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The Effect of Artificial Intelligence on the Financial Industry

Considering the enormous impact Artificial Intelligence is having on multiple aspects of our lives and in the most diverse areas of human activity since its inception over 60 years ago (not including Raymond Lull’s concept of ‘thinking machines’ developed in 1300 A.D), the gains for the financial industry have been highly significant. AI’s capacity for processing, recognizing and responding to human language and speech through processes like Semantics technology and cognitive computing has led to a broad use of AI technology within the IT, high-tech and telecommunications sectors which have combined efforts to deliver the latest innovative technologies to every area of industry—Transport, Health Care, Agriculture, and many more—in a process of integration that goes hand in hand with the rise of ‘transhumanism’ (the integration of humans and machines), Robotics, Virtual Reality, and the evolution of Cloud-based online technology. For this reason, artificial intelligence software has helped boost production and efficiency in almost every sector of society (from your smartphone or tablet to smart homes that can literally take care of themselves), and more and more financial firms are turning to A.I. machine learning to do the job that humans have been doing for decades.

The high speed of data integration, processing and delivery by AI is making the job much easier for financial firms; the wide number of A.I. apps and data analytics computing software processes that are available (coupled with the diverse number of digital media devices available to the public user) has boosted their capability to eliminate data noise and reduce bureaucracy, forecast and anticipate financial trends among consumers, and deliver to clients financial solutions that are totally customizable and can even identify in advance (through constant monitoring of personal data and external sources) any financial concern which may arise in the future. In banking especially A.I. applications in Open Source Intel (Osint) have made it possible to analyze vast amounts of data and extract solutions which could not be discovered (or processed) without the aid of machine learning.

The best part is that the cost of computing has thus dropped remarkably while computing processes continue at an exponential growth as machines continue to learn at a faster rate. Moreover, the rise of A.I. has contributed to the free flow and exchange of information across multiple industries in a cross-sectioning and transversal process that allows the unfiltered access to business solutions for any company that is willing to adopt and implement these innovative technologies. A.I. personal assistants are already being used by companies worldwide to engage customers online, and likewise, robots are already being used in hotels, restaurants and airports to satisfy the needs of clients and travellers. Soon everyone will have their very own A.I. financial advisor that can recommend solutions and business strategies in every area of banking, recommending investment or market opportunities while determining and monitoring cost/benefit risk analysis—all at the touch of a button on their smartphone.

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