Artificial Intelligence: Is it really the solution we were hoping for, or the start of new challenges that need to be dealt with? | NTT DATA

Thu, 26 November 2020

Artificial Intelligence: Is it really the solution we were hoping for, or the start of new challenges that need to be dealt with?

Artificial Intelligence is a little bit of both. It has come to stay and has experienced such an advance that its direct applications are more present than ever before both in our daily lives and the way we do business. Advances such as NLP or Machine Learning have disrupted the financial sector.  However, along with these new advances, ethical challenges also emerge.

When you hear the words ‘Artificial Intelligence’, what is the first thing that comes to mind?  Something sinister or something kinder, friendlier, and fun? Will the prospect of AI really bring a dystopian future or should we be embracing the benefits of this technology as a force for good? After all, despite being “artificial”, it is also supposed to be “intelligent”, and that which is intelligent is supposed to be good, right?

But can we trust it? Well, before I answer that question, let us delve a little deeper into what AI actually means…

If I pull out my iPhone and ask Siri to read me the definition of ‘Artificial Intelligence’, “she” will tell me that it “is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages”.

AI’s origins can be traced back to 1950 when English mathematician Alan Turing wrote a landmark paper titled “Computing Machinery and Intelligence” that asked the question: “Can machines think?”.  As a result of that paper, further work came out of a 1956 workshop in Dartmouth, England where the  “Artificial Intelligence” term was coined.

But how do we see AI today? Well, in many cases, in our own pockets. On our phones, intelligent digital personal assistants such as Google Assistant, Siri, and Alexa come packaged as standard on mobile operating systems such as iOS and Android. We can use them to set reminders, take notes, calendars, and much more. In short, they help us find useful information when we ask for it just by using our voice.

In recent years, AI has also taken many other shapes and forms such as GPS, photographic enhancement, and robotics.  Google has become a major player in AI transcendence and Deep Learning which is basically another name for machine learning based on algorithms.

Several AI applications are also appearing in the financial sector which are helping to improve internal transformation (operational competitiveness, organisational advantage, and innovation) and business methods (new models, new products and services, and customer experience).

Successful implementation of AI depends on collaborative innovation which encompasses several different areas of action. The most important of these is crowdsourcing which is the outsourcing of microtasks. When carried out on a large scale, this benefits the financial institution and accelerates the process of innovation. This is especially important for banks as it allows them to reinvent themselves to remain flexible.

With the rise of AI in the financial sector, it is clear that there are multiple benefits to these institutions which can be used to optimise every part of the value chain from client interactions to market analysis, process functions, and risk control and monitoring.

But how can financial institutions capitalise on the value offered by AI? Understandably there is a certain degree of hesitation to implement these technologies into their processes, but the benefits definitely outweigh the cons as seen through the growing number of AI applications focused on banking operations in areas such as risk management, regulatory compliance, operations, commercial banking assets management and corporate banking as well in key business processes such as credit rating and granting, the prevention of money laundering, improving the customer experience and portfolio management.

AI is a broad discipline in which different sub-fields and techniques are combined. Machine learning, deep learning, robotics, representation of information, the processing of natural languages, and computer vision are among the most common. These are not isolated branches, however, and they also overlap and connect.

A highly evolved branch of artificial intelligence is natural language processing. To allow machines to understand and communicate with the verbal or textual language of individuals, NLP integrates computer science, linguistics, and machine learning. In industries ranging from text translation to automotive, aeronautics, smartphones, and healthcare, it has many applications, some of which were mentioned earlier in this post.

Banks' investment departments are using NLP techniques to analyse financial documentation. Some U.S. banks have incorporated conversational devices, known as chatbots, to assist customers. It is also used to identify the market sentiment based on a company's results or a given investment situation.

As ever, when a new technology is implemented along come certain risks and AI is not unique to this. Indeed, the implementation of AI can lead to discrimination infringements on privacy such as facial recognition. The best way to deal with risk is to understand them and therefore it is important to understand the ethics behind the use of AI and the algorithms used behind their programming. Without this precaution, automated decisions can discriminate again certain population groups based on ethnic, social, or other features excluding them from access to credit, for example.

Artificial intelligence biases can affect any industry or sector of business. One example of this was seen in 2014 when the algorithm governing Amazon’s recruitment process for technical programmers overwhelmingly favoured men. Therefore, it is important to guarantee that automated decisions do not generate unfair discrimination based on race, ethnic origin, religion, gender, sexual orientation, or any other feature. Transparency is key here and even more so in the financial sector as there is not only a growing sensitivity but also hesitation when AI features are implemented into their systems.

AI is undoubtedly the leading-edge technology that shows the most promise for use in the industry, even amid the exceptional current circumstances brought about by the Covid-19 pandemic. Its advantages are evident from both the perspective of enhancing operational efficiency, as well as the benefits it offers for improving products, services and the customer experience. Furthermore, when managed with ethical and responsible criteria (so-called “trustworthy AI”), artificial intelligence is an opportunity to bring additional value to companies and contribute to the well-being of citizens and society as a whole. AI is not the future, it is the now, and it is changing our lives and transforming how we live and work in ways that we only ever imagined possible in science fiction.

Learn more about AI in banking reading our “AI in the Financial Sector Report”. Free downloading here

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