Finding Genius

by Kunal Mehta

  Sallie Krawcheck, the CEO and co-founder of Ellevest, decided to focus on a specific underserved segment of the market: women. Discussing the genesis of Ellevest, she described to me an epiphany she had: “I had this blinding insight that the retirement savings crisis is a women’s crisis. The way to solve it was not just through helping women earn more money at work and not just through the traditional means, which people have tried. But there was something that I had a unique insight into even though I didn’t realize it: the gender investing gap.”

  Solving the gender investing gap has become Krawcheck’s mission. Through Ellevest, she hopes to broaden the reach of financial tools to women, who have historically been underserved by wealth management firms and as a result, have not spent enough time and money on investing and managing their wealth.

  Robo-advisory startups are employing big data strategies to understand their customers’ investing needs and desires and to optimize their clients’ portfolios. They can train their algorithms to take various factors into account. For example, Wealthfront asks questions about income, reasons for investing money, and investing philosophy. Ellevest asks similar questions and in addition, takes into account women’s specific financial experiences, such as different salary arcs and longer lifespans. Ellevest uses its algorithms to go beyond a wealth management platform that only has female-friendly marketing; instead, its technology enables it to truly better serve women and broaden the access of sophisticated financial tools to women.

  While this onboarding process provides robo-advisors a solid understanding of their customers, it also offers customers a streamlined experience that takes fewer than five minutes. Robo-advisory startups are able to automate every element of the process: onboarding, generating investing strategies, and re-allocating portfolios. Providing a frictionless onboarding process is essential because it is likely the first time many of their potential customers have used a wealth management platform. Jon Stein, the CEO and founder of Betterment, says that one of his constant initiatives is to “help reduce the barriers to entry for customers by experimenting with more seamless customer onboarding.” Meeting millennials where they are — online or on mobile — also adds less friction to the process. Additionally, automation significantly lowers the amount of required human capital and eliminates the need for costly consumer-facing brick and mortar locations.

  Millennials’ distrust of incumbent financial institutions has been a key force in helping robo-advisors grow. According to the Goldman Sachs report The Future of Finance Part III: The Socialization of Finance, millennials have lived through two recessions and consequently, often do not believe in active investing or trust wealth managers the way their parents did. Passive investing has skyrocketed in popularity in the last decade: in 2018, 42% of all US stock funds are passive mutual and exchange-traded funds compared to 24% in 2010 and 12% in 2000.18 In a similar vein, Goldman Sachs reports that the wealth management industry has evolved from a time when personal advisors were sought after to one where consumers prefer an automated platform because they are hesitant to trust humans, who they believe are more prone to error.

  Distrust has led millennials to rely more on their own networks and peer reviews for financial advice. Brian Hirsch recommends that startups leverage the power of social media and word of mouth referrals, especially from “early customers who become your major brand advocates. It lowers your customer acquisition costs.” In fact, unlike other startups, investing platforms are not permitted to request testimonials due to regulations. As a result, social network and word of mouth referrals have to be “very organic where women are talking to other women about what we’re doing and telling them to go check us out,” according to Krawcheck. Ellevest’s customer acquisition efforts have also been bolstered significantly by Krawcheck’s own personal brand. Before launching Ellevest, she spent years building her social following and cultivating trust from a group she describes as a “tribe of women and men who were interested in the financial process.” Jon Stein echoes that “most of our customers have come to us through word of mouth. Over 50% of our customers say they heard about us through a friend.” Further contributing to a positive customer experience are the transparent and often lower fee structures these robo-advisors offer. Lower operating and marketing costs enable these startups to maintain strong unit economics while still having lower account minimums that allow them to reach more diverse and younger investors that incumbent wealth management firms have typically neglected.19

  These startups also aim to communicate a sense of authenticity to differentiate themselves from the incumbents. Stein conveys Betterment’s authenticity as a customer-centric robo-advisory through their product design and workplace culture:

  “From day one we wanted to be customer-aligned. It’s important to build around the customer and always put the customer first. We realized there was a way to rethink products around customers. Other financial tools have been designed by financial services experts for financial services experts. We wanted to create a solution for regular people. Everyone here at Betterment spends time on the phone and via email with customers.”

  To convey Ellevest’s values, its slogan is unabashedly female-empowering: “Invest Like a Woman.” Krawcheck recalls that when Ellevest first launched, some people said her team would have to dumb down their content and “what was not surprising but still disappointing is that not a single person said ‘this is for women; it must be better, it must be more sophisticated.’” Not heeding their advice, Ellevest speaks to its customers in an intelligent and empowering manner. For example, in March 2018 after the Marjory Stoneman Douglas school shooting, some of Ellevest’s clients asked if their money was invested in gun manufacturers’ stocks. In line with being transparent and value-driven, Ellevest conducted research and published an open letter that there was likely minimal exposure to gun manufacturers and retailers. Ellevest proved they were listening to their customers by responding in an honest way, solidifying customer trust.

