Impacts of Artificial Intelligence on FinTech
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Impacts of Artificial Intelligence on FinTech

With the development of artificial intelligence algorithms, the added value they provide to industries has increased significantly in recent years. That's why banking and finance industries are partially obliged to realize the digital transformation due to the increasing threats from next-generation FinTech enterprises. Technological transformation in these industries is delayed because of compliance and regulations, and old-fashioned, bulky systems are no longer satisfactory to meet customer needs. However, as the industry leaders attach importance to digital transformation, things will change faster than expected.


Main areas requiring digital transformation are the increasing costs, operational efficiency, changing customer needs, and inevitable evolution. Recently, another factor that comes to the fore a little further than all these has emerged, and it has the potential to develop the related industries much faster: artificial intelligence! It is a well-known fact that artificial intelligence carries the industries it touches far beyond their time. It is not only limited to industries; artificial intelligence has also set its eyes on some professional groups. In the near future, drivers in the road transport industry will face the danger of unemployment. With the help of artificial intelligence, e-commerce sites can say "customers who bought this item also bought that item" or show their customers the products which are not in their area of interest yet. Amazon aims to set the cargo on the road even before the customer decides what he/she wants, in the near future.


An interesting anecdote of artificial intelligence has recently taken place in the world of chess. This game is estimated to have a history of 1,500 years. For over 1,500 years, chess masters have developed techniques for the game, and they have made efforts to become the best by guessing beyond dozens of moves. The period 1995-96 is kind of a milestone for chess. When IBM's supercomputer Deep Blue defeated world chess champion Kasparov, its superiority to the human mind was proven for the first time. Of course, it was hard to talk about artificial intelligence at that time because Deep Blue did not have a learning structure. It started each game from scratch and couldn't make an estimation over its opponent's moves in the former games.


In 2017, the world of chess experienced a new milestone. Guided by Deep Blue, engineers and chess masters developed the open-source software called StockFish and this software was nominated to be the best in the world by the chess community. While Alpha Zero, on which Google directed its artificial intelligence research, was not even aware of chess, a game was planned with StockFish. Google engineers taught Alpha Zero the rules of chess, and Alpha Zero developed chess knowledge by playing chess by itself for 4 hours. Subsequently, 100 games were played between StockFish and Alpha Zero, and with 28 victories and 72 draws, Alpha Zero tore down the 1,500 years of knowledge, opening and closing strategies. (A note for chess lovers: 25 of 28 wins were with White and three with Black.) Can you imagine what artificial intelligence achieved with only 4 hours of practice? More precisely, can you imagine to what point artificial intelligence can carry the humanity when it is used properly?


The main objective of FinTech is to create value and achieve competitive advantage by using data and predictions. It is highly possible to create scenarios and make predictions about the future when there is high-quality, clean and significant data. The quality and the significance of the data used by predictive algorithms brings along some doubts. As these algorithms do not have sufficient data extraction capability, unexpected situations may occur. With the expansion of artificial intelligence solutions, even small-scale companies can compete with global giants. The most important priority of the FinTech world is to estimate customer behavior. The answer to questions such as what the customer will want to buy in the next shopping experience or if the customer will be able to pay the loan on time is hidden within the data. Algorithms are capable of responding to such questions through prediction, but it is unlikely to link their response to a reason. Therefore, artificial intelligence is not a decision maker, but it works much more efficiently in roles that support decision-makers.


One of the target areas of the finance industry is fraud. Particularly, due to the security gaps in online transactions, cyber hacker attacks are focused on these types of transactions. Banks and other financial institutions are also planning security measures to differentiate real transactions from fraudulent ones. The algorithms developed against fraud are trying to identify situations that are not similar with past transactions. For instance, there are routine controls such as whether the device used is the same or the country/location where the customer previously shopped is similar. Of course, these algorithms can capture fraud, but when the customer buys a new device or travels abroad, it can also lead to negative customer experience.


As the amount of data processed by artificial intelligence algorithms increases, certain patterns are formed, and the algorithm develops itself by learning and becomes ready to protect itself against potential attacks. Widely used image verification, fingerprint readers and face recognition technology of next-generation phones are additional aspects that can support this algorithm.


The impacts of artificial intelligence on communication with the customer have been highly observed for the last 10 years. The latest product in this area was ChatBot. Both next-generation FinTech initiatives and traditional banks have implemented ChatBot applications and have taken a big step towards efficiency in customer communication. Although it is claimed that ChatBots will replace call centers in the future, this does not seem possible in the near future. Especially as generations Y and Z are familiar with mobile communication and prefer texting to calling, it will be increasingly used in communication with these generations. Amexbot, developed by American Express, and Bank of America's ChatBot application ERICA are considered as industry-leading applications with integrated analytical forecasting features.


Although artificial intelligence promises great opportunities in terms of cost advantage, efficiency and decision-making when used appropriately, many industries are not yet ready to adopt this technology. Because the security-oriented financial sector is exposed to cyberattacks or misusage, its interaction with artificial intelligence will probably take more time than expected. In 2013, an automatic tweet was sent on the death of Barack Obama when the Twitter account of Associated Press, one of the world's most well-known news agencies, was hacked. The cost of 3-minute financial turbulence caused by serving unverified data from a reliable source was estimated to be $136 billion.


Until recently, artificial intelligence was merely SkyNet in Terminator films for all of us. It is possible to say that with the technological revolution we have been experiencing in the 2000s, it has made through its initial stage. Artificial intelligence is increasingly used more commonly and is recognized in almost every industry today. The substantial benefit it provides is that it enables small and medium-scale companies to compete with technological giants. In FinTech, it is difficult to say that artificial intelligence will replace people in the near future, but it is not hard to predict that it will be critical in supporting decisions. Both decision-makers at companies and end-users will benefit from the advantages offered by artificial intelligence within the next 10 years.


Through customer loyalty applications developed on PayFlex platform and ChatBot application, it is possible to embrace the future of customer communication in advance. PayFlex ChatBot application, which provides the customers with the right guidance by understanding customer demands and is equipped with information, order tracking and similar features, paves the way for next-generation customer communication. In the scenarios where loyalty applications are integrated with ChatBot, it is up to you to achieve loyal customers by providing high customer satisfaction at all points of contact.