Deloitte Insights and our research centers deliver proprietary research designed to help organizations turn their aspirations into action.

DELOITTE INSIGHTS

  • Home
  • Spotlight
    • Weekly Global Economic Outlook
    • Top 10 Reading Guide
    • Future of Sports
    • Technology Management
    • Growth & Competitive Advantage
  • Topics
    • Economics
    • Environmental, Social, & Governance
    • Operations
    • Strategy
    • Technology
    • Workforce
    • Industries
  • More
    • About
    • Deloitte Insights Magazine
    • Press Room Podcasts

DELOITTE RESEARCH CENTERS

  • Cross-Industry
    • Home
    • Workforce Trends
    • Enterprise Growth & Innovation
    • Technology & Transformation
    • Environmental & Social Issues
  • Economics
    • Home
    • Consumer Spending
    • Housing
    • Business Investment
    • Globalization & International Trade
    • Fiscal & Monetary Policy
    • Sustainability, Equity & Climate
    • Labor Markets
    • Prices & Inflation
  • Consumer
    • Home
    • Automotive
    • Consumer Products
    • Food
    • Retail, Wholesale & Distribution
    • Hospitality
    • Airlines & Transportation
  • Energy & Industrials
    • Home
    • Aerospace & Defense
    • Chemicals & Specialty Materials
    • Engineering & Construction
    • Mining & Metals
    • Oil & Gas
    • Power & Utilities
    • Renewable Energy
  • Financial Services
    • Home
    • Banking & Capital Markets
    • Commercial Real Estate
    • Insurance
    • Investment Management
    • Cross Financial Services
  • Government & Public Services
    • Home
    • Defense, Security & Justice
    • Government Health
    • State & Local Government
    • Whole of Government
    • Transportation & Infrastructure
    • Human Services
    • Higher Education
  • Life Sciences & Health Care
    • Home
    • Hospitals, Health Systems & Providers​
    • Pharmaceutical Manufacturers​
    • Health Plans & Payers​
    • Medtech & Health Tech Organizations
  • Tech, Media & Telecom
    • Home
    • Technology
    • Media & Entertainment
    • Telecommunications
    • Semiconductor
    • Sports
Deloitte.com
Deloitte Insights logo
  • SPOTLIGHT
    • Weekly Global Economic Outlook
    • Top 10 Reading Guide
    • Future of Sports
    • Technology Management
    • Growth & Competitive Advantage
  • TOPICS
    • Economics
    • Environmental, Social, & Governance
    • Operations
    • Strategy
    • Technology
    • Workforce
    • Industries
  • MORE
    • About
    • Deloitte Insights Magazine
    • Press Room Podcasts
    • Research Centers
  • Welcome!

    For personalized content and settings, go to your My Deloitte Dashboard

    Latest Insights

    Creating opportunity at the intersection of climate disruption and regulatory change

    Article
     • 
    7-min read

    Better questions about generative AI

    Article
     • 
    2-min read

    Recommendations

    Tech Trends 2025

    Article

    TMT Predictions 2025

    Article

    About Deloitte Insights

    About Deloitte Insights

    Deloitte Insights Magazine, issue 33

    Magazine

    Topics for you

    • Business Strategy & Growth
    • Leadership
    • Operations
    • Marketing & Sales
    • Diversity, Equity, & Inclusion
    • Emerging Technologies
    • Economy

    Watch & Listen

    Dbriefs

    Stay informed on the issues impacting your business with Deloitte's live webcast series. Gain valuable insights and practical knowledge from our specialists while earning CPE credits.

    Deloitte Insights Podcasts

    Join host Tanya Ott as she interviews influential voices discussing the business trends and challenges that matter most to your business today. 

    Subscribe

    Deloitte Insights Newsletters

    Looking to stay on top of the latest news and trends? With MyDeloitte you'll never miss out on the information you need to lead. Simply link your email or social profile and select the newsletters and alerts that matter most to you.

