In his bestselling book Homo Deus: A Brief History of Tomorrow, Yuval Harari writes at length about the onset of a new worldview he believes will revolutionize humankind. He calls this worldview dataism – the belief that super intelligent computer algorithms will become so precise that we will trust them to essentially run our lives.
We see early stages of dataism today. For instance, technologies such as Waze effectively crunch mountains of data to provide useful advice for drivers to get to their destination more quickly, and marketing companies like Route pull GPS data to update digital outdoor media in real time based on the context.
These technologies will only become more and more accurate as more people use them. And, the same scale of progress will affect a range of future technologies, such as embedded body scanners that track every aspect of your health, smart fridges that track your food purchases, career guidance assistants, and intelligent financial services.
Smarter Banking Algorithms
Think of the possibilities as they relate to banking.
For instance, when a consumer wants to decide where to go for dinner, their body scanner might tell them their allotted remaining calories for the day and map that information to their bank account to give them exact meal recommendations for the right price — perhaps including discounts for businesses the bank loans money to. Their would also be a connection made to their remaining budget for food for the month.
Or, say a consumer is looking for a car loan. Their banking app might pair with every car lot near them, instantly matching their car preferences with the best loan offers given their credit history, and give them a list of best options.
Or perhaps they’ll be looking for something to do on a weekend night. Their body scanner might analyze what types of activities will be best considering their current mood, and then map those activities to their total monthly entertainment budget.
In each of these cases, a consistent principle is that different technologies will work together to create smarter banking and lifestyle algorithms. In this way, the financial institution’s branding can be constantly top of mind, with associations to better life decisions.
Software aside, your optimization strategy could be losing you money. But, with the right goals as your strategic foundation, your ROI will trend upward.
This webinar will show how to develop marketing strategies that will generate new checking account volume.
Better Than Humans
Of course, if you’ve dealt with algorithms and digital assistants, you know that they’re often clumsy. When Siri was first released, for instance, users complained that the product gave them all sorts of incorrect answers, and many users still find issues with the product today.
However, digital assistants are quickly improving. In 1996 the error rate for speech recognition was over 43%. By 2001, that was down to about 20%; outside of limited vocabularies like numbers, out of a sentence of ten words, two of them would be wrong. But unless users were prepared to invest a few months training recognition systems, the error rate stayed much the same for the next decade, plateauing around 15%.
In 2016, a Microsoft Research team got the error rate down to 5.9%. That matched the human error rate when we hired a professional transcriber to transcribe the same data.
Since then, there’s been some debate about how accurate you can get a human transcription to be. IBM used four teams of people, doing multiple transcriptions of each sentence and combining their work got the error rate as low as 5.1%. Other research has seen even better results.
The point here is that a technology that might legitimately have been useless for decades might have crossed a threshold in the course of a a relatively short time to become better than human. An accuracy rate of 0 to 95 percent on certain might seem worthless. But 98 percent accuracy…
In Homo Deus, Yuval Harari makes the case that this transition to super intelligent algorithms will give humans access to almost ‘godlike abilities’, including the ability to know exactly what we should do with our money to find long-term well being.
Banks and credit unions will be at the heart of this process as they lean into decisions today that will bolster the use of algorithms tomorrow. As this happens, more and more consumers will come to view their financial institutions as an integral part of their lives, trusting them to make a difference in their day-to-day lives with targeted advice potentially even outside the realm of financial services.
This will result in technologies such as Clinc, which is working with USAA to replicate and even exceed the service that users expect from support centers. With Clinc, users can interact via voice commands to instantly learn details about their spending habits and trends.
Soon enough, users will be able to use that data to get a super intelligent advice on what they could do with their finances. Perhaps they’ll explore the option of getting an SBA loan or a mortgage. Perhaps they’ll explore a range of time deposits or savings accounts. In both cases, the super intelligent algorithm will be able to spell out the pros and cons of each choice and make an ultimate recommendation based on millions of data points. In short, super intelligent algorithms will give advice that’s far superior to anything humans can offer.
Again, while these super intelligent algorithms might not sound feasible given the current state of technology, change can happen all at once. When it does, we will move quickly into a new state of banking, where the best knowledge is immediately to end users. It follows that financial institutions that start laying the foundation for this revolution will get the upper hand in the decades to come and will be viewed as the primary financial service provider for users who benefit from their super intelligent offerings.
For most organizations, it is time to shift thinking from doubting that superhuman banking can happen to preparing for its inevitable arrival.