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Financial Entities Embracing Technologies
By Steve Mcatee, SVP & Chief Technology Officer, ORNL Federal Credit Union
I have been taking in a lot of information and data lately. I have been training the “Steve” machine model. I have also been following CULedger.com’s efforts in blockchain. While I am not an expert in Blockchain, I am a Blockchain tinkerer. I have come to this conclusion. It is an up-hill battle. Blockchain is having the same battle as Bitcoin. Even though they are not the same thing, they have the same fight. To adopt one or the other you have to give up a legacy- institutionalized process, whether that is the transfer of money between institutions or transfer of an asset between institutions and/or individuals. Institutions make a lot of money on their processes. If their process is not in a lot of pain, there is no reason to change. Blockchain will find its uses but in my opinion, there is a lot of hype right now. Of course, I will keep watching. However, I have started tinkering on other things. I have started tinkering on AI.
The evolution of cloud computing, big data, and neural networks is about to accumulate and form a category five hurricane on the global workforce
Every now and then, I will have a long drive. I hate driving. Since I cannot afford a Tesla, I rely on audible books to keep me engaged on the drive. My latest book was “The War on Normal People” by Andrew Yang. As I mentioned before I have been following politics. Collecting data and “training my model”. Here is what my model has learned. Mr. Yang has it right. Like Bitcoin, he is fighting an up-hill battle in politics seeking the Democratic Party nomination. However, he has it right on AI. The ability to train Machine Learning models is exploding in all cloud providers. The evolution of cloud computing, big data and neural networks is about to accumulate and form a category five hurricane on the global workforce.
It will not only be the workforce that is affected. It is going to be institutions that do not have the size, depth or expertise to tinker, train and learn AI. I am pretty sure as I write this the large financial institutions are building incredible machine learning models. Small and medium sized financial institutions are not. The vendors small and medium sized financial institutions rely on also are not. In the Financial Industry, size has many benefits. In the case of AI size means you have both expertise, labor and data. To get really good AI you have to have data. You have to have a lot of data. The vendors small and medium sized financial institutions rely on either do not have the data or are not making efforts to collect it. Most notably vendors do not collect customer interactions with the institution.
For example, if you are a bank you want really good call center agents. How do you get really good call center agents. You train them. Mostly though you coach them through interactions with customers. You show them examples of good interactions with customers and examples of bad interactions with customers. You give them data and they learn. AI is the same. However, instead of a good coach you have Data Scientist and Programmers and lots of data. Big financial institutions have both of these. Collectively small and medium sized institutions and their vendors have some, neither, or none.
As the big institutions train their AI they will need less human labor and make fewer mistakes. Large Financial Institutions will start applying their models to all of their processes, their efficiency ratios will increase, and their profit margins will grow. Their product pricing will become industry disruptive. The financial industry is going to become dominated by large institutions run by AI.