FinTech, innovation in the banking sector

A new word has emerged in the field of technology and it’s here to stay: FinTech is a portmanteau of financial technology.

According to experts, we are on the threshold of a new model of financial business which can only be accessed through the application of Artificial Intelligence (AI).

As is normally the case, the term is coined after the activity it refers to has been consolidated in the sector. Examples of FinTech at the user level include mobile banking, the foreign exchange market, P2P loans, and digital money such as bitcoin, to name just four examples. What appears certain is that companies doing business in the world of finance have spent years, decades even, trying to apply artificial intelligence to their activities.

In all of these processes, each one exponentially greater with respect to its predecessors, the management of millions of data made it possible for the system to function and for the new products and services to be successful. But we have arrived to the point where traditional computing systems are no longer able to organise this information, or do so in a very costly and inefficient manner. Moreover, companies in the sector need to have an added value to these data. Now they expect to analyse the data quickly and automatically in order to make purchase and sales decisions, change or risk analysis, among other things.

 From the company’s point of view, we are talking about the ability to generate intelligent systems capable of making decisions based on the data they manage and, most importantly, on their ability to connect this information with their experience.

For companies, the application of AI makes it possible to carry out complex operations such as trading, transactions on the foreign exchange market, and to manage digital money, taking advantage of neural network systems which use artificial intelligence. In the case of administrations, the most relevant possibilities are related to controlling fraud: the use of AI permits greater effectiveness in the fight against money laundering which, according to the International Monetary Fund, is equivalent to between 3-5% of the global GDP.

Banks are interested

It is therefore not surprising to note an interest by banks in directing and taking the helm in methodological changes which technology is introducing in their business. For some time now bank board members have been managing the real possibility of having to share part of the profit pie with companies such as Google, Apple, Amazon, or mobile telecommunication platforms, which are developing their own payment systems. But not everything is on the table with large multinationals. Every day we hear about start-ups developing FinTech applications and software which are achieving great international success.

As with all processes of scientific and technological development, advances made today are supported by the work of previous researchers whose achievements have allowed us to count on better, more accessible and stronger calculations tools, new ways of organising and applying knowledge, and developments in algorithms which were until recently unimaginable. This is why growth in the FinTech sector is based not only on the explosion of start-ups, but on the less visible, although equally or more important, efforts of the researchers who work at universities and technology centres.

It is difficult to be fully aware of the arithmetic operations which move the banking sector throughout the world. The transfer of capital alone represents one out of every 10,000 operations, which means that in order to manage that amount of data and to do so effectively and efficiently, it is absolutely critical to use strong algorithms and complex processes which, through the use of Artificial Intelligence, can review 250 banking operations per second.


Artificial Intelligence in other sectors

We in the BISITE research group have been working for years on the application of artificial intelligence in very diverse sectors. One recent case in point is joint effort with other groups in Italy, Ireland, Poland, Portugal and Bulgaria, in which we developed the Opportunities for overcoming the crisis (OTOD) project, through which we provided solutions to improve risk management in decision-making processes, market detection, the application of ID and production oriented to safe selling, among other aspects. All of this was done by applying Artificial Intelligence, which allowed us to obtain a series of indicators with which to organise a risk prevention management model.

Another project in which we successfully implemented Artificial Intelligence is the Crisis Project, in which we worked on designing a system which permits seasonal businesses (such as the construction or hotel industry) to remain in the market and overcome crisis by keeping the greatest possible number of jobs.

Collaborations among businesses, governments and research centres

The goal is a process of learning by doing, adapting legislation to the new and emerging financial business map. These players are not the only ones interested in being the first to impose order in the FinTech ecosystem. In fact, the European Union has already its intentions to do so.

The goals are not smaller than the potential offered by technology. And in this case, as with all cases, the first to venture out will have a tremendous advantage compared with those who follow. Because of this and the magnitude of the goal, collaborative efforts have been imposed in which companies, governments and research groups work together in a coordinated manner.

As researchers, we are counting on the advantage of our experience in the use of these technologies in other fields.

Let´s talk!

Juan Manuel Corchado

Full Professor in Computer Science and Artificial Intelligence, Department of Computer Science and Automation, University of Salamanca, Spain.


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