Artificial intelligence is taking over financial services

(O'Reilly Conferences, CC BY-NC)

Artificial intelligence could become a useful force in the financial services sector, but it could also become a destabilizing force posing a threat to the global financial system.

In the past, dominant market institutions were created on the basis of the scale of assets, mass production, exclusive relationships, high costs of changes, and the dependence on human ingenuity. At present and in the future, institutions are and will be built on the scale of data, the experience of the product or service users, and on the optimization of digital connections, in conditions where human performance will be supported by technology.

It’s more accurate than humans

Artificial intelligence (AI) is fundamentally changing the financial services sector. It is weakening the existing links between financial institutions. At the same time — as pointed out by the World Economic Forum — it opens up the possibility of entirely new operating models and introduces new rules of competition, which will be much more favorable to institutions focused on the scale and complexity of data than to those focused on the scale or complexity of capital. As a result, the potential of AI constitutes a major challenge for the traditional economy and society.

Institutions that will be the first to introduce AI to financial services will be able to take advantage of its data-driven potential, benefiting both the front office and the back office. This will have a significant impact on the companies’ strategic approach to market cooperation, infrastructure development, and talent management.

Artificial intelligence is no longer seen merely as an element of science fiction. It is now seen as a mathematical approach to the development of self-perfecting regressions, known as machine learning. One subset of this discipline covers neural networks, which are a method of processing data — for example, by solving complex tasks on the basis of large data sets. It turns out that neural networks make fewer errors in solving problems than humans. Moreover, artificial intelligence can also be used as a creative ability to quickly develop ideas or to perform emotional tasks.

Artificial intelligence requires hardware with huge computing power and datasets with millions of rows, containing information about various kinds of human activity. These resources have been created as a result of the development of the computer network during the recent decades. While there are currently more than 7.6 billion people in the world, there are already more than 20 billion intelligent computing devices, supported by the cloud-based data storage market worth USD100bn. Thus far, venture capital has been investing USD5-10bn per year in machine learning companies, attracting both human and financial capital.

It will assist us at our homes

According to Autonomous Research, due to the development of AI in financial services, within the next 10 years the financial industry will save USD1 trillion in costs by automating certain activities.

In particular, the most important factor limiting the rate at which institutions implement artificial intelligence will be the transformation of skills. This will pose a threat to the competitive position of both companies and countries that cannot cope with the demand for skills resulting from the progress of technological investments.

For example, in the United States approximately 2.5 million workers in the field of financial services are exposed to the impact of these technologies. According to the “Machine intelligence & augmented finance” report, financial companies see the biggest potential savings — to the tune of USD490bn — in the field of direct customer service. At the same time, one possible scenario — albeit rather unlikely — is that instead of lowering costs, the new technology will lead to improved productivity. This would mean that employees keep their jobs and are trained to perform advanced, creative or emotional tasks.

It is currently difficult to predict the future of AI in financial services. In one potential development scenario, the large technology companies dominating on the market will continue to add and improve the skills of their smart home assistants, such as Amazon Alexa, thereby supplanting the financial companies. Another possible direction of development is the one exemplified by China, where technology and finance are being combined in order to build full psychographic profiles of customers, based on social, personal, and financial data. Another potential path of development are decentralized autonomous organizations that are built by the cryptographic community in order to give power back to individuals, with skills derived from the component parts created on the basis of an open source code.

It carries a certain risk

In each of these cases, an important role would be played by the proper understanding and regulation of the ethical issues and issues concerning data privacy.

The laws governing privacy and the possibility of transferring data will affect the ability of financial and non-financial institutions to implement AI solutions, thereby becoming as important as the traditional regulations for the competitive positioning of companies. The evolution of data regulations around the world will therefore be a key factor determining the role and position of various players in the field of financial services.

The global regulations concerning data are currently undergoing significant changes, as countries are introducing new rules in order to protect and empower their citizens. For example, the purpose of the European Union’s revised Payment Services Directive (PSD2), which entered into force in January 2018, is to enable more innovative payments across Europe. Together with the General Data Protection Regulation (GDPR), these laws will force institutions to adequately balance the requirements for sharing data with third parties, as they will be threatened with the possibility of substantial fines in the event of improper data management.

Further challenges related to AI are associated with cyber threats. In order to prevent such operational risk, financial institutions will have to develop strategies to mitigate the growing risk of fraud and leakage of confidential information both at the customer’s level and at the transaction level, as well as the risk of increased dissemination of sensitive information.

Additionally, due to the fact that AI is playing an increasingly important role in the everyday functioning of the financial system, it constitutes a new source of systemic risk. Without proper supervision, innovations in the field of artificial intelligence could introduce new threats into the financial system and could increase the risk of contagion. As a result, AI will force institutions to reanalyze the existing rules and techniques of supervision and regulation — including financial supervision and regulation — in order to avoid a possible disruption in the economy.

Artificial intelligence could have a transforming effect on the global financial system, but it will only be possible to maximize its benefits if the social structures and processes are adapted in order to support new ways of working, and if the emerging risks are simultaneously minimized.

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