Welcome back

To join via SSO please click on the key button below
Still not a member? Join My Deloitte

Effecting behavior change in a world of automated financial advisors

by Thomas H. Davenport, Jim Guszcza
  • Save for later
  • Share
    • Share on Facebook
    • Share on Twitter
    • Share on Linkedin
    • Share by email
29 June 2016

Effecting behavior change in a world of automated financial advisors

30 June 2016
  • Thomas H. Davenport United States
  • Jim Guszcza United States
  • Save for later
  • Share
    • Share on Facebook
    • Share on Twitter
    • Share on Linkedin
    • Share by email

Automated financial advisors can offer unbiased, data-based advice, but humans, often less than rational in their actions, require some behavioral science interventions to ensure they make the best use of it. Which is probably why some traditional investment firms are both adopting robo-advice and preserving a human role for behavioral interventions.

Many judgments and decisions today are increasingly being made by (or with the help of) smart machines—computer algorithms that employ codified knowledge, understand and generate language, and learn over time. This development offers great potential advantages in terms of decision quality, productivity, and other benefits, although it has created considerable anxiety about potential job loss. One aspect of more automated decisions that few observers have addressed is the potential for human workers to focus on behavioral and change issues.

In a variety of different domains, “getting the right answer” is an objective that will often be best obtained with the help of computers. Data, analytics, and heuristic rules can often produce a high-quality answer to any question for which there is codified knowledge. Indeed, if there is considerable data and expertise to be absorbed, and time pressure to make a decision, it is often impossible for humans—even the most expert ones—to make the best possible decision. There is simply more data and analysis required than the human brain can muster on short notice.

However, even if judgments and decisions are being made by machines, it is usually humans who have to act on them—or not. You may have heard about “behavioral economics,” which is based on the revolutionary (if seemingly obvious) principle that humans routinely deviate from the principles of economic rationality that until recently were considered sacrosanct.1

We humans, equipped with less-than-rational mental capabilities, have to decide whether to seek out machine advice in the first place, and to accept it once provided. We may have available, for example, high-quality driving direction advice from GPS mapping devices and apps, but many of us fail to consult these maps in the first place, or override their recommendations and become lost. We also have less-than-ideal self-control. For example, being provided with personalized diet and exercise recommendations is typically not enough to prompt the needed actions. Analytics and algorithms will often provide the best answer, but humans still must act upon it and change their behavior. One of us has referred to this as the “last mile problem” of predictive analytics.2

One area in which both automated advice and poor human behavior are both present in spades is personal financial investing. In the remainder of this essay we’ll use that important industry to illustrate both the challenges that human behavior presents to personal investing (often referred to as “behavioral finance” in the investment industry) and the opportunity for humans to address the problems that smart machines alone can’t address.

The rise of the robo-advisor

The recommendations traditionally made by personal financial planners and brokers—specifying what financial assets a client should invest in—are increasingly being made by computers. This trend even has a name—the “robo-advisor.” These tools, which are offered by both start-ups and well-established asset management firms, provide basic personal investing advice with regard to asset allocation, matching portfolios to risk preferences, and end-of-year rebalancing and tax loss harvesting. In most cases they recommend not individual stocks and bonds, but broad-segment (for example, S&P 500) mutual funds and exchange traded funds ETFs.

These decisions aren’t rocket science, and they are well within the capabilities of intelligent machines today. They can certainly handle more data and can provide more personalized recommendations than the typical human brain. They are also less expensive than the typical human brain; robo-advisors typically cost about 0.25 percent of assets, whereas a human advisor can often charge 1 percent or more of assets.3

Most robo-advisors only recommend investing actions, however, and don’t carry them out in an automated fashion. Even assuming that the investor has decided to engage with a robo-advisor in the first place, this leaves the “last mile” to be conquered: persuading said investor to take the recommended actions.

That is a considerably more difficult problem than determining what stocks and bonds to buy. The area of personal financial investing has long been known as one that is rife with problematic behaviors; it is, according to the behavioral insights classic Nudge,4 an example of a “fraught choice.”  Fraught choices are complex and difficult for humans in that they require specialist knowledge, are made infrequently, do not have immediate feedback, and have important effects that are only experienced in the distant future. It’s easy to see why investors so often make bad decisions like buying high and selling low, or underinvesting for retirement.

