you’re a entrepreneur looking to incorporate a ML powered feature into your product, reach out to us, and we’ll get in touch with how the Engine can help you.