What are the best ways to use machine learning to improve deal sourcing accuracy?

2 Collect and clean data

The next step is to collect and clean data that can help you find and evaluate deals. Data sources may include online platforms, databases, networks, referrals, news, social media, or reports. You need to ensure that the data is relevant, reliable, complete, and updated. You also need to preprocess the data to remove noise, outliers, duplicates, missing values, or errors. You can use various tools and techniques such as web scraping, data extraction, data cleansing, or data integration to automate and streamline this process.

3 Train and test your model

Once you have your data ready, you can train and test your machine learning model to source deals. You can choose from different types of machine learning models depending on your goals and data. For example, you can use supervised learning models such as regression, classification, or decision trees to predict the outcomes or ratings of the deals based on your criteria and metrics. You can also use unsupervised learning models such as clustering, association, or anomaly detection to discover patterns or segments in the data that can reveal hidden opportunities or risks. You need to train your model on a subset of the data and test it on another subset to evaluate its accuracy and performance.

4 Apply and refine your model

The final step is to apply and refine your model to source deals. You can use your model to generate and rank a list of potential deals that match your criteria and metrics. You can also use your model to filter and screen the deals based on your preferences and constraints. You can then review and verify the results of your model and compare them with your own analysis and judgment. You can also use feedback and new data to update and improve your model over time.

Machine learning can be a powerful tool for financial managers who want to improve their deal sourcing accuracy and efficiency. By following these steps, you can leverage machine learning to find and evaluate the best deals for your portfolio.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?