  The Goldman Sachs report suggests that robo-advisors are typically marketing to a specific millennial demographic — HENRY’s (High Earning Not Rich Yet). These consumers have a growing amount of assets, but are still too small for traditional wealth management firms. Attracting them as customers now is part of a long-term strategy because they have the potential to become more lucrative customers in the future. While robo-advisors’ intentions are not fully certain, they are still democratizing access to financial tools that would have otherwise been unavailable to large swaths of the population, not just HENRYs.

  Robo-advisors are becoming subject to heightened scrutiny from the Securities and Exchange Commission (SEC). In 2017, the SEC released guidance on robo-advisors, advising that they are subject to the same regulatory framework as traditional wealth advisors. Given robo-advisors’ increasing market share in a massive industry, it is integral that they follow SEC regulations to protect their clients’ wealth and maintain their trust.

  The Incumbents

  Since 2015, many firms such as Charles Schwab and Vanguard have been launching their own robo-advisory services and have seen great success. Schwab Intelligent Portfolios and Vanguard’s robo-advisory offering launched in 2015 and had over $38 billion and $130 billion in AUM, respectively, by the end of the first quarter of 2019 according to The Robo Report™: First Quarter 2019. Schwab Intelligent Portfolios and Vanguard have far surpassed startups, which have a wide AUM range between $100 million and $17 billion per startup. Incumbents have a built-in network of clients who might want to try out a robo-advisory service, reducing their customer acquisition costs. BlackRock also got into the game with its 2015 acquisition of online wealth management platform FutureAdvisor.

  Betterment is in a unique position as it has a direct-to-consumer product and a business-to-business product, Betterment for Advisors. Stein believes that “because of our Betterment for Advisors platform, many incumbents think of us as a partner. We work closely with three institutions that a
lot of people would think of as competitors.” Krawcheck says that a number of investment platforms have reached out to her to use Ellevest’s branding or content but Ellevest has rejected these offers. Interestingly, Morningstar, an investment research company, led Ellevest’s first round of funding so they can share information and work through problems together. Both startups have found ways to work with or partner with financial incumbents in a way that felt authentic to who their startups are, providing them with additional scale and resources, strategies that no doubt will prove helpful in the race to seize market share and contribute to longevity and market durability.

  While incumbents’ movement into the space provides validation, it also threatens startup robo-advisors. However, in the last year, a notable shift has been occurring within robo-advisory startups. They are now adding the human touch to their services so they can cater to those with more assets and upsell HENRYs as they move up the economic ladder. For example, Betterment and Ellevest now provide solutions offering one-on-one access to one of their certified financial planners. Money is personal, so offering people more options ranging from fully automated to a hybrid of humans and automation provides more comfort to people trusting these firms with their assets.

  Krawcheck believes that over time, there will be fewer and fewer people and more technology in wealth management companies. She believes, “moving from financial advisors to a digital offering is challenging. People really hate to give up clients. It’s better to start with digital and add people.”

  It is still too early to say if robo-advisory services can provide strong returns; however, it’s an easy way for people to start investing instead of doing nothing at all.

  Insurtech

  In the last few years, the insurance industry has begun to undergo long-needed innovation and as a result, has become a popular area of investment for venture capital firms. Investors poured $3.2 billion into insurtech startups in 2018 alone.20 The key drivers of insurtech innovation are more data sources and an increasing focus on creating a positive customer experience to drive customer loyalty. Both insurtech startups and established insurance companies are attempting to reach millennials, who are starting to make their first insurance purchases. Brendan Dickinson points out that “millennials are less engaged with insurance out of anybody who’s previously been in that age range. All of the carriers are standing at the edge of this oasis in the desert but they see it slowly shrinking because nobody likes them so they’re all really concerned.” As a result, insurtech startups are targeting this market and hoping to gain millennials’ trust through increased transparency and positive customer experiences.

  The insurance industry is long overdue for modernization; for example, it is still mostly built on legacy systems from the 1960s and 1970s. In addition, buying insurance is a universal experience — a universally negative experience. Steve Lekas, CEO and co-founder of Branch, a home and auto insurance company, says that what ultimately caused him to found an insurtech startup after a career in insurance was the “recognition that my customers hated me and their belief that I was intrinsically evil.” These factors have created an immense opportunity for insurtech startups to emerge.

  New Data Strategies

  In the insurance industry, data is essential; it helps insurance companies understand customer behavior, predict trends, underwrite, and optimize pricing. As a result, insurtech companies are employing an array of new data sources and optimizing their algorithms to offer improved pricing. Spencer Lazar, responsible for Special Projects at insurtech startup Lemonade and a former partner at General Catalyst that invested in insurtech startups such as Lemonade and Shift Technologies, described to me that what drew him to insurtech “was the explosion of new data sources used for underwriting and claims processing; opportunity to disintermediate legacy agent-based customer acquisition models; and new distribution opportunities stemming from the proliferation of ecommerce and software in all parts of the economy.” Dickinson echoes that he initially became interested in insurtech because “there’s a host of new data sources that can be used to make the products more efficient.” Ingesting and analyzing multiple data streams requires insurance companies to invest in data analytics capabilities and resources. It becomes a virtuous data cycle: the more data that insurance companies can ingest, the better they can understand risk at an individual level and provide more personalized, tailored solutions, even offering tips to customers on how to make their behavior less risky. Improved solutions lead to better customer engagement and more optimal pricing, leading to customers being more willing to share more data to continue to get better products and pricing.

