Artificial intelligence and machine learning: a new blueprint for the financial technology industry

Artificial intelligence and machine learning: a new blueprint for the financial technology industry
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Companies are not taking full advantage of artificial intelligence and machine learning.

There is no doubt that artificial intelligence (AI) and machine learning (ML) are becoming hot topics in the financial technology industry. In almost all seminars and conferences, we heard news about the rise of these emerging technologies and their potential to disrupt business.

Obviously, artificial intelligence and machine learning are the blueprints on which the financial technology industry relies. However, it is obvious that no matter how the influence of financial technology artificial intelligence on enterprises is hyped up, because many companies cannot visualize, integrate and adopt these new technologies, it is still not fully utilized by these companies.

Recently, many industries have started a lot of conversations about the potential of these technologies, but according to Accenture research, 87% of business leaders in the UK are struggling with their adoption issues.

This is not to say that people do not understand the importance of achieving strategic priorities. Indeed, three-quarters of executives believe that if they do not expand the scale of artificial intelligence in the next five years, they may close their doors.

Nevertheless, there is still a gap between “hype” and “actual implementation.” Less than 5% of companies have successfully industrialized artificial intelligence, while 80% to 85% of companies are looking for scattered proof-of-concept products-in this case, the power of artificial intelligence and machine learning is often Out of touch with business results or strategic requirements. Many companies do not take full advantage of the full potential of emerging technologies, thus limiting their business impact.

With a large amount of historical data and structured data, financial technology provides fertile ground for artificial intelligence and machine learning technologies to generate customized products and solutions, thereby helping companies improve profitability and save costs. So why do companies usually adopt, implement, and expand emerging technologies slowly in short-, medium- and long-term strategies?

Embrace the benefits of artificial intelligence and machine learning

Due to the lack of technical knowledge (from an integration perspective and due to people’s limited understanding of business value), many companies are slow to adopt artificial intelligence and machine learning.

It is important that companies work with the right people to debug artificial intelligence and machine learning products and solutions that have real business benefits and impact at the customer level.

As a former Silicon Valley technician and research engineer of a large technology company, I found that these technologies can play a vital role in the operation of the entire enterprise. Companies can find opportunities to save costs while improving efficiency, so that the chief financial officer can more easily assume the key role of company growth.

Companies can discover opportunities that fail to fully accelerate their daily activities and processes by combining artificial intelligence and machine learning technologies. These technologies enable customers to make more informed decisions and operate more efficiently. At the same time, emerging technologies will increase development opportunities, thereby helping global business development and helping companies flourish in an international environment.

Recent research has pointed out that executives are not trying to expand artificial intelligence because of budget constraints, but the operational challenges of integrating these technologies into current business processes. There are many obstacles to using artificial intelligence and machine learning within the organization, such as the inability to establish a strong organizational structure, the lack of basic data functions, and the lack of full adoption among employees.

It is these factors that distinguish companies that have successfully expanded artificial intelligence and machine learning from companies that simply pursue proof of concept. Business owners must not only consider the adoption of artificial intelligence and machine learning as part of their business strategy to enter the market, but they must also actively integrate these technologies and encourage employees to apply them in their daily operations.

Discover data insights

The beauty of artificial intelligence and machine learning is the ability to uncover data insights that were previously unavailable in traditional manual processes. This also has nothing to do with the size of the company. In other words, the success rate or return on investment of using AI and machine learning does not depend on the size of the company. Instead, focusing on implementing appropriate artificial intelligence and machine learning functions and ways of thinking in the organization’s corporate culture is crucial. Whether you are a startup, a growing company or a large enterprise, artificial intelligence and machine learning can be used to drive the company’s development strategy.

The business advantages of strategically expanding emerging technologies are enormous; compared with companies pursuing isolated projects, the success rate of these companies’ artificial intelligence investments is almost three times as high, and the return on artificial intelligence investments is three times that.

The scope of the successful use of artificial intelligence and machine learning is very broad: a Japanese life insurance company used artificial intelligence to calculate the cost of compensation to policyholders. As a result, its productivity increased by 30% and it saved approximately $1 million per year. Similarly, having an underwriting platform driven by artificial intelligence enables car rental companies to reduce losses by 23% each year and predict risks more accurately. Top US banks have used cybersecurity companies driven by artificial intelligence technology to distinguish real customers from robots. Its machine learning model enabled a major bank to protect its customers from account hijacking and detected a million “credential stuffing” attacks in the first week of use. Therefore, artificial intelligence and machine learning can not only improve profitability and save costs, but also protect your company from fraud and security breaches in the future.

Less talking, more working

In order for companies to take advantage of artificial intelligence and machine learning, it is essential to shift from exaggerated theoretical narratives to actual implementation work.

As an industry, we must speak less and do more to accept the business impact of artificial intelligence and machine learning. These technologies should no longer be seen as vassal solutions, they are now indispensable to various business models. It is critical to develop plans and integrated strategies on how your company will use artificial intelligence and machine learning to mitigate the risks of cybercrime and fraud, while seizing opportunities that can have a real business impact.

Freelancer Blogger and Writer. I am now studying CSE at Chengdu University Of Technology. Feel free to contact with me.

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