Fintech or Financial Technology solutions are a perfect partner for voice services, allowing users to access information more quickly and directly by saying what they want to know or achieve.
“What’s my current bank balance?” or “Please tell me my top 10 moving stocks today.”
It could be to get a voice alert every time a particular KPI is hit within a business or a series of sensors within manufacturing, alerting bosses to failure, with the appropriate losses calculated and relayed in real time.
All of this can be achieved without requiring another human being in the loop. The user simply asks for the information they desire or receives it via pre-requested notifications.
For consumers, it can be as simple as moving money between different bank accounts or more complex multi-party payment scenarios.
“Please pay John, Sally and Sarah £15 each towards last night’s dinner from my current account ending 0876.”
“Let David, Chris and Barry know they owe me £5 each for last night’s round of beers.”
To which Chris could reply
“Pay James £5 for last night’s beers from my beer fund account.”
All of this is logged automatically to their bank accounts with the transaction happening in real time, making the payment quick and easy to Request, Pay and Receive without having to touch a physical device such as a smartphone. Users simply say what they’d like to achieve and the voice service takes care of the rest.
This works because we can take a complex sentence structure that a user may utter and break it down into its component parts, the actual data we need to act on.
Queries can be even more complex if we wanted to create a system that can interact with the stock market via a third party backend.
We could ask:
“Buy 1,000 shares in MSFT immediately and sell 500 shares in APL if the price dips below 5% of target over the next three days, also when GOG releases a financial statement if they miss the target by more than 2% sell 5% of my holdings.”
This chain of requests to a voice service would then be passed to a machine learning based financial services system which would carry out these requests on the user’s behalf. It would then – once a particular threshold of the request is met – relay that information back to the user via the voice Interface.
“I have purchased 1,000 shares in MSFT on your behalf and a watch has been set on AAPL if the price dips below 5% over the next three days. I am waiting for latest GOOGL results and once published will let you know the outcome.”
“Alert: GOOGL results show 3% growth, would you like me to place a buy order?”
In the first statement, our Voice Interface has confirmed the request the user made, where there was an action to take immediately it is taking it and, where there was a request to evaluate, it is waiting until it can run evaluation and return the result.
In the second statement, an alert has been delivered by the Voice Interface because the condition has been met, the evaluation was run, but because growth has been achieved where the user requested a sell if GOOGL dropped, the user is asked if they want to buy instead.
“Yes, 1,000 shares.”
Anticipating the user’s potential need we can shortcut the next stage of the user’s conversation with the Voice Interface. Now the user simply says ‘yes’ and the amount they would like to buy. We already understand the context because it was the last thing we communicated to the user, the results of GOOGL’s financials.
If you would like to learn more about how Voice and Fintech can work together then please book a free call back with one of our voice consultants.