Fintech – Artificial intelligence has become increasingly crucial in various sectors of business, including FinTech. AI is revolutionizing the FinTech industry by driving innovation and propelling businesses to new heights. It is redefining traditional financial technology in a significant way. Our focus will be on exploring the contribution of AI to the advancements, achievements, and breakthroughs within the FinTech industry.

FinTech, AI and Banking

Machine learning has the potential to enhance FinTech intelligence significantly, despite the fact that prior to this era, AI was only minimally utilized. Why was AI not made accessible to the general public and kept as a highly intricate topic only found in PhD-level materials? It is possible that we will need to await another pertinent blog entry, potentially due to certain circumstances.

In this context, we won’t delve into the specifics of how blockchain is connected to AI and fintech. One possible rephrased version could be: The integration of an unalterable sequence of machine states, linked to data blocks within neural network training settings, could act as a playback tool for human cognition to understand artificial intelligence.

Role, Discovery, Invention and Innovation !!

The role played by any discovery, invention or innovation in the FinTech industry has its own meaning and importance. Now if we just touch upon blockchain a little bit. When economically feasible, blockchain would potentially disrupt contemporary thinking about ‘Opaque’ vs ‘Transparent’.

  • Artificial Intelligence and Data Science Technologies – Data Science of FinTech deals with both structured and unstructured data. This provides insights in a well-organised manner that combines the programming, logical reasoning, mathematics and statistics. AI is an umbrella of several techniques that are used for extracting the information. AI module data science is responsible for the creation of data products and several other data based applications that deal with data in such a way that conventional systems are unable to do so.
  • Digital Age of financial transactions – As smartphones become a bigger part of our everyday lives, it’s only natural that we will use them more and more for shopping. Studies seem to back up this simple reflection. Business Insider expects mobile commerce, also known as m-commerce, to reach 45% of total e-commerce sales by 2020.
  • Machine Learning to Demystifying FinTech – In this modern world technical revolution has taken place thus artificial intelligence and machine learning has come into existence because of its accurate predictions. Algorithms are built through which input is received and after statistical analysis output value is predicted. Because the algorithms are trained from the dataset and thus learn from data, finally improved results are predicted. Furthermore, the improved functionality of computers.
  • Global currency disorders are on the rise – Think of what’s happening in India, where the government recently scrapped 86% of cash in circulation. Zimbabwe in 2008 and Venezuela in recent, where the currency is so devalued people now need to carry stacks of cash just to buy food. As a result, many retail investors are turning their attention to digital currencies, as well.
  • Financial Inclusion to improve people life – Africa is the land/Home of Mobile Money and Mobile is most frequently used and widely acceptable technological device than any other. Financial services are a key need for most people due to almost less negligible banking penetration and it makes sense to enable Mobile devices with a set of financial tools and features as mobile handset penetration is more than 10 to 15 times higher than banking.
  • Mobile devices in the Finance sector – The evolution of mobile devices has helped FinTech to grow at a rate which is unmatchable in the finance sector. Fintech takes advantages of mobile devices to penetrate all classes of society so the birth of mobile money. Addressing the opportunities of mobile money in today’s rapidly changing environment; MNO’s, FSI and technology providers face the challenges of strategy design and modelling through operational efficiency, management of partnerships, risk, compliance and regulatory complexity are getting easy to handle

FinTech Amalgamation with Powerful Artificial Intelligence

Artificial Intelligence is a field that includes everything that is associated with the data (cleansing, preparation, analysis and many more), Learning processes to describe, diagnose, predict and prescribe with use of AI subfields like Machine Learning, Deep earning and Neural networks. Machine learning is a field of Artificial Intelligence, which is allowed to software applications for making accurate results.

Use of big data and artificial intelligence – specifically machine learning has made it possible to lend money profitably to underserved segments of the population. I will describe more in details about how “Big Data” can help for Small Credit to improve underserved community life in my upcoming post. This is a very important development in financial inclusion by AI.