  This model is in contrast to the typical insurance model, which pools people’s risk and requires those individuals to pay a certain price as a group. Lekas explained that the data that is most useful to an insurance company “is the data that helps segment risk. That data is not always very apparent on why it segments risk exactly and it’s most frequently a proxy for behavior.” Being able to layer an individual’s risk profile, along with the segment they are in, should reduce risk and therefore make pricing more competitive. The more data insurance companies can collect, the more accurate their risk profiling will be. While unique insights into underwriting are essential for insurtech startups, Lazar points out that “the hard thing is you don’t really know in some cases how well you’ve done in that regard for some time because of the delays that often occur between purchasing a policy and making a claim.”

  The cross-section of Internet of Things (IoT) devices and big data is pivotal to helping the insurance industry innovate. There is now an inundation of real-time data that insurtech companies can use to better understand their customers from devices such as cell phones, watches, and cars. People’s lives are increasingly connected by IoT devices in all areas of their lives: at home, in their cars, at work, and on or near their bodies. McKinsey states in its report There’s No Place Like [a Connected] Home that as of 2017, there were 29 million connected homes in the US, up from 22 million the year before. The insurance industry is prioritizing IoT data because it empowers them to take a more proactive stance in preventing risk. For example, insurance companies can provide tips and incentivize homeowners to switch their alarms on and stoves off. Some auto insurance companies now offer telematics where consumers can have a device in their car feed information to insurance providers. This data enables auto insurers to create a full picture of consumers’ driving behavior and map out various associated risks. Devices in cars could also alert drivers to a potential breakdown or other risks. Research in Accenture’s report Technology Vision for Insurance 2017 found that 64% of people wanted more personalized advice and that 57% were willing to share more personal information to get additional benefits. This shows a clear understanding of an exchange of data for more value. In other words, the relationships between insurance companies and their customers have evolved into partnerships.

  Incumbents are also taking advantage of this trend. Progressive offers a solution called Snapshot that provides usage-based automotive insurance and it has collected over 25 billion miles of driving data across its usage-based insurance solutions.21 In 2018, Progressive rolled out a new solution, Smart Haul, a usage-based insurance offering for commercial truck drivers. If drivers share driving data from their electronic-logging devices (ELD) with Progressive, the insurance company promises a minimum of 3% savings on their insurance. MetLife has a solution called My Journey® that tracks drivers’ behavior on the road and provides feedback to improve driving and insurance rates.

  Insurance companies are also using computer vision to gather more insightful data. For example, Lekas says that roof quality and age are very important factors in understanding homeowners’ investment in their homes and houses’ ability to withstand storms. Analyzing roofs using computer vision becomes a valuable data input in pricing home insurance. More broadly, Lekas believes there is “tremendous opportunity within imagery interpretation through compute
r vision because there’s so much data about assets that hasn’t been available.”

  A New Customer Experience

  As in other areas of fintech, customers are increasingly demanding a positive, frictionless experience from insurance companies, in contrast to the status quo which is often associated with dread and complex paperwork. Insurtech startups have the advantage of starting as customer-centric models. Dickinson believes that for insurtech startups, building trust is not as tough as it might seem: “when you’re operating in a market where the incumbents have a Net Promoter Score below cable companies, you’ve got some leeway. You’ve got some opportunity.” Winning clients over in the first point of contact is key and will create customer stickiness. Lazar recommends three steps to creating a positive customer experience:

  “One way is to start with a brand that speaks in a language consumers actually understand. The second thing is to use technology and distribution channels that they’re familiar with — whether that’s chat, mobile, or desktop web. The third is to over-invest in services in the beginning because people have had such bad experiences historically that their expectations are very low.”

  “On demand” or “pay-as-you-go” insurance is a prime example of a customer-centric framework in insurance. It marks a dramatic shift in the insurance industry from the “set and forget” approach. This hyper-personalized approach to insurance is based on when people are actually using their assets and when they are therefore at risk. For example, Slice Labs protects property only when homeowners rent out their houses. If they are not renting out their homes frequently, this ends up being cheaper than insuring their homes for the full year or for multiple years. In the article “Will On-Demand Insurance Become Mainstream,” KPMG suggests that digital natives expect flexible, dynamic options at their fingertips instead of fixed plans that are difficult to commit to for a long period of time. They state that 93% of millennials would be interested in purchasing on-demand insurance if prices were the same. Consumers pay a premium for the convenience of on-demand insurance as a per unit purchase is more expensive than it would be under an annual policy.22 While insurance companies sacrifice some customer stickiness with this model, they make a higher margin. One potential issue is adverse selection: customers might only activate their insurance if they are in risky situations. Lekas also believes that on-demand insurance creates friction for users because it forces users to remember that they need to insure themselves in specific instances; however, he acknowledges that “consumers will jump through a lot of hoops to get a cheaper price” when the insurance is compulsory like auto insurance.