Artificial Intelligence (AI) and Machine Learning (ML)

Hello tech enthusiasts, welcome all of you to another article in the series of FINTECH. In the last article we discussed how information processing has advanced in finance sector with FINTECH. We have discussed how AI and ML have been used in this transformation. As promised, today I’m going to explain more about Artificial Intelligence and Machine Learning.

History of Artificial Intelligence/Machine Learning

In 1959, Arthur Samuel defined machine learning as a “field of study that gives computers the ability to learn without being explicitly programmed”. Samuel Checkers Playing program is one of the world’s first successful self learning programs and can be considered as a very early stage demonstration of the fundamental concepts of Artificial Intelligence.

AI was first developed in 1950s. In 1980s neural networks (computer systems modeled based on human brain) became widely used. However for about another decade the required hardware for AI found to be expensive and there was not enough data. The revolution of AI started in 2000s with the growth of personal computers along with World Wide Web. This led to a sharp decrease in price of computer hardware as well as opened the access to massive amounts of data. With that AI became increasingly effective in many areas and started experiencing resurgence.

Modern Applications of AI/ML

In the last decade AI has become a value added component to enterprise and computer software. It became a part of daily life with following applications.

  • In mobile phones with mapping and navigation software.
  • In ride sharing applications to assist with dynamic pricing.
  • In aviation to assist pilots in flying planes.
  • In operating systems to learn user preferences.
  • In financial institutions to detect fraud.

However AI was seen as a mean of technology differentiation rather than a market, as most industries can potentially benefit from AI applications. Companies in any given industry could have competitive advantage using AI as a tool and there were many opportunities for those who leveraged on AI. Industry experts predicted emergence of markets with monetization of AI and ML algorithms. After 2017, companies across many industries who have invested in AI started realizing tangible financial benefits. Many industry giants such as Google, Face book, Open AI started entering open-source AI product offerings making it is more accessible.

Industry Trends

Global funding in AI market has increased from approximately $280m in 2011 to $2,400m in 2015. Leading market research firms covering AI industry estimated that total value of AI industry would be $50billion to $60billion by 2025. AI established a global footprint with nearly every major technology company across the world adopting some type of AI strategy/application.

Artificial intelligence in Finance

When it comes to finance sector, AI had experienced various hype cycles followed by periods of disillusionment in the past. Many financial institutions attempted to build AI systems to process/analyze financial data and assist with financial decision making. With availability of data and reduced cost of computing, these efforts are becoming more lucrative and effective. More attention given in processing large amounts of financial data and creating new products that could be personalized to meet each user’s unique and changing needs. This means each user can have his/her own digital financial assistant/adviser.

AI is already being used to detect fraud at banks and to automate various compliance tasks. These applications served to reduce compliance cost for financial institutions and provide assurance on safety of assets to their clients.

AI could ultimately used to profitably trade in financial/equity markets and eventually replace the services of professional fund managers and investment advisers. Many large quantitative hedge funds have hired AI/ML experts to design trading strategies across various asset classes and the results seem promising.

Future of Artificial intelligence

Next wave of innovation in AI/ML would be to allow machines to learn not only from past data but also predictive analysis to make decisions in very similar way a human would do. AI can be divided in 3 phases.

  • Narrow Artificial Intelligence – Machine will do a specific task. Some examples are Google assistant, Google translator, Siri in Apple, Alexa or artificial chess players etc. We are currently at this stage.
  • Artificial General Intelligence – This is a hypothetical intelligence of a machine that has the capacity to learn any intellectual task that a human being can. Currently there are many experiments being carried out in this area.
  • Artificial Super Intelligence – This is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. This is still a far away dream and there are mix of opinions on the subject as to will it serve the human kind or destroy it.

I believe you got a fairly good idea about Artificial Intelligence and Machine Learning in terms of it’s history, it’s applications, it’s impact in finance sector and also what it holds for the future.

I will discuss about Robo advisory and it’s application in personal financing and investments in my next article. Be wise and Stay safe Everyone!!!


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