Robo-advisors and behavioral interventions

Even if some financial decisions are made well by robo-advisors, investors will almost certainly still need some help in adopting and maintaining responsible investing behaviors over time. What’s to keep them, for example, from panicky selling when there is a substantial drop in the stock market? What will prevent them from investing when the media (and taxi or Uber drivers) are talking up a rising market? Some other common ways that investors make poor decisions include “loss aversion”—caring more about not losing a dollar than gaining a dollar—and “familiarity bias”—being more willing to invest in familiar assets, like the stocks of companies in their home country, than those in companies they’ve never heard of.

The good news is that several of the firms that have adopted robo-advice have realized that there is a need for behavioral change. Some of the impetus for correct investing behavior is built into the automated advice itself. At Betterment, for example, one of the larger and more successful start-ups in the robo-advisor space, there is a “behavioral finance and investing” department comprising five experts focusing on how to improve their system’s investment advice, determining the right asset allocation, changing investment management strategies over time, and “behavioral design”—trying to ensure that Betterment customers display rational economic behaviors with their investments. For example, the company’s algorithms attempt to discourage such irrational behaviors as active trading and market timing. Betterment has a substantial amount of advice on its website as well, as does Wealthfront, another robo start-up. In one blog post, the Wealthfront chairman notes: “Despite how much we focus on fees in this blog, bad behavior is the single biggest destroyer of long-term returns for the average investor.5

A role for humans?

It’s difficult to truly influence behavior with blog posts alone, however, and some traditional investment firms are both adopting robo-advice and preserving a human role for behavioral interventions. Vanguard Group, for example, traditionally offered human advisors in its asset management business. Now, however, it has added some automated advice to these human capabilities in a “hybrid” offering called Personal Advisor Services. Not only does the Personal Advisor Services arrangement equip advisors to give better advice, it also gives them the capacity to serve more clients. By removing the burden of manual calculations, Vanguard enables them to focus more of their time and attention on the empathetic coaching that is their forte—and the lower fees charged for partially automated advice means more clients can have access to it.

With a lot of the basic investing decisions and information transmittal tasks now being handled by a machine, Vanguard executives felt that human advisors would have more time to work with clients on important financial behavior issues. The company thus embarked upon a strategy to equip its advisors with more behavioral coaching abilities. According to Karin Risi, Vanguard’s head of Personal Advisor Services,

The new system gives advisors more freedom to interact with their clients. Many of them are now using face-to-face video for these meetings, since all of the informational details are in the system. The advisors are also doing behavioral coaching when they interact with their clients—it’s very common, for example, for them to be a voice of reason when clients want to get out of the market in a downturn. Some of our clients turn to advisors for help because they know they lack the discipline to contribute steadily and take a long-term approach. It’s not unlike using a personal trainer to help you exercise.6

Like the robo-advisor start-ups, Vanguard also incorporates behavioral finance approaches, whenever possible, into the system itself. It tries to gently nudge clients, for example, into increasing their 401K contributions.

These hybrid offerings suggest new roles for humans in a world in which many decisions and judgments are made by machine. This could apply to a wide variety of individual and organizational decisions and actions. As in personal financial investing, perhaps humans can focus on the psychology and psychiatry of behavioral change—understanding customers’ (sometimes irrational) behaviors, persuading them to stay the course, and even reconciling the diverse orientations of a married couple. It may be that machines will never be able to take on such roles simply because they are not irrational enough to understand our behaviors. Finally an area in which humans have a competitive advantage!

