Chief financial officer, TD Ameritrade
Can you give us a feeling for the size, scope and direction of TD Ameritrade?
We currently have 6 million clients, predominantly in the United States, and that number grows by a few hundred thousand a quarter. Our clients do in excess of 100 million transactions a year, from trades to deposits and withdrawals, which generate a huge volume of data. We’re on a constant search for more granularity and smart analysis as a way to adapt our business strategy. But it really starts with a huge push into big data.
We hear a lot about the difficulties—technologically, culturally and otherwise—that come with trying to share data across departments. That must be especially true for a company like yours that has done so many acquisitions over the years. How integrated are TD Ameritrade’s various departments?
It’s true, Ameritrade has grown through a series of acquisitions of online brokers, and those operations have been merged into ours. That can create some back-office issues. Our systems do work well, but could be done better. Now, we’re trying to streamline the back-office and some of the front-office operations, too—the client-facing pieces, for example—to develop one merged, interconnected system.
What will be the benefits of a more integrated set of processes and systems?
We are trying to become more Amazon-like in our approach, with targeted recommendations – the “if you like this, you might like that” kind of offer. That requires us to spend a ton of money on the front-end client. One example is in geo-targeting our customers. If we know they live in a specific zip code, we can target appropriate marketing materials to them. This is where we need more agility to determine what data is relevant and to analyze it in order to make those offers more compelling. The promise of data analytics is it allows you to be agile in analyzing clients – where they are at with their portfolios, what kind of investments they prefer, that kind of thing. Also, any number of factors can shift trading habits. Data analysis should be able tell us specifically why any of our clients change their habits. It’s complicated, but it’s precisely the type of analysis I want to be able to pull off. This level of data analysis should change our margins, our earnings per share and our overall performance.
What do you consider to be the primary role of finance, and can you describe your department’s relationship to the rest of the organization?
I push the message that there is one version of the truth and that version resides in finance. We have finance people in each function of the business, and finance owns the data. Here’s how it works: The finance people in marketing sit within marketing, and they attend all management team meetings, but they still report to me. These are senior level people. The head of marketing understands that this finance officer is there to help him analyze his business, develop his budgets, run his budgets to actuals, and to create what-if scenarios, too. At the end of the day, I’m going to turn to the finance person in marketing to confirm that the numbers are good. We require that managers be accountable to outcomes and to the data that they ultimately present. By embedding finance so strongly into many parts of the business, we’re also unlocking a lot of data that can drive growth. This has been a sea change for us—learning to liberate the data and not hoard it.
What’s the key to making the data useful?
In our world, the data itself is not enough. You have to tell the story. You have to make the data meaningful. Just having raw data and spreadsheets without answering the question of “what does it mean?” is not helpful.
We drive accountability for information by making sure all schedules have an owner so you know who produced it and can go back to that person for fact checking. Having ownership makes the analysis more proprietary to them and encourages a lot more completeness from an analysis perspective.
The same set of numbers can be viewed differently by a reader that is less familiar with the underlying data set. Accountability for the analysis and story is the key to usefulness.
What is one of the biggest growth opportunities your business sees now?
We launched our mobile trading app a year and a half ago. The volume of our mobile trades has gone from zero two years ago to 4 percent last year. Now, about 10 percent of daily trades are via mobile. The mobile trader is an active trader. We’ve concluded that anyone who adopts mobile will make one more trade per month. That is a big piece of data for us. Do we put a push on marketing and the call-center outreach to encourage mobile trading? Yes. Another fascinating opportunity about mobile is the location data. If you look at the demographics of the mobile trader, you can find similarly profiled customers living nearby and offer them an incentive if they sign up for mobile trading. If people do it and see how easy it is they will continue to adopt.
What is the role of finance in identifying and driving new growth opportunities like mobile?
At TDA, it is mostly the business that identifies the opportunities and generates ideas. Finance assists in scoping project duration, cost, pay back and ROI analysis. Finance is in an assist type of role to help the business identify and prevent scope creep. For example, with mobile we will refine the scope to a specific agenda and not try to solve all problems. Finance is, in effect, the discipline for the business.