Numbers add up as Voya Financial uses Microsoft Azure’s data science capabilities for Investment Management

Voya Financial has long had a compelling elevator pitch. It wants to be “America’s Retirement Company®.” Its name is a nod to the fact that, for many people, retirement is about a journey —or voyage—rather than a destination.

The retirement, investment, and health benefits company, which is listed on the New York Stock Exchange (NYSE: VOYA), serves the financial needs of more than 14.8 million individual, workplace, and institutional clients across the U.S. The company registered $7.6 billion in revenue in 2020 and $721 billion in total assets under management and administration as of June 30, 2021.

Offering innovative health and wealth solutions to its millions of customers is central to Voya’s business. As digital technology continues to advance, Voya has been intentionally evolving its strategy to focus on becoming a technology-enabled company that provides holistic and personalized health, wealth, and investment management experiences.

Its strategy relies on technologies such as cloud computing, analytics, Big Data, machine learning, and artificial intelligence (AI) to make smarter investment decisions, analyze market trends, and better understand—and meet—its customers’ needs.

Building data science on the Azure cloud platform

Along its journey, Voya developed an “Enterprise Data Science Team” dedicated to developing and applying AI algorithms and other technologies that will help its business units improve customer service and organizational performance. “Data is pivotal in understanding our customers,” notes Rejeesh Ramachandran, VP, Enterprise Data Science at Voya Financial. “So we built a pipeline of AI and data science use cases within our business processes that will offer greater insight into customer behaviors.”

As Voya advanced on its journey to the Azure cloud platform—to leverage more powerful and flexible computing power than traditional technologies stored on premises—Rejeesh and his team identified a use-case opportunity to support its investment management business. This use case involved Voya’s investment administrative platform that manages approximately $252 billion in assets across fixed income, senior loans, equities, multi-asset strategies and solutions, private equity, and real assets.

As Rejeesh explains, “There was a clear opportunity to enhance the speed and flexibility of the computing tasks and the power of the administrative system itself.”

Rejeesh says the firm considered expanding its on-premises platform to execute the new use case, but decided a third-party service provider was a more sensible option. “We don’t want to maintain a data science platform,” he says. “The data science team’s value does not come from technology expertise, so we don’t want to spend our time or be responsible for such tasks as patching servers. We want to be users of the product rather than managing the product.”

After talking to a range of IT suppliers, Voya did a proof of concept that included Azure Machine Learning, Azure Data Factory, and Azure Databricks. The team decided those were the components it needed to move forward and selected the Microsoft Azure cloud platform. Rejeesh says that was the result of Microsoft having the right mix of technologies with the right user experience—including “agile machine learning”—and previous experience in delivering similar projects.

Collaborating to create an innovative AI platform to support investment management business

The timing couldn’t have been better. Implementing a new cloud-computing platform with built-in machine learning solutions when Voya was already accelerating its cloud migration was ideal. It allowed the enterprise to strategically develop other technologies, such as natural language processing (NLP) and “cognitive” technologies, which are expected to have a significant impact in the next decade.

“Our use case was complex,” says Rejeesh. “There was no template to follow because not many had done this before publicly.” When Microsoft Enterprise Data Science Team approached Voya about the prospect of collaborating to build new machine learning models that address Voya’s emerging use cases, the organization welcomed the opportunity. The project, completed in 2020—during the pandemic—went smoothly.

Rejeesh explains, “We worked collaboratively with the Microsoft team on the project. My contact at Microsoft was amazing—she never dropped the ball. People fell into their roles easily. Everyone understood our common goals, and there was strong cohesion across the team in how we’d achieve those goals together.”

Building better retirements by focusing on investments

Rejeesh adds: “I’m very happy with what we’ve achieved with this project. The Data Science team is moving full-speed-ahead with Microsoft Azure. It’s now our data science target cloud environment, and we are working on moving our data science systems there.” While still fairly recent, Voya is already seeing benefits, adding that the project has confirmed the effectiveness of a cloud-based, agile, machine-learning platform.

Voya’s customers will also benefit from this. “The output of one such project can now be leveraged to enhance Voya Investment Management’s proprietary stock selection models, which will enable our quant team and fundamental analysts to make smarter investment decisions,” says Rejeesh. “By using AI, we are helping grow our customers’ assets.”

Given this early success, the company expects to implement many more projects using the same technology to further improve customer service and investment returns. It’s an example of how Voya is becoming a technology-enabled financial services company and bringing its strategy journey to life.

Collaborating further with Microsoft

“Voya’s move to the cloud, and the use of AI, analytics, and other technologies, is likely to grow considerably from here,” Rejeesh adds. “For example, Voya plans to use Azure Machine Learning to analyze public transcripts from companies’ earnings calls with investment analysts, going beyond simple dictionary approaches.” This capability can analyze the analysts’ sentiment on specific companies and stocks more comprehensively, whether their views are positive, negative or neutral, to help Voya’s investment managers and traders make even smarter investment decisions.

“Improving investment returns could also grow market share and create additional income for Voya, because more investment partners will use the company’s financial investment products due to the AI-powered platforms improving average returns for investors,” Rejeesh says.