The current crisis of the coronavirus will reveal, sooner than expected, the penetration of cutting-edge technology in all sectors and products especially in the financial sector, since this sector has been traditionally conducive to innovation and change. Innovation will change the fact that many of the leading companies in the industry continue to stand out because they heavily rely on interpersonal relationships and a lack of transparency. Automation will lead to this change through the adoption of artificial intelligence in the financial industry.
Artificial intelligence with machine learning is expected not only to enhance the processes and transparency but also to improve the relationship between financial advisors with clients.
This will be done because the overriding feature of artificial intelligence is that it will be able to provide services for all clients at a low cost. Using AI with machine learning, we can understand the real needs of clients in the whole spectrum of the customer base. Thus, financial companies will not be focused on a small number of clients. It will be able to provide solutions to the broad spectrum of clients by expanding, in reality, their customer base even if they keep the same number of clients that they had.
Today, financial companies spend billions investigating and researching the possibilities of AI and machine learning. Their target is to find ways in which artificial intelligence can enable the creation of new products, improve existing business areas and improving business processes, as this will give them a competitive advantage.
Even the financial companies that do not have a robust back office will significantly benefit from the development of AI in both CRM management and risk management.
It is evident that with the development of AI, financial companies will require more sophisticated ways of supervisory monitoring in the future.
It is also apparent that the integration of artificial intelligence into human relationships poses ethical and regulatory challenges, such as if decisions affecting customer wealth should be entrusted to a machine. Such issues need to be addressed as it will become apparent soon that the financial services sector will integrate artificial intelligence by creating a new landscape, dominated by platforms, that will utilize the capabilities of machine learning.
However, this development could create systemic risks at a global level as regulators are not ready to deal with such issues as well as other critical issues. For example, a significant problem in the future will be that it will not be easy to explain to the supervisory authorities the mechanism of decisions used, due to the multifaceted nature of machine learning. Another problem that can arise is the possible over-dependence on artificial intelligence. Also, artificial intelligence could, in conditions of financial uncertainty, lead to coordinated risk hedging, thus creating dynamic trends that are not beneficial to financial markets. The more the markets become homogenized, the more they become more fragile. Moreover, the inability to understand the mathematical models used by the artificial intelligence can, as in the past, lead to a crisis since the use of sophisticated and little-understood mathematical models caused the global economic crisis of 2008.
On the other hand, the positive impact of artificial intelligence can be multifaced. In the current coronavirus crisis the data analysis with the use of AI and machine learning, has enormous value on the research that scientists are doing to find the appropriate medicine and vaccine, against the coronavirus disease.
Obviously, moral dilemmas arise, such as to whether patients' personal data can be used in research. Similar dilemmas will be raised in the financial sector. However, a new reality for humanity is being created, as we are moving to a trans-human era.
Regulators should be ready to face new challenges to deal with this new era as most likely, artificial intelligence will increasingly penetrate human activity, research, and business development.
Artificial intelligence should be used as a tool that machine learning specific functions, are understood by both companies and supervisors. If this happens, then it will act as a very critical factor in the new era after the crisis of coronavirus, as it can offer effective solutions for the creation of new structures in the innovation and enterprise economy, offering the maximum in the economic recovery.
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