Using artificial intelligence to make loans in emerging markets which have reported some performance information are yet to come to light but surely with lots of confidence, I can say this is the way to go.

Artificial Intelligence Demystifying FinTech

However day by day AI will gain more and more attention in industries.

Thus first of all as engineers, we should be well known to these advanced techniques of AI spectrum i.e machine learning and its algorithms. We should be aware of what is machine learning? It captures data in the most ingenious ways and encourages the ability to look at things from a different perspective.

FinTech is known through the help of AI that, in one way or another how to make money. The application of any computer-enabled algorithm that can be applied against a data set to find a pattern in the data. Because of this, new wild and flashy AI systems that are making FinTech ‘s smart systems smarter and can help them to fly.

Not surprisingly, these companies each have a clear market application and reduce friction in the business problems they address. Fintech’s Artificial Intelligence revolution is a perfect example and the era of pervasive AI financial technology services.

Chatbots in FinTech, Banking and much other business for speech processing which is basically time series analysis using RNN/LSTM deep neural nets also have to be trained on known ‘good speech’. For example, one strategy is to train the RNN not only for content but also for simple conversational English using existing datasets may be old film scripts.

Companies in the FinTech industry will find multiple opportunities to enhance decisions on lending, such as how to optimise financial advising or execute better trading decisions. AI could also help improve the algorithms to create optimal financial advising.

Despite the enormous technological and political difficulties involved in upgrading AI  core developers have finally introduced real benefits of AI to the network of professionals who really understand and can make use of it in Fintech.

The benefits of AI and blockchain like technologies are clear: a higher transaction throughput without altering the block size, no transaction malleability and faster block validation. AI  also makes it easier to develop better wallet software and permits off-chain transactions on the lightning network, a protocol for scaling and speeding up blockchains. Though AI and Blockchain have a basic architectural model difference.

Points to Note:

All credits if any remains on the original contributor only. We have covered all basics around mobile payments security and the importance of mobile payments data. In the next upcoming post will talk about implementation, usage and practice experience for markets.

Books + Other readings Referred

  • Research through open internet, news portals, white papers, notes made at knowledge sharing sessions and from live conferences & lectures.
  • Lab and hands-on experience of  @AILabPage (Self-taught learners group) members.

Feedback & Further Question

Do you have any questions about AI, Machine Learning, Data billing/charging, Data Science or Big Data Analytics? Leave a question in a comment section or ask via email. Will try best to answer it.


Conclusion –  We expect that over the next year there will be more information emerging on how advanced technologies like AI and its subfields will help Financial Inclusion, FinTech and banking based on actual performance, and based on the ability of some of these early-stage businesses to raise additional funding. 

We should see in the next couple of years a vast improvement in current state-of-the-art machine learning role in cyber-security, payment intelligence and info-security intelligence. Instead, business silently gravitates toward the subtasks that have implicitly performed. With technology advancing at breakneck speeds and demystifying robotics and artificial intelligence role in new applications, machinery, and ultra-fast process in business, factories and homes in short from teleportation to autonomy.

#ArtificialIntelligence #MachineLearning #PaymentIntelligence 

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Posted by V Sharma

A Technology Specialist boasting 22+ years of exposure to Fintech, Insuretech, and Investtech with proficiency in Data Science, Advanced Analytics, AI (Machine Learning, Neural Networks, Deep Learning), and Blockchain (Trust Assessment, Tokenization, Digital Assets). Demonstrated effectiveness in Mobile Financial Services (Cross Border Remittances, Mobile Money, Mobile Banking, Payments), IT Service Management, Software Engineering, and Mobile Telecom (Mobile Data, Billing, Prepaid Charging Services). Proven success in launching start-ups and new business units - domestically and internationally - with hands-on exposure to engineering and business strategy. "A fervent Physics enthusiast with a self-proclaimed avocation for photography" in my spare time.

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