Table of contents

  1. Machine learning
  2. Applications of Machine learning
  3. How machine learning is useful?
  4. Purpose of Machine learning
  5. Artificial Intelligence Markup Language
  6. Conclusion

“Machine Learning: A computer can learn from experience without being specifically programmed.”

  1. Machine learning

As new technology is been discovered the different sector distributed for different purposes are making use of it and if we talk about the crucial sector which is none other than finance and banking sector than it has been trying to implement these technologies as much as it can so that the customer satisfaction can be improved and the new modern technology can replace the old one so that the smooth working can be carried out. This behaviour of opting the modern technology has made banks to look forward to a various domain and one such famous machine learning which in past years has done a lot of research in technology to come up with advance systems.

Machine learning has been around for quite some time and there are many technologies under this which are been used in today’s world thus it is first of all important to understand what does machine learning means? What is the application under it and how it affects the sector we are presently in use?

2. Applications of Machine learning

  • Machine learning is the application of artificial learning that enables our system to learn by its own to improve the experience like a human without actually been programmed.
  • This technology accesses the data and learns through it. It also focuses on the development of a computer in a well-functioned manner.
  • The process which is adopted is started with the learning of data, direct experience or finding a pattern among.
  • Mainly here the most important thing is to enable the computer to learn on its own without human involvement which would then be said as smart systems.
  • The algorithm here play a major role in considering a sequence of keyword.it has been said about ML that:

“Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in an autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.”

  • This is true as the ultimate goal of machine learning to solve modern world problem which the use of data as the main tool.
  • There are huge changes made to machine learning of the present as compare to that in past. The evolution started hare from a term known as pattern recognition and a saying that computer can interact so much to human as a human.
  • The famous researchers found it impressive and wanted to hand-on this technique to check whether it works or not.
  • The procedure here was independent as the result that came into existence were quite impressive. The computer was able to generate a more reliable and effective result that was not expected. 

3. How machine learning is useful?

  • Many machine learning algorithms was around us for quite some time but to handle complex concept they were recently updated this was included to provide the base too big data in a faster way. Machine learning can be said as a subset of artificial learning.
  • There is a huge demand out there for machine learning and thus there would be some reason such as data presentation capabilities, the algorithm for both basic and harder complex problem, an automatic and iterative process which it uses in most of the cases to handle the problem provided, scalability and none other than ensemble modelling.
  • Let’s learn some things which most of us aren’t aware of in machine learning a target is known as a label.

4. Purpose of Machine learning

  • The finance and banking sector have started using machine learning for mainly two purposes which are first to identify the important information out of data.
  • Secondly to use it for preventing fraud known as fraud detection. The information that is obtained from insights of data is used for investment purpose and also to get to know about customer needs.
  • Data mining is used to identify the customer whose profiles are at high risk so that in future if any problem is caused due to them or on them then cyber law can be considered for action. Cyber surveillance is used as a pointer in case of fraud happened.
  • The increased use of mobile technology in today’s world has helped a lot in-stream less transaction to take place all the information that is required can be accessed within seconds through our fingerprints and much more.
  • The only place where we are lagging is human interaction. As due to all machine around the sense of human touch has vanished these are the parts said by the customer as a drawback of our modern world technology.
  • The relationship-based interaction is now not possible. Put the inventors wanted to come up with the idea that could even make that thing possible.
  • To develop a platform that listens to a customer problem, interact and welcome them online, provide the information they need as soon as possible and not only that it could advise them in taking some important decision related to finance, saving, investing etc. there were who found this idea useless as nothing like that could be built. In that regard, the invention of chatbot took place which was capable of all the above activities.

5. Artificial Intelligence Markup Language

As it was a platform designed to understand, learn and even convey a message like a human giving advice to a human. Chatbots have attracted the attention of many people worldwide that what the reason knows many firms have started to show interest in this new technology. There are several advantages of chatbots such as this technology is available for the customer service 24/7 without getting tired and bored that we human mainly are after working for hours. The response to the customer query is provided within seconds without any kind of lag in between. Also, it can handle many customers at the same time without getting confused between there doubts and any sort of delay. The customer history is remembered here and preference is made accordingly as the chatbots learn from customer response each time. The task is performed here in a fast speed. The follow up is made upon the feedback was given by the customer and the relevant improvement is made as soon as possible. It responds to easily understandable language also the customer can ask the same question again and again without feeling any kind of a shame as the technology just don’t get irritated like humans. The same experience is been provided even if you use a mobile, web etc.

Due to the unlimited use of this technology worldwide, the firms have started making personalized chatbots according to the domain they work for. The development of chatbot is done through artificial intelligence markup language (AIML). Fintech world also started showing interest in the technology of chatbots. Several companies have already developed their chatbots using proprietary technology and algorithms. Some website even possesses the payment options also through the chatbots. Financial institution interest in this technology is much more than other domains as various testing is also provided through this portal.

6. Conclusion:

Machine learning emergence in the tech world to support other sector is achieving great heights and thus one can rely on this technology for more innovation to take place in future.

About the Author

BankReed Admin

Banking Professional with 16 Years of Experience. The idea to start this Blogging Site is to Create Awareness about the Banking and Financial Services.

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