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Coming Soon: Next Level Digital Assistants for the Financial Industry

Aug 08. 2017

20170808en_Joshua ChoiCoauthored by Joshua Choi, Senior Research Analyst, NRI America

 

 

20170808en_Makiko Tanakaand Makiko Tanaka, Research Analyst, NRI America

 

 

 

Introduction

    IoT offerings, like chatbots and smart home devices, are shedding their industry preconceptions as unreliable solutions. As it stands, the standing public opinions regarding the aforementioned offerings are unfavorable, as critics tend to prudently question just how much of a help chatbots and smart home devices can provide to the financial industry. But, we live in an era where financial institutions and advisors are continuously seeking ways to be closer to the customers they serve. And nearing 2020, a year by which Gartner states that customers will manage 85% of their relationship with the enterprise without interacting with humans, financial institutions and advisors will have to start taking a deeper look at how they can adopt these IoT solutions. When looking at how far chatbots and smart homes have come along, it is difficult to deny their potential to thrive as commercially successful solutions.

Chatbots

    Up until recently, majority of chatbots came with predetermined response options. This is not to say that those options even managed to fully cover what the customers intended to express in their inquiry. Therefore, for financial institutions to be able to provide the most user-welcomed chatbot, they must invest to address what the current generation of customers truly needs in a chatbot. And some have deemed that their answer to this chatbot challenge is to develop a bot converted through AI technology. 

    Capital One and Mastercard have been developing chatbot solutions which use natural language processing (NLP). These two entities have both made it clear in their intent to use NLP-implemented chatbots as persistent conversational partners, a direction based on their belief that chatbots will serve to be more of an ATM rather than a customer representative. For example, Capital One’s Eno uses a natural language processor to comprehend the variations within customers’ text-based inquiries. Eno can take in colloquial text commands, like u, r, and pmt over, respectively, you, are, and payment. Similarly, Mastercard is working with Kasisto, an external AI R&D company, to bring their customers KAI. Mastercard’s KAI runs on a recognition engine backed by NLP which can even take in unique inquiry commands and questions without providing the customers with pre-set response options. And while these chatbot offerings are impressive in their own distinct ways, in lieu of this NLP focus, there are alternative paths as well to investing into chatbots. 

    To recognize such other means of chatbot investments, financial institutions must differentiate what they can uniquely offer themselves versus what they can easily outsource for chatbots. After all, it is inevitable that select chatbot applications will be outsourced to external parties, when even at this moment there are major institutions like Wells Fargo and Mizuho Bank exploring chatbot technology through Facebook M. NLP is an ever-evolving application. There will come a point in the future when what is considered the pinnacle of NLP now, like IBM’s Watson, can be obtained through external means. Presently investing into any NLP application-based chatbots, although well-founded in intent, is more so providing a tool can only attempt to imitate the sensation of a conversation. Ergo, instead of improving the way chatbots interact with their customers, financial institutions should consider developing chatbots which can accurately address their customers’ needs by using what is exclusive to them alone: the customer data. 

    A prime example of an institution investing with a customer data focus is Bank of America. Bank of America is scheduled to release an AI powered voice- and chat-based digital financial assistant in the fourth quarter of 2017. Known as Erica, the chatbot aims to take digital advisory to the next level, with enhanced knowledge of the customers’ overall account. Erica analyzes and predictively advises ways to optimize the customer’s account performance. Further, Erica proactively suggests bank accounting options based on a customer’s banking habits, using terms like “typical monthly spending”, “this can save you…per year”, before any customer inquiry comes in at all. In this sense, Bank of America’s Erica is not only revolutionary in its service aptitude, but also exemplary in serving the financial industry today. What industry customers seek now in a chatbot is a “one-stop shop” solution. Realizing this, Bank of America invested in harnessing their customers’ financial and transactional data and allowing Erica to flexibly cater to the existent customers’ ongoing needs, based on identified patterns and banking habits. In a way, Bank of America found the most appropriate and sensible solution to the current financial industry customer population. However, it does not end here for chatbots and their potential applications. Erica is also supposedly able to update customers on changes in credit scores. With this information in mind, it would not be strange for financial institutions to see a chatbot demonstrate lending capabilities in a few years.

