Finserv Glossary

AI

What is Artificial Intelligence (AI)?

The use of Artificial Intelligence in the financial services industry has impacted the ability of institutions in the complex, highly-regulated industry to perform functions in such a way that automates regulatory compliance processes, marketing offer management, and other processes. Platform technology innovations, like those developed by Naehas, work with financial services and insurance industry customers to expand both the understanding and application of AI-powered platforms to improve efficiencies, reduce errors and enhance compliance.

A textbook definition of artificial intelligence comes directly from Britannica, which offers this thorough summary:

AI is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Britannica also notes that since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks—as, for example, discovering proofs for mathematical theorems or playing chess—with great proficiency.

History

The earliest substantial work in the field of artificial intelligence was done in the mid-20th century by the British logician and computer pioneer Alan Mathison Turing, as detailed by Britannica. Its historical summary of the theoretical work behind the emergence of AI includes this interesting background on the thinking and work of Alan Turing.

In 1935 Turing described an abstract computing machine consisting of a limitless memory and a scanner that moves back and forth through the memory, symbol by symbol, reading what it finds and writing further symbols. The actions of the scanner are dictated by a program of instructions that also is stored in the memory in the form of symbols. This is Turing’s stored-program concept, and implicit in it is the possibility of the machine operating on, and so modifying or improving, its own program. Turing’s conception is now known simply as the universal Turing machine. All modern computers are in essence universal Turing machines.

During World War II, Turing was a leading cryptanalyst at the Government Code and Cypher School in Bletchley Park, Buckinghamshire, England. Turing could not turn to the project of building a stored-program electronic computing machine until the cessation of hostilities in Europe in 1945. Nevertheless, during the war he gave considerable thought to the issue of machine intelligence. One of Turing’s colleagues at Bletchley Park, Donald Michie (who later founded the Department of Machine Intelligence and Perception at the University of Edinburgh), later recalled that Turing often discussed how computers could learn from experience as well as solve new problems through the use of guiding principles—a process now known as heuristic problem solving.The use of Artificial Intelligence in the financial services industry has impacted the ability of institutions in the complex, highly-regulated industry to perform functions in such a way that automates regulatory compliance processes, marketing offer management, and other processes. Platform technology innovations, like those developed by Naehas, work with financial services and insurance industry customers to expand both the understanding and application of AI-powered platforms to improve efficiencies, reduce errors and enhance compliance.

A textbook definition of artificial intelligence comes directly from Britannica, which offers this thorough summary:

AI is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Britannica also notes that since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks—as, for example, discovering proofs for mathematical theorems or playing chess—with great proficiency.

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