Artificial Intelligence, the next key in the banking transformation
Artificial intelligence (“AI”) has represented a drastic change in the technological revolution, reaching many industrial sectors. To date, it continues to be an enigma for many people, since, on many occasions, we would only associate it with humanoids and robots product of fiction. However, there is much more to it than that, for example: a network of business solutions that are changing the way of doing business, including banking.
We begin this article with a short definition of Artificial Intelligence, followed by a brief repository of the different types of artificial intelligence and some applications in the financial industry.
Definition of Artificial Intelligence
According to Gordon Scott, “Artificial Intelligence refers to the simulation of human intelligence in machines that have been programmed to think like humans and carry out activities similar to these.” It is worth mentioning that the term also covers a machine that is associated with a human mind to carry out some activity, such as learning (also known as machine learning).
Understanding Artificial Intelligence
The reason why most of us first think of robots when we hear the term Artificial Intelligence is because of the big-budgeted and fascinating work of TV series and novels, but nothing is further from reality.
With the advance of technology and the advance of artificial intelligence, we find an endless number of benefits and applications of AI in all industries, most of the times not in the form of hardware. AI is an example of what a true modern technological tool is, especially in the financial sector.
In 1987, Warren Buffett, the biggest investor of its time, wrote in a letter to shareholders in Berkshire Hathaway, “In my opinion, the success of investments will not be produced by the formula sand, it will be the computer programs that anticipate market price signals according to the behavior of stocks and market.” Thirty years later that prediction became a reality. Since the year 2016, Aidyia, a fund investment company located in Honk Kong, has based its investments on algorithms. Incredibly, the company is fully automated without the help of any human intervention.
Marvin Minsky, one of the pioneers in the field of Artificial Intelligence, defines it as “the science of getting machines to do things that require human intelligence to do them” (Minsky, 1968).
It is no surprise that banks are adopting Artificial Intelligence in an endless number of ways. Big banks are entering a fast race for the adoption of different technologies, such as AI, Blockchain, and Big Data just to mention the most important ones. However, just implementing new technologies first does not mean that they will generate added value in the short term, as their premise can be false. Banks need to continue to innovate to ensure the best possible results and to better address its necessities, which include improving the user experience for each client. In this regard, Banks see Artificial Intelligence as a way to help and provide a hyper-customization of services offered by automatic monitoring and improvement of back-office operations.
Different types of Artificial Intelligence.
According to Deloitte, there are different types of artificial intelligence:
· Machine learning
This refers to a computer system where the performance of a task or activity improves through experience and exposure to added information. The critical element here is that the machine represents the ability to perform the activity and improve without the need to follow any instructions.
Some examples of applications in the financial sector include fraud prediction or trading recognition.
· Autonomics
Autonomics refers to a system that is capable not only of learning to identify new patterns of information with a data store but also to perform tasks or activities with a human being.
The systems here are not only capable of recognizing an incident or a pattern of incidents but can also be implemented in the routine to resolve such an incident.
Some examples are the execution of a credit risk analysis through software.
· Machine Vision
Machine vision refers to the ability of a computer to recognize and identify objects, subjects, activities in images. This machine may be able to classify undefined objects as something the computer recognizes.
An example of the use of Machine Vision may be the recognition of a user’s approval of some asset.
· Natural Language Processing
This is where the computer can process and interpret human language and respond appropriately.
An application of this type of AI is the review of legal documents within a financial institution. This type of AI can help analyze large volumes of legal documents within seconds.
Banks are forerunners in automating their compliance processes, and in the case of searching and reviewing an extensive volume of documents, artificial intelligence can be especially beneficial, saving time and costs. Improved search capabilities can allow compliance officers to find relevant information among thousands of digital documents quickly without the need of human efforts.
Computers with artificial intelligence are capable of making decisions faster than any human. This can be a great tool when the matter in question involves large volumes of data to consider for said decision.
Disruptive Capacity
The most prominent players in the financial sector are increasingly facing disruption in a market full of innovative solutions. Now, according to a KPMG report called “the pulse of Fintech 2020”, with the recent arrival of Fintech companies, the global financial sector has changed and expanded. BigTech has increased in value by more than $2 billion according to different reports from the same international consulting firm.
Today, we see also see support from governments to these matters, such as the case of ADGM (Financial Services Regulatory Authority), which launched three projects that included artificial intelligence in the improvement of regulatory processes through Regbot systems.
Customization
In the services that are provided by banks to individual customers, Artificial Intelligence has a great potential to massively expand the boundaries of the interfaces. This can be possible through automated and intelligent customer interaction using Machine Vision.
Certain products can be offered due to customer behavior using Netflix or Spotify, just to mention a few platforms. This simply has a great future in improving the banking customer experience.
Regulatory challenges of Artificial Intelligence
Improving processes through artificial intelligence can be excellent; however, just as AI brings us benefits, it brings as well many challenges. The use of this type of technology is a whole new test for regulators.
One of the problems is the dislocation between the need for transparency in financial regulation and, on the other hand, the impenetrability of information that the use of an artificial intelligence system can represent. The more advanced these systems are, the most difficult it becomes to know and understand the result of a machine’s decision-making process. That makes it difficult for the regulator to determine the rules and regulations applicable to AI systems.
Conclusion
Today Artificial Intelligence brings the financial industry many benefits, including cost reduction; new, improved, and customized services; as well as better customer experience.
Artificial intelligence has the potential to change the way business is made around all sectors of the economy, and finance is at the forefront of this exciting change.
The adoption of artificial intelligence in the financial sector is constantly changing, providing better-personalized customer experience and increasing the opportunity for further growth. In the meantime, regulators will require to do their best to understand the necessities and challenges of such technology, and provide flexible and adaptable rules to match the ever-changing landscape of AI.
For more information you can contact:
Diego Ramos Castillo. dramos@rrs.com.mx
Antonio Casas Vessi. acasas@rrs.com.mx
Rodolfo Ramos Ortiz. rramoso@rrs.com.mx
Arturo Canseco Álvarez. acanseco@rrs.com.mx
Guadalajara | Américas 1500, piso 14, Col. Country Club, Guadalajara, Jalisco, México +52 (33) 3627 5035 + 52 (33) 3121 3014.
Mexico City | Torre Esmeralda I, Blvd. Manuel Ávila Camacho 40, Piso 14, Lomas de Chapultepec, V sección, Miguel Hidalgo, 11000, Ciudad de México + 52 (33) 1518 0445 + 52 (55) 6823 3004
Digital Resources:
Minsky, M. 1968, Semantic information processing. Cambridge, MA: MIT Press.
ARTIFICIAL INTELLIGENCE 2020 5
https://becominghuman.ai/a-simple-introduction-to-natural-language-processing- ea66a1747b32
https://home.kpmg/xx/en/home/insights/2020/02/pulse-of-fintech-archive.html
https://home.kpmg/xx/en/home/campaigns/2020/02/pulse-of-fintech-h2-2019.html
https://www.weforum.org/projects/generation-ai
https://www.weforum.org/platforms/shaping-the-future-of-technology-governance-artificial- intelligence-and-machine-learning
https://www2.deloitte.com/content/dam/Deloitte/pt/Documents/strategy/2lu-intelligent- automation-business-world.pdf
https://www.adgm.com/media/announcements/fsra-launches-regtech-initiatives https://fortune.com/2020/01/20/natural-language-processing-business/
https://www.accenture.com/_acnmedia/PDF-94/Forbes-Accenture-Avanade-Microsoft-AI- Research–Full-Report.pdfrule
https://wam.ae/en/details/1395302838113.
