Blog

In a crowded world where active equity strategies increasingly look alike, machine learning’s potential to deliver genuine differentiation as well as mass-customization make it an invaluable tool for investment managers.

Demystifying the role of machine intelligence in stock selection.

While the phenomenon may seem contained to a handful of stocks, we believe there are broader ramifications for active managers to navigate.  

Special needs planning is an emerging issue expected to become critical in the future; today, plan advisors have an opportunity to take the lead in addressing this concern with their clients.

Voya’s Equity Machine Intelligence team aims to take emotion out of the investment process to deliver alpha that is uncorrelated to more traditional equity strategies.

Separating signal from noise with natural language processing techniques.

Plan sponsors see barriers to retirement preparedness as key challenges to participants, and see decision-making support as essential to overcoming those barriers.

The underperformance of value stocks over the past decade has many practitioners wondering when - if ever - valuation factors will work again for active stock selection.

Sponsors likely will recognize the importance of financial wellness but may not understand the cost-benefit analysis of such programs.

Voya’s approach examines the benefits of incorporating alternatives in target date funds by integrating within glide path design critical elements such as risk premia, skill premia and excess returns relative to fees.