Improving client experience with the help of a few billion data points

December 18, 2020
Tony Cyriac, Chief Data & Analytics Officer, discusses how Schwab is bringing the best of technology and people together to serve clients.

Data science is changing our everyday lives, from how we shop to how we get news or decide what shows to binge. At Schwab, our focus is figuring out how to provide the best of what technology and people can bring to our clients’ experiences. Data is a big part of that. Data can help improve not just online digital experiences, but also personal, one-on-one interactions.

We caught up with Tony Cyriac, Chief Data & Analytics Officer, to find out exactly how Schwab does this.

Tony, in layman’s terms, what does your team do?

TONY: We’re focused on improving the client experience by harnessing the power of data. It’s one of the key drivers of a broader digital transformation process taking place across Schwab. Through our centralized data and analytics teams, we support almost every business unit and function. It’s a pretty cool mission and an exciting time to be doing this work.

How is your work improving the client experience today?

TONY: We look at every interaction a client has with Schwab to understand their unique needs. That requires coming up with a way to organize billions of pieces of data, and then turn that data into insights about how we can make the investing experience easier and more accessible. We developed a patent-pending algorithm to help us do that, and we’re proud that it was recognized by The International Institute for Analytics with the 2020 Award for Excellence in Analytics

A good example of what the algorithm enables is data-driven call routing. If a client attempts to conduct a wire transfer online but then calls the Schwab service line, we know what they are likely to need and can instantly route them to the right service team for help.   

There’s also the scenario where that same client doesn’t call in. He or she stalls the transaction midway online to search for help. We see that and can proactively prompt a chat offering to help.

The same algorithm might detect that a client has been browsing a particular topic online, but they don’t need help right away. We can share that information with our field support teams – in the branch and call centers – so the next time the client contacts us we can help.

There is also Schwab Assistant, an artificial intelligence (AI)-powered assistant on our mobile app. In this area we’re using natural language understanding and other data science techniques to be able to recognize clusters of requests on similar topics and get better at proactively helping.

What makes Schwab stand out?

TONY: Both scale and expertise make a difference. We focus on developing best-in-class financial services offerings, and we have the scale to quickly develop and innovate according to our clients’ needs – which we know based on data.

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I think there’s something to be said for how all the different parts of Schwab work together toward a common purpose – serving clients – and we complement one another in interesting ways. We get data inputs about every facet of our clients’ experience with us, not just their actions but also their feedback. Our Client Easy Score, for example, is a way that we survey our clients to understand how easy various investing experiences and interactions with Schwab are.

- Tony Cyriac, Chief Data & Analytics Officer, Charles Schwab

The core of our work, though, is how we organize, connect, and analyze data across billions of data points from our client interactions. This is certainly not easy when you consider that our digital properties that capture this data are constantly evolving and the data can look different from yesterday to today. However, the algorithm we have developed can dynamically adapt and has led to some really good results.

Where is this all going, and what do you think clients can expect in the next three-to-five years?

TONY: I’m glad you framed it in terms of client expectations because “through clients’ eyes” is our north star.

We start with desired outcomes and work back to see how our data and data science can help us get there. We want to improve people’s financial lives in many of the same ways you’re seeing take shape in other industries. The way we monitor and take care of our health through digital tools and feedback, for example, can be modeled for financial health.

I believe there is a digital transformation underway that clients will feel profoundly over the next few years, and we’re excited about the possibilities ahead of us.

How do you balance the expectation for better and smarter service with concerns about privacy?

TONY: For many companies there’s a tension between anticipating client needs through personalized experiences and making sure not to compromise privacy and trust. But we have several head starts there.

For one, clients already trust us with something very precious – their money. We treat, value, track and guard their data the same way.

There’s also a track record. For decades we’ve demonstrated that ethics are part of our culture. We’re among the most trusted financial services providers for a reason.

Of course, it’s not enough to say we take data protection and privacy extremely seriously. Businesses must show it, and that means a whole new level of transparency about how, when and why data is used and the ability for clients to adjust and manage their data preferences as they go. Brands have an obligation to educate consumers on this topic, and we’re all in on that.

(1220-ONHE)