The Financial Industry Under the Impact of Digital Economy and Artificial Intelligence

Around 2020, the logic of economic growth and wealth in many countries will change significantly. The world is at the turning point of technological revolution from “informatization” to “intellectualization”. These great changes make many professions present different characteristics from before. The financial industry has been at the top of many industries. What kind of changes will happen in the digital economy? What is the development trend of the financial industry in the future?

1. What is the impact on the financial industry?

But this logic is no longer absolute truth. In the next decade, many employees in the financial industry will face a high risk of unemployment. For example, traditional grassroots positions such as bank tellers and lobby managers will disappear in large numbers. 

In China, China’s four major banks have laid off nearly 80000 people in recent years (Zhang, 2019). Why? Because the bank realizes the intelligent network, all kinds of intelligent machines can now undertake more than 90% of the business.

The former most attractive credit officers also face the risk of being laid off. Like Alibaba’s e-commerce bank, which serves tens of millions of small and micro enterprises a year (12.27 million in 2018), it uses the zero manual intervention lending process based on big data and artificial intelligence technology, which can complete the application within three minutes and receive the loan within 10 seconds. There is not a single credit officer in the whole bank.

Also, investment bank traders and even data analysts are out of work. Goldman uses software engineers to replace traders, and about one software engineer can replace four traders. Now this trend is still spreading. Some studies estimate (Yang, A., 2018) that in the five years from 2020 to 2025, about 10% of the jobs on Wall Street will disappear.

These are not individual cases. Many people don’t realize that finance is actually an industry with a high probability of AI substitution.

Frey and Osborne (2017) did a study, and they calculated the probability that different industries could be replaced by artificial intelligence. According to their data ranking, the probability of AI substitution in the financial industry is as high as 69% on average. 

In addition to credit officers, there are many jobs in the financial industry, such as budget analysts, insurance contractors, accountants, tax inspectors, all of which are more than 90% likely to be replaced by artificial intelligence. By contrast, the probability of service industry being replaced by AI is only 43% on average.

2. Jobs in the financial industry are mostly “codeable”

It’s easy to understand that assembly line workers are replaced by robots, but why industries with high education and threshold like finance are also high-risk industries in the era of artificial intelligence?

This is actually a very different place in this technological revolution of artificial intelligence. Most of the previous technological revolutions (Bessen, 2016) replaced human power with machinery, which did not involve our most proud “brain power” activities. Therefore, most of the positions based on the ability of “reading, writing and calculating” are the “white-collar high-end jobs” in the minds of people in the last era.

But the emergence of “artificial intelligence” began to invade human brain activity.

What is encoded work? The essence of artificial intelligence is actually “data intelligence”, which means that human beings find the rules of behavior, make algorithms, and then rely on massive big data to let computers learn and simulate the process, and then make decisions. Therefore, as long as there are many repeatable details and clear task objectives in the work content of any kind of occupation, it is easy to be coded and programmed by computer algorithm – this kind of work is called “coding” work. In the future, in these jobs, the computer will use the powerful computing power to quickly grasp and optimize these skills through the learning of massive data, leaving human far behind.

For example, data reading, memory, retelling, data analysis, summary – these are originally high threshold human skills, but under the impact of artificial intelligence, these skills will depreciate rapidly, and the skills of related professions will be destroyed in a flash (Xu Xianjun, 2018).

Unfortunately, a lot of jobs in the financial industry are “codeable”. The tellers, financial managers and credit auditors are all highly “procedural” and “process” jobs, such as reading materials, checking reports, making phone calls, reviewing information and evaluating risks according to models. The impact of AI on them is much greater than we think.

3. What will happen to the financial industry in the future?

The answer is No. Because finance is a big industry, there are many sub occupations, and the gap of AI substitution probability of each sub occupation is very large: in the financial industry, about 60% of the positions have a high AI substitution probability, more than 90%, but 25% of the positions have a low AI substitution probability, less than 30% (Wolla, 2018).

In fact, in industries such as finance, all kinds of subdivided occupations present a “pyramid” shape: most of the grassroots to middle-level positions are coded, while a small number of positions at the top of the pyramid are more “irreplaceable”, and the wealth of the industry will be more inclined to these positions.

For example, bankers, most of their jobs are “finding resources, coordinating relations and balancing interests”. These top-level positions are not “Data-Driven”, but “people-oriented”. These skills are just the most non coding and non procedural.

Good fund managers, even quantitative fund managers, are not “dependent on data” as many people think (Pupillo et al., 2018). Data is just their tool and reference. Their decision-making depends on the combination of experience, intuition, decisiveness and judgment, which will not be replaced.

Speaking of this, you may understand. Under the impact of artificial intelligence, a pyramid like career like finance will present two aspects. On the one hand, a large number of positions that can be coded will be replaced, and on the other hand, the positions at the top of the pyramid will get higher profits.

Source of pictures: Retrieved from www.visualchina.com

Reference:

Bessen, J. E. (2016). How computer automation affects occupations: Technology, jobs, and skills. Boston Univ. school of law, law and economics research paper, (15-49).

Carnevale, A. P., Smith, N., Stone III, J. R., Kotamraju, P., Steuernagel, B., & Green, K. A. (2013). Career clusters: Forecasting demand for high school through college jobs, 2008-2018.

Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280.

Official website of Alibaba e-commerce bank：https://loan.mybank.cn/index.html

Pupillo, L., Noam, E., & Waverman, L. (2018). The Internet and Jobs. CEPS Policy Insights.

Wolla, S. A. (2018). Will Robots Take Our Jobs?. Page One Economics®.

Xu Xianjun. (2018). The limits and the future of artificial intelligence. Natural dialectics, 40 (1), 27-32.

Yang, A. (2018). The war on normal people: The truth about America’s disappearing jobs and why universal basic income is our future. Hachette UK.

Zhang. (2019). The bank of China international finance research institute expects GDP growth at 6.5% this year. The Chinese national power, (1), 25.