Smart Homes

    Like chatbots, smart home devices also are doubted in their aptitude to flourish in the financial industry. For one thing, it is difficult to speak on smart home devices’ future with certainty, as the offerings in question are far too premature. Most notably in the financial space, Capital One and American Express began providing payment services through smart home devices. But past these payment capabilities, smart home devices have not yet presented significant proofs of applicability in the financial industry. Still, knowing the progress made by Amazon, the leading smart home developer in the market, the financial industry must give smart home devices more credit with their potential to succeed in the financial industry. 

    Above all, we must commend Amazon’s recent success in raising awareness of and interest in using smart home devices. Amazon, who allows third parties to develop skills on Amazon’s Alexa, has observed exponential rates of growth in the number of skills from 1,000 to 15,000, between January 2016 and June 2017. Thereby, Amazon not only became recognized as the most major operating system of the IoT world, but Amazon also managed to garner more users to accept smart home devices as common household items. Additionally, in 2017, Amazon released its camera and touch screen infused smart home device, Echo Show. As Echo Show functions through video chat, a method becoming more widespread in usage for its ease, the product is expected to widen user demographics from the younger millennials all the way to the older baby boomers via network effect. The rise in skills and Echo Show emphasizes the market trend Amazon is pushing for, in increasing the rate of smart home device adoption. Catching onto this movement, many financial institutions have already started works on offering elementary stages of financial advisory through Amazon Echo. 

    Parties like FIS and Fidelity Investments have begun to accept smart home devices as future channels to reach their clients. Fidelity released a skill on Amazon’s Alexa to offer users financial updates. Naturally drawn to the idea of leveraging smart homes to assist clients, Fidelity decided to launch a tool for Echo users which can provide real-time insights into market trends, such as stock prices. Though judged as very limited for now, it appears that Fidelity will improve the Fidelity skill over time by collecting data and feedback from users. On the other hand, FIS seems more committed to including smart home devices in their financial services, to perhaps ultimately offer proactive advisory. In 2016, as part of PYMNTS.com’s Alexa challenge, FIS began developing Faye, a skill acting as a digital advisor to provide financial budgeting, savings, and planning for millennials. Faye can track a millennial user’s life patterns to prepare for his or her future in terms of wealth management. For instance, Faye can notify a user of how realistic it is to purchase a car based on his or her spending habits and income status. Should the user’s situation be dire, Faye can suggest a meeting with a human financial advisor. FIS is hoping Faye will be an easy-to-understand, instructional financial advisor for the younger Echo users. Granted, FIS and Fidelity have taken strides which more and more financial institutions will aspire to take as well. Yet, there is a financial institution determined to bring advisory and smart home devices a step further. 

    UBS has been running pilot programs on Emotionadvisor, a tool collaboratively being developed with AI-startup nViso. Emotionadvisor is declared as a tool which uses facial expressions for analyses, to be later used by financial advisors for direct advice. While it is uncertain as to whether this facial expression analysis will be useful for financial advisory, it is clear that UBS is trying to become closer to their clients. Based on a study by FIS, 72% of banked millennials have no form of financial advisor. Realizing this truth, UBS seems set on offering an advisory tool which can properly assess their client’s position, no matter how inexperienced the user is. What Emotionadvisor may offer is relatable data and insights, collected through visual analysis. If actually acquired, this sort of data would better grasp a client’s goals in financials management, thus managing to shorten not the physical distance but the relational distance between the client and the financial advisor. Clients, in the comfort of their own homes, can leisurely gain access to financial advisors’ expert opinions. 

    On top of their advisory developments, since 2016 UBS has been piloting a service on Amazon’s Echo, known as Ask UBS. Ask UBS is supposed to be able to respond to basic financial questions, like how the US economy is doing or what inflation means. Observably, with the mentioned Emotionadvisor and Ask UBS, we see that UBS is moving along with both advisory services and Amazon’s smart home device. As such, it may be very possible that UBS will offer its Emotionadvisor tool via Echo Show, to use Echo Show’s camera feature to read facial expressions. The progress UBS has accumulated with financial advisory and smart home devices is indicative of the financial industry’s belief in smart home devices, like Amazon’s Echo line products, as promising channels for financial advisors. In the case UBS manages to combine its two pilot programs into one product, UBS would be leading a revolution among the active omni-channel offerings in the financial industry.

Conclusion

Evidently, chatbots and smart home devices are becoming more charming as financial solutions, both with their own justifiable pace and direction. Seeing how there can only be growth from here on for chatbots and smart home devices, it is time for the financial industry to stop ignoring the fact that the next age of viable digital financial solutions is much closer than we may suspect.