Credits

Written by: Thomas H. Davenport, Jim Guszcza

Cover image by: David Owens

Endnotes
    1. Perhaps the best accessible description of the ideas in behavioral economics is Daniel Kahneman’s Thinking Fast and Slow (Farrar, Straus and Giroux, 2011). View in article
    2. James Guszcza, “The last-mile problem: how data science and behavioral science can work together,” Deloitte Review 16, January 2015. http://dupress.com/articles/behavioral-economics-predictive-analytics/. View in article
    3. Eva Lyford, “The true costs of robo advisors: What are the annual fees,” Investor Junkie, https://investorjunkie.com/42668/true-costs-robo-advisors/; Advisory HQ, “Average financial advisor fees in 2016: How much does a financial advisor cost?,” http://www.advisoryhq.com/articles/financial-advisor-fees-wealth-managers-planners-and-fee-only-advisors/. View in article
    4. Richard H. Thaler and Cass R. Sunstein, Nudge: Improving Decisions About Health, Wealth, and Happiness (Yale University Press, 2008). View in article
    5. Andy Rachleff, “Tax-loss harvesting as a behavioral tool,” Wealthfront blog post, October 22, 2015, https://blog.wealthfront.com/tax-loss-harvesting-behavioral-tool/. View in article
    6. Interview with Karen Risi from Thomas H. Davenport and Julia Kirby, No Humans Need Apply: Winners and Losers in the Age of Smart Machines (Harper Business, 2016). View in article
Show moreShow less

Topics in this article

Deloitte Consulting

Learn more
Download Subscribe

Related

img Trending

Interactive 3 days ago

Thomas H. Davenport

Thomas H. Davenport

Senior Advisor | Deloitte Analytics and AI Practice

Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College. He is also a visiting professor at Oxford’s Said Business School, a fellow of the MIT Initiative on the Digital Economy, and a senior advisor to Deloitte’s AI practice. His most recent book is Working with AI: Real Stories of Human-Machine Collaboration (MIT Press, 2022).

  • tdavenport@babson.edu
Jim Guszcza

Jim Guszcza

Jim Guszcza is Deloitte’s US chief data scientist and a leader in Deloitte’s Research & Insights group. One of Deloitte’s pioneering data scientists, Guszcza has 20 years of experience building and designing analytical solutions in a variety of public- and private-sector domains. In recent years, he has spearheaded Deloitte’s use of behavioral nudge tactics to more effectively act on algorithmic indications and prompt behavior change. Guszcza is a former professor at the University of Wisconsin-Madison business school, and holds a PhD in the Philosophy of Science from The University of Chicago. He is a fellow of the Casualty Actuarial Society and recently served on its board of directors.

  • jguszcza@deloitte.com

Share article highlights

See something interesting? Simply select text and choose how to share it:

Email a customized link that shows your highlighted text.
Copy a customized link that shows your highlighted text.
Copy your highlighted text.

Effecting behavior change in a world of automated financial advisors has been saved

Effecting behavior change in a world of automated financial advisors has been removed

An Article Titled Effecting behavior change in a world of automated financial advisors already exists in Saved items

Invalid special characters found 
Forgot password

To stay logged in, change your functional cookie settings.

OR

Social login not available on Microsoft Edge browser at this time.

Connect Accounts

Connect your social accounts

This is the first time you have logged in with a social network.

You have previously logged in with a different account. To link your accounts, please re-authenticate.

Log in with an existing social network:

To connect with your existing account, please enter your password:

OR

Log in with an existing site account:

To connect with your existing account, please enter your password:

Forgot password

Subscribe

to receive more business insights, analysis, and perspectives from Deloitte Insights
✓ Link copied to clipboard

Deloitte Insights and our research centers deliver proprietary research designed to help organizations turn their aspirations into action.

Deloitte Insights

  • Home
  • Topics
  • Industries
  • About Deloitte Insights

DELOITTE RESEARCH CENTERS

  • Cross-Industry
  • Economics
  • Consumer
  • Energy & Industrials
  • Financial Services
  • Government & Public Services
  • Life Sciences & Health Care
  • Tech, Media & Telecom
Deloitte logo

Learn about Deloitte’s offerings, people, and culture as a global provider of audit, assurance, consulting, financial advisory, risk advisory, tax, and related services.

© 2025. See Terms of Use for more information.

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee ("DTTL"), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. DTTL (also referred to as "Deloitte Global") does not provide services to clients. In the United States, Deloitte refers to one or more of the US member firms of DTTL, their related entities that operate using the "Deloitte" name in the United States and their respective affiliates. Certain services may not be available to attest clients under the rules and regulations of public accounting. Please see www.deloitte.com/about to learn more about our global network of member firms.

  • About Deloitte
  • Terms of Use
  • Privacy
  • Data Privacy Framework
  • Cookies
  • Cookie Settings
  • Legal Information for Job Seekers
  • Labor Condition Applications
  • Do Not Sell My Personal Information