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New-Tech Solutions for Low-Tech Problems

Moiz Kohari | State Street Corporation

November 01,2018

Even in our innovation-driven world, some older technologies have somehow managed to stick around.

Even in our innovation-driven world, some older technologies have somehow managed to stick around. In the financial industry, as we race ahead with technologies such as artificial intelligence and blockchain, low- or archaic-tech tools still make occasional appearances. Of course, when consumers use low-tech tools in their personal lives, it's sometimes considered quirky or even charming — think of the vinyl record players treasured by music lovers, or the flip phones stashed in the pockets of smartphone-eschewing consumers. But is it the same when it comes to business environments? When low-tech tools surface in a high-tech business environment like ours, they come with unintended negative consequences: Work slows down and the risk of errors increases.

Though such situations can be frustrating, true innovators see them as an exciting challenge and an opportunity for more innovation. That's because the solution to the low-tech/high-tech conflict may just lie in even more tech — that is, in automated tools that can integrate old-fashioned ways of doing business into our digital landscape.

Take, for instance, fax machines. As tech-savvy as our clients may be, some still opt to communicate with us by fax. Their reasons vary, but often it's a result of an issue with their computer systems that requires them to fax their requests to us while those technical issues are resolved.

Currently, the way we accommodate fax communications is as you'd expect: A human must review a fax transmission and decide how to address its contents. If it's an order for a particular transaction, that order must be manually keyed into our system — a step that takes much more time than a digitally requested transaction. It also opens up the possibility of "fat finger" errors, so whoever is doing the data input must be extra careful (read: work more slowly) to ensure they're typing accurately.

The solution to the low-tech/high-tech conflict just may lie in even more tech.

So how can we manage this divergence in technology better? By having machines do the work for us. Right now, we're working on developing a system in which computers "read" faxes for us and then route transaction orders and other requests exactly where they're supposed to go — with minimal or no human intervention. It works through a combination of optical character recognition (OCR) — which allows scanned-in images of text to be converted into text that machines recognize as easily as typed letters and numbers — and machine learning, in which computers are "trained" to make decisions based on available data. The ultimate goal is to eradicate all manual processing of faxes.

It's important to note that tech-based solutions aren't infallible. In the occasional case when an algorithm can't definitively categorize a fax, automation is paused and humans intervene. Even with those occasional interventions, however, automated solutions are still proving faster, more efficient and, ultimately, more productive than manual approaches to processing fax transmissions and paper contracts.

Someone once asked me if I can envision a day when we'll no longer have to develop high-tech solutions to address low-tech problems. The answer, quite honestly, is "no." After all, even the technology we believe to be highly sophisticated today may someday be antiquated and will require integration into an even more advanced technological environment. In other words, there is always room for improvement ... and those of us working on such improvements are always game to tackle another challenge.

Topics: Data Management , Advanced Technology , Innovation

Moiz Kohari | State Street Corporation

Moiz Kohari is a senior vice president and chief technology architect at State Street. In this role, he is responsible for the enhancements to State Street’s digital enterprise architecture, and the creation of the next generation digital enterprise that delivers on-demand secure computing capabilities, driven through machine learning paradigms and all pertinent fin-tech disruptive technologies. He can often be found rock climbing in Indian Creek, just outside Canyon Lands National Park in Utah.