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Voice-enabled investing: Three steps to prepare for enhanced client interactions

(Image credit: Image source: Shutterstock/polkadot_photo)

Less friction in the client experience and higher levels of investor activity: these desirable goals could potentially be facilitated with effective voice-enabled investing strategies. Growth in accessibility to smart speaker devices (e.g. Google Home and Amazon Alexa), advances in natural language recognition, and the broadening ecosystems in third-party integrations are all factors contributing to the growth of voice technology. Financial institutions and advisors have the opportunity to leverage voice-enabled services to reduce friction in and improve client interactions, all benefiting the bottom line.

With 91 per cent of brands investing in voice, as reported in a recent study by Adobe, many companies are still exploring how to best implement voice technologies. Financial institutions are taking varied approaches to investing in voice, using it to automate simple tasks or to offer clients more ways to interact with their advisors, as I explore in detail in the report "An Introduction to Voice-First Investing: Key Steps to Harness its Potential." To keep pace with the trends developing in smart speaker usage and the opportunities they present for wealth management, consider these three steps:

1. “Ignore voice at your own peril”

Blogging about what insurers should pay attention to regarding voice, analyst Donald Light advised insurers to “ignore voice at your own peril.” His observation was that virtual assistants are becoming increasingly embedded in homes, cars, and lives, and that industry needs to keep pace with customers’ behaviours and preferences. I believe the same admonition holds true within finance.

Voice-enabled offerings have taken root. Predictive analytics will be a key function of voice, helping advisors anticipate their clients’ needs, suggesting options as market conditions change or as a client’s situation evolves. Over the coming five years, virtual assistants will become partners—not mere tools—to help effective institutions grow. Today, voice isn’t a single solution that eliminates client or advisor challenges, but it is a valuable way to automate simple tasks and offer clients increased choice in their interactions. While more mature developments are certainly on the horizon, now is the time for financial institutions to monitor this space, to follow the trends, and to make initial moves toward implementing a voice-enabled investing strategy.

Today, common voice use cases are present across varied functions of financial services. Voice-enabled services within capital markets include delivering analyst coverage/reports, target prices, transcriptions of earnings calls, and company information for institutional clients. Within wealth/asset management, services include providing market updates and daily flash briefings, quotes on securities, or letting advisors and clients track portfolio activity to get a breakdown of portfolio performance. Commercial and retail banking are using voice-enabled services to help clients keep track of account balances, budget, spending, and upcoming payments and rewards accumulated through past purchases.

Maturity of voice services varies within the industry. Because there is not yet wide adoption of voice offerings, most wealth management firms use voice for only basic queries (e.g., delivering flash briefings and market updates). In contrast, the leader in the voice space, TD Ameritrade, goes further, allowing clients to execute live trades, for example.

As the voice-enabled investing space evolves, it is likely to be used to automate certain back office processes and cater to assist front-line staff with basic client inquiries. Some financial institutions are incubating these capabilities internally by spinning off a dedicated centre of excellence that accelerates the development of voice-enabled solutions. Moving forward, voice may potentially evolve into a robust notification system and a decision support tool for advisors.

3. Create a voice strategy

A strategic approach for using voice is essential. To begin, institutions should identify the business cases that may benefit from voice-enabled services. When your client calls for Alexa, what basic tasks (FAQs, daily flash briefings) can you provide? What account-specific queries?

Identify an organisational roadmap for the transition, including how to build, deploy, and continuously improve services. Keep the user experience in mind to ensure that virtual assistants provide consistent services across all lines of business deploying this. This approach requires ensuring that all use cases for a financial institution feel like a singular experience, integrated into a shared enterprise architecture across all channels (e.g., smart speakers, desktop and/or mobile chatbots, etc.). Financial institutions may partner with AI-specialised vendors to help their IT/digital teams in the voice development process. Steps include:

  • Identifying a deployment strategy to meet the financial institution’s architectural standards and to outline the optimal customer journey;
  • Assessing data requirements, including processing unstructured data for integration with front end systems;
  • Implementing conversational design, such as designing a virtual assistant persona, designing the flow of conversations, and utilising a natural language processing (NLP) engine to develop processes that are tailored to the institution’s clients; and
  • Creating a maintenance and analysis plan in order to track engagement and scale the institution’s offerings.

Voice, like mobile before it, may be positioned to possibly become the next major channel for customer interaction and support. Moving to this natural method of client interaction can reduce layers of friction and potentially increase utilisation of services. Will you be ready?

Awaad Aamir, wealth management analyst, Celent

Awaad Aamir is wealth management analyst at Celent. Previously he worked in banking and telecommunications, focusing on enabling front-line operations with AI-based technologies.