By leveraging powerful algorithms and large volumes of data, machine learning can provide investors with insights that would have been impossible to get just a few years ago.

With the help of machine learning, investors can identify patterns and trends in data, allowing them to make more informed decisions when evaluating startups. This can result in more accurate valuations and better investment opportunities.

Machine learning enables investors to identify potential risks and opportunities, giving them an edge over the competition. Ultimately, machine learning is transforming the way investors value startups, and it is likely to become even more important in the years to come.

So, what exactly is Machine Learning and why are investors turning to it more and more to make their financial decisions?

Machine Learning is a form of Artificial Intelligence (AI) that enables computers to learn from data without being explicitly programmed, allowing them to identify patterns in data and make decisions based on those patterns. By using Machine Learning, investors can access, analyse and interpret large amounts of data quickly and accurately, which can help them predict stock prices and identify profitable investments.

Data quality is essential

ML algorithms can analyse larger amounts of data than traditional models, but there are data challenges when applying advanced techniques to investment strategies.

The problem is that financial data is mostly non-stationary and messy. It is far more complex than the data collected for customised ads on Facebook or Instagram.

The financial market has transformed over the last decade because of the increasing popularity of passive and active quantitative strategies.

“Machine Learning continues to deliver across numerous fields.  It now inhabits the intellectual atmosphere, adding diversity of thought in a totally new way which would have been scarcely believable even a few years ago.” Mark Feerick  - Co Founder of This is Run Limited

ML models require clean and well-processed data to generate reliable predictions. Data processing is a labour-intensive and time-consuming step in building ML strategies, and the experience and expertise of the quantitative investment team are essential for making judgments on how to process the data.

The rapid growth of ML

Machine Learning is exploding in the global market, with its estimated size expected to grow from $21.17 billion in 2022 to $209.91 billion by 2029. Its primary use in investor markets is for cost reduction and risk management.

Reducing the bias

Machine Learning can also reduce human bias in investment decisions, as psychological factors or emotions do not influence algorithms and can provide investors with an impartial view of the data.

This helps investors make more informed decisions and increases the likelihood of profitable investments. The great thing about machine learning is that the algorithms can be updated quickly to reflect changing market conditions, allowing investors to stay ahead of the curve.

How entrepreneurs can benefit from ML in their Pitches

VCs can use AI to better understand which data is most indicative of successful startups. This knowledge can help entrepreneurs refine their pitches and adjust their companies’ profiles to better match what AI considers successful startup metrics. This could lead to more accessible capital.

For example, Hone Capital partnered with AngelList to create a machine-learning model that uses a database of over 30,000 deals from the past decade to identify the 20 most indicative characteristics of future success in venture capital investments.

Data like this will benefit investors and entrepreneurs alike. As the use of machine learning continues to grow, it is likely to become an even more important part of the investment process in the future.

With the right approach, machine learning can provide investors with an invaluable edge when evaluating start-ups.