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Artificial intelligence leads the financial industry to change and create the future bank
Artificial intelligence leads the financial industry to change and create the future bank
Looking back at history, you'll find that the financial sector is the hardest to change. But inevitably, big banks and entrepreneurial companies still made great breakthrough in the financial sector, I think this is not because they use what special technology, but because of their inherent cultural differences, diverse structural stiffness and other cost-effective business model.
In other words, banks do not innovate because they are too large to adapt quickly and follow external incentives, or because they don't know how to (or want) to change. Not only in the financial sector, but also in academia, until the mid 90s of the last century, financial innovation without any breakthrough progress. In fact, in a small amount of survey literature (Cohen and Levin, 1989; Cohen, 1995), more than 600 different articles and books were cited, but none of them was related to financial innovation.
Of course, in the past five years, the situation has changed, but I think this change is passive, not from the voluntary push of the banking sector.
Therefore, financial innovation seems to be generally introduced from the outside rather than internally generated, and more often than not product innovation rather than process innovation (although I think it is controversial). Given the new technology paradigm (which is strengthening the strong causal relationship between innovation and growth), we seem to wonder if a better innovation model can be imported from different industries.
I found a very special and interesting examples, the industry must be "innovation survival", rather than "innovation growth": that is, the bio pharmaceutical industry (Baker, 2003; Gans and Stern, 2004; Fuchs and Krauss, 2003; Lichtenthaler, 2008).
Innovation transfer: biopharmaceutical industry
The biopharmaceutical industry is not a single industry, which includes two different fields: the field of biotechnology, composed of promoting the research and exploration stage of small companies; and pharmaceutical companies, these companies become a huge market and sales of enterprises in the last century.
Therefore, part of it is pure (high-risk) innovation, and the other is purely commercial skills...... It's something we've seen, hasn't it? The pharmaceutical industry and the financial industry have formed a significant polarization
The characteristics of the biopharmaceutical industry are that risk exists primarily in the initial development process rather than in the market sales phase. The problem is not to meet the needs of customers, nor to find the market for your products, but first to develop this drug molecule. The probability of success is very low, the timeline is long (10 - 15 years), and the 20 year patent is just a temporary advantage. More importantly, only about 2/3 of the drugs can offset the cost of development, and most of the companies are at a loss, while the top 3% of the company's profits accounted for almost 80% of the profits of the whole industry, this is a difficult business.
The biopharmaceutical industry is no longer just a human intensive industry, it's an industry that needs a lot of money. But innovation is not an cornerstone of the survival and development of enterprises. This is why they have identified a series of different ways to promote their development of innovation: development, competitive cooperation plan, risk investment, joint ventures, acquisitions, creating a limited partnership agreement etc..
So far, my goal is clear: the financial sector did not feel strongly like the biopharmaceutical industry as the demand for innovation, and it is not to try and push the creation of new mode, to get maximum benefit.
Introduce artificial intelligence, your personal financial subversive
Now you may still think that "innovation is really great, but the financial industry and the pharmaceutical industry two is very different" so why I insist on introducing innovation model from other industries? Well, that's the problem: I don't think they are different.
And the reason they're getting more and more similar is artificial intelligence. Artificial intelligence is injected with a strong innovation in the financial sector, it has a development cycle and characteristics, similar to the biopharmaceutical industry: it takes a long time to be created, and the implementation of the right deployment (of course, the financial industry standard is consistent); it is highly technical, highly specialized talents; it is highly uncertain, because before finding the feasible solution, you need a lot of tests, the artificial intelligence has brought huge pressure of innovation in financial industry.
But artificial intelligence has also brought new development speed and credibility to the financial industry, reducing the similar errors in the biopharmaceutical industry. If your algorithm points out the problem product or the recommended error book, it's very easy. If your system incorrectly interprets some of the signals on the market, or when there is a mistake in developing a drug, you lose millions of dollars in seconds, or even lose your life.
Therefore, it is not only an extension essentially belongs to the problems in the financial sector, such as supervision and accountability, but also brought some new problems, such as biased data or lack of transparency (especially in consumer applications).
Finally, according to the "construction of artificial intelligence vs buy" presents a problem, the problem is even bigger than the last century in 90s the biopharmaceutical industry, reached a peak in the current pharmaceutical biotechnology dichotomy (if you want to know