Helios enhances its Suite of Customized Investment Models with ML

Helios, pioneer of the Insourced Chief Investment Officer (ICIO) model, created to equip financial advisors with the necessary investment models, analysis tools, and support to increase scale and efficiency as well as communicate with more confidence, announced the implementation of machine learning to its suite of bespoke investment models. This marks a significant advancement in the models’ ability to respond rapidly to dynamic market conditions.

Machine learning will enable Helios to process and rapidly analyze an extensive array of real-time data sets. This advanced technology enhances the firm’s investment models, enabling them to adapt to changing conditions and thereby seek to minimize downside risk.

“We are excited to usher in a new era of precision and adaptability to the wealth management industry, marked by the addition of machine learning to our customized investment models,” said Jason Van Thiel, managing director of product at Helios. “With this technology, our models gain the ability to rapidly process vast amounts of data, adapt to fluctuating market conditions, and identify key trends with a level of precision previously unattainable. The goal is to empower advisors and investors to navigate the dynamic marketplace with unparalleled efficiency and consistency.”

With machine learning, Helios can work beyond traditional constraints, efficiently incorporating hundreds of data series across its models. This expanded capability allows the solution to process thousands of trading and market signals monthly, filtering down to those exhibiting the highest predictive patterns. Ultimately, this approach aims to drive more successful client outcomes through a consistent and adaptable investment strategy.

This latest development follows another recent enhancement to the Helios Tools platform, which allows advisors using Helios the ability to selectively participate in scheduled rebalances of their chosen models according to their preferences.

“Integrating machine learning into our models has transformed our data processing capabilities,” said Chris Shuba, Helios founder and CEO. “”It enables us to analyze impactful portfolio data with unprecedented speed and accuracy, focusing on the most pertinent information. This allows advisors to tell a more dynamic story to clients when selecting and reviewing their investments, with the potential to drive better client retention and seek more consistent investment outcomes.”

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