A Day in the Future
What was it the clients said at the December meeting? A financial advisor launches a CRM application and brings up the household’s profile. The profile contains a list of interactions in different formats— video, voice, email and social media based on Facebook, Twitter and Snapchat integrations. The data is stored securely in a compliant manner and can be played back anytime.
The advisor searches a transcript of all audio conversations in the last quarter. One issue keeps coming up—setting up a trust fund for the teenaged grandkids. Looking at sentiment analysis, the advisor can see the clients become more anxious when they mention instilling the right values about an inheritance.
The advisor tags financial education as a high priority concern for the couple and schedules an informal VR session with the teens.
Demystifying the Technology
Human speech is magical. It is more complex and sophisticated than we intuitively understand. Linguists like Noam Chomsky have built a science of language, deriving not only the surface logic of words but the underlying processes in charge of thinking. Language is more than spoken information. Rather, it is a process of analyzing, communicating and empathizing with others in real time. Since humans think faster than they actually speak, spoken communication twists and bends as participants take turns listening and responding to each other in conversation.
In the near future, it is possible that most speech will be recorded, saved and parsed for meaning by artificial intelligence. Putting aside legitimate privacy concerns for the moment, the implications of having massive amounts of searchable data derived from our verbal communication is revolutionary. Already today, our email providers index written conversation to derive eerily targeted online advertising.
Natural language processing (NLP) is the capability of computers to understand language, including converting spoken word to digital text. Though NLP has been around since the 1950s, it has seen tremendous strides over the last several years as processing power and wireless Internet made this computationally expensive innovation ubiquitous. Just ask Siri.
Semantic analysis is a subset of NLP that derives meaning from the written word. It parses grammar and word usage to extract intent, mood and personality behind the text itself. When combined with the advances in big data and the computing power of our phones, such technology could be the quantified emotional barometer of our lives.
Implications for Wealth Management
If you haven’t yet, pick up your phone and ask Siri, or any of her digital sisters, “What is the hourly weather in New York?” Or next time you receive a text about dinner plans, answer by pressing the microphone icon on the keyboard and dictate “I’ll be there in a few minutes.” Magic. Natural language processing enables an entirely new type of communication pattern and interface with software, and it is made possible by artificial intelligence.
The wealth management industry is predicated on trust and personal relationships, with technology acting as an amplifier of the help an expert can provide to a client. The ability to save conversations and map their meaning allows us to be better fiduciaries because it increases the advisor’s understanding of the client’s situation.
Profiling clients to the right investment product becomes a richer, more meaningful experience. Semantic analysis can tell us, just by looking at social data alone, the extent to which a client is extroverted, creative, neurotic, practical or altruistic. Our language is pregnant with meaning —hopes and dreams constantly communicated in the context of life. Future technology will uncover this information, cement it to financial goals, and execute an investment plan that helps clients become who they want to be.
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