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Fintech means Blockchain? Is there anything else? Posted on Sep 11 - 2017

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Blockchain technology is just about the first thing that comes to mind whenever a discussion centers on the topic of fintech innovations. The tendency to synonymize fintech with Blockchain isn’t entirely faulty, especially considering that even the World Economic Forum, in a 2016 report, said that Blockchain technology will fundamentally change the way financial institutions around the world operate.

While Blockchain technology is most likely going to alter the financial services landscape, it would be specious to attach the concept of fintech exclusively to Blockchain. Other technologies, artificial intelligence for instance, also have the potential to change financial services as we know them. This piece looks at a number of other innovations that are disrupting or can disrupt the financial services landscape.

Artificial Intelligence

Put simply, artificial intelligence has to do with the development of computer systems that can perform tasks that are usually performed by humans — in many cases more efficiently than the latter.

Financial services firms have been deploying artificial intelligence to improve the way they do business for a number of decades. Although it’s now mainstream, the first Automated Teller Machine, or ATM, only came around in the 1960s. Until then, the withdrawal process was entirely manual. I bring up this example to point out that artificial intelligence in the financial space isn’t a new concept. It’s been around for decades. I also want to point out that it’s the advancement of artificial intelligence that’s disrupting the financial space — just like it has disrupted it over the last few decades. That said, here’s how the advancement of artificial intelligence is currently disrupting the financial services landscape.

Deep learning. Deep learning is a subset of artificial intelligence. The concept of deep learning is quite complex, but we can think of it simply as a concept in which a computer system looks into datasets to learn patterns gradually and in the end, uses what it has learned to take, or not take action, or offer quick insights in presented situations. View More


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