Chandra Ambadipudi, Chief Executive Officer, Clairvoyant discusses the potential for and Machine Learning in financial service.
What is the difference between and Machine Learning?
is the concept of machines performing tasks that are characteristic of human intelligence — it is the all-encompassing phase that is highlighted in multiple Sci-Fi movies like Terminator, Matrix, etc. The concept of is to address things like recognizing objects and sounds, learning, planning and problem solving.
Today most of the used in a business context is specific to one area, it displays characteristics of the human intelligence in one specific area like sound, or problem solving. The evolution of to replicate multiple aspects of human intelligence is the next stage in its evolution and that is the focus of new emerging initiatives across industries.
Machine learning in its most basic form is a way to achieve . Machine learning is a way of training an algorithm so that it can learn how to learn. The training here involves feeding large amounts of data into an algorithm and allowing the algorithm to adjust itself and improve. To further expand on this, can be achieved without by writing significant amounts of code or programs, but today algorithms make the process of creating -based applications much easier than through manual processes.
What are some of the common misconceptions about and Machine Learning?
People often think that Artificial Intelligence (through ) will replace their job functions completely and perform at a higher level than humans, or that has human-level emotions and intelligence. Naturally, these stem from a misunderstanding as to what can truly do. While it is capable of processing large amounts of data very quickly, it’s certainly not at human-level in terms of judgement and perception. There’s also a misconception (often fueled by sci-fi movies) that applications will suddenly become sentient. could certainly become destructive, but not at the level often portrayed in Hollywood. A final misconception is that is a silver bullet. can solve for a lot of things, but there’s not one magic algorithm that can solve everything. Most applications need to be built and implemented for a specific purpose based on the industry and company.
What are the current applications of and Machine Learning in banking, finance and insurance?
More and more institutions are utilizing automated processes, and is currently driving some of the biggest industry changes in banking, finance and insurance. By making frequently performed duties automated, makes it possible to focus on higher level objectives. You see this in tasks such as document management, where it reads through documents, including forms, contracts, etc.[…]