About two years ago, 29-year-old Samuel Dalsimer opened his first personal investment account.

The New York-based public relations manager initially considered traditional investment management services such as ING and Allied Bank, where he would have sought counsel from professional financial advisers. But many of his friends were using software applications — often called “robo-
advisers” — designed to provide automated financial guidance.

Though he was wary of online banking — particularly when managed by small companies with whom he was unfamiliar — Dalsimer eventually signed up for Betterment, an online financial advisory service based in New York.

He said the system is easier than working with a traditional human adviser; he checks Betterment once a week either on his smartphone or his computer. It notifies him when he receives dividends, and measures his progress toward savings goals — he’s now trying to make a real estate down payment. If he’s lagging behind on goals, it might recommend he adjust his deposits or tweak his investment strategy. Betterment takes a management fee of between 0.15 and 0.35 percent of balance, pro-rated for the year but charged each quarter.

Although the jury is still out whether such services can outperform traditional advisers, a growing number of tech companies and financial firms are betting that Dalsimer is part of a larger market — young investors willing to trust computer programs with their finances. (Betterment’s more than 30,000 users have an average age of 36.)

(Christopher Serra/For The Washington Post)

Fueled by venture capital, Betterment aims to combine market data with algorithms that adjust to a user’s investment behavior. Boston-based Covestor lets users automatically tie their own portfolios to that of a portfolio manager of their choice; both are Security and Exchange Commission-registered investment advisers.

In May, investment management firm Morningstar acquired District-based HelloWallet, which also runs an online personal financial management service relying heavily on user behavior, for $52.5 million.

HelloWallet “lets us go beyond just recommendations like ‘these are the investments you should invest in’ ” said Brock Johnson, president of retirement solutions for Morningstar’s Investment Management division. Analytics let the company predict user behavior months ahead of time — if a person seems a candidate to take a loan out of his or her 401(k) account, for instance, Morningstar’s system can advise them on the trade-offs

Unlike human financial advisers, software applications can combine market data with large volumes of behavioral data, said Betterment’s director of behavioral science, Dan Egan.

“In broad strokes, consumers don’t naturally behave well when it comes to finance and investing,” he said, noting software applications can also rapidly assess a user’s investment tendencies and adjust accordingly.

In some cases, Betterment’s software can identify when investors are “market timing” — attempting to predict the best time to buy and sell stocks, often in search for short-term profits. According to Betterment’s historical data, ­market-timing does not always produce the best long-term results, Egan said. So when a Betterment user’s behavior suggests a tendency toward market timing, the service might send a message encouraging a change in strategy.

When viewed in aggregate, user behavior data can help sites such as Betterment refine its recommendations. In one case, Betterment’s data scientists discovered that newer investors tend to log in to the site more often than experienced ones.

“That also means they’re going to perceive more risk in their portfolio,” he said, adding that the more investors check, the more risky they feel their investments are. Betterment can use log-in data to adjust messaging, based on a user’s risk perception.

The financial tech trend is attracting more than just start-ups. In the past few months, IBM’s Watson Group — the company’s nine-month-old business dedicated to commercializing its supercomputing system — has been developing applications for the financial sector. Watson’s technology can process natural speech and mine large volumes of data to find answers to queries.

“If you look at the characteristics of financial services, it is data intensive. What makes Watson relevant are industries that are information intensive, [where] timed decision-making is critical to the outcome,” said Watson Group Vice President Steve Gold.

Still, Watson’s current financial applications are limited. In July, IBM designed its first direct-to-consumer application for the United Services Automobile Association, which provides financial services to military members and their families. The application can process financial documents to guide military personnel through certain questions, such as how to interpret the GI Bill. In January, Singapore-based DBS Bank agreed to use Watson to provide advice to its wealth management clients.

IBM is still beta-testing software that would help Watson adapt to individual user behavior or gauge a person’s personal risk tolerance, Gold said. IBM’s ultimate vision in which a consumer can have a conversation with Watson about investment decisions, while Watson churns through market data, blogs, news articles and social-media platforms for hints about market direction, is far off, he said.

And until they can gauge human sentiments, though, software applications won’t be able to fully replace human financial advisers, Gold said.

“If you’re talking to someone, you can hear it in their voice — are they excited or are they worried [about a financial decision]? . . . Those are sensory functions, and the human-to-human contact provides an added dimension.”