Can We Teach Users to Trust FinTech?

March 29, 2018 - 4 minutes read

FinTech app developer

There’s no doubt that the development of FinTech has the potential to transform finance. But like other disruptive technologies, this promise of improvement also usually brings some trepidation of adoption from established industry players.

The Benefits Are Clear, but so Are the Limits of Trust

FinTech-fueled automation has already found its way into numerous processes in the financial sector. Whether it’s in London or NYC, developers at every major financial company are implementing these recent innovations to replace the need for human participation in repetitive tasks.

But FinTech is moving fast, so fast that tasks, like making advisory decisions or negotiating and executing contracts, are now within its scope. At this point, change isn’t being halted by technological limitations; it’s more prudent to ask ourselves, “What are we comfortable with machines doing,” not “What can machines do?”

Jason Gabauer, a comptroller at real estate investment company Halstatt, has seen the benefits of FinTech first-hand. In fact, he’s always using financial management platforms like Sage Intacct to automate document creation, a task that would normally warrant a couple more human workers in the office.

But does Gabauer trust FinTech? Not exactly. “I’m still in the trust but verify [stage] when it comes to AI,” he says. For Gabauer, the benefits of boosting FinTech tools with more intelligence are clear-cut in terms of time and effort saved. But he still wouldn’t trust automation with the responsibility of making a decision. At least, not yet.

Training Humans to Trust

This problem of trust is obvious to many, including Oracle. But unlike the others, the famous software company is taking a unique approach to solving this: it’s training users to trust AI in increments.

To start, its FinTech applications offer recommendations to users. If the user begins to agree with the recommendations, the AI will start offering ones that tackle harder problems. If the user becomes completely comfortable with the recommendations, they can let the AI take over and make the actual decision. Jack Berkowitz, the Vice President of Products and Data Science at Oracle’s Adaptive Intelligence, calls this “[going] straight into machine-to-machine capabilities.”

An example of this would be negotiations for payment terms. The AI could simply re-adjust the terms for an early payer without having to bother both parties in the agreement.

Early Embracers Get Early Benefits

Research and advisory company Gartner recently reported that AI “will become a key differentiating factor in finance system evaluations” in enterprise systems by 2020. But you don’t have to wait that long to see that FinTech has become a linchpin for many organizations already.

For now, it’s mostly relegated to taking care of repetitive tasks, but this is already yielding substantial results in terms of time and money. It’s hard to imagine the limit of benefits that AI and FinTech will bring in the near future. But soon, maybe these technologies will be able to figure that out too.

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