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金融業積極導入 帶動數位經濟 (2018-07-25 IEK產業情報網 )

In the face of an emerging technology, the biggest winners are not those who duplicate past success. Rather, the victory is for the society and the companies who can guide people toward growth industries. The robot industry is a good example. Google, Microsoft, Facebook, Apple and IBM are fighting for AI leadership by launching their own AI related products. The next step is to materialize the value of AI through robots. In the future, the robot industry will see dramatic changes brought about by AI. Start-ups will also play an important role in the up-and-coming changes.
The likely winners in the robot market are those who are able to analyze the Big Data required by AI, apply the intelligence in a reliable, distortion-free manner between machines and data centers and identify the essential, specific applications. IEK forecasts the AI market relevant to the global robot market will grow exponentially to over $80 billion by 2020.
The AI movement is an unprecedented renaissance in the industry. Everybody has been thinking about how to achieve greater automation. However, some companies have rushed to purchase robot arms to get ready for Industry 4.0 and introduced software to develop AI before they can even tidy up their messy production lines and workstations. In fact, lean production is a prerequisite before the introduction of automated manufacturing processes. The procedure should be as follows: rationalization and improvement of production lines, standardization and a systematic approach to production and operations, then automation of the workflows with robots and automation of the information flows with software in order to achieve smart manufacturing.
The main purpose of using AI is to reduce the costs incurred in response to external changes, particularly in the case of manufacturing robots. In fact, leading industrial robot makers are getting a bigger piece of the market. Taiwanese suppliers should not just focus on the production of robot arms with a high cost/performance ratio in order to compete head-to-head with market leaders such as Kuka from Germany and Fanuc from Japan. The focus should be placed on the integration of AI, robot manufacturing and the IT communication system, so that Taiwanese players can achieve a competitive advantage, even as late starters in the industry.
Confronted with the challenge of new fintech players, mainstream financial institutions have been learning from startups and investing heavily in innovative companies in order to compensate for where they are lacking in competences. Many new ventures own core competences in AI related applications. The combination of AI and fintech is a promising area for unicorns, and it is hardly surprising that venture capitalists always look for opportunities in this segment.
IEK has observed a rapid rise in “AI + fintech” applications. For example, the global robo-advisor market for wealth management is expected to grow at a CAGR of 47.5% in 2017-2021, with a user base of 94.5 million globally by 2021. The insurance industry can also rely on AI plus insutech to reduce costs and enhance service levels. In fact, one of the derivative benefits from AI is the effective prevention of over 20,000 telecom frauds each year in Taiwan.
Fintech encompasses four main types of services, i.e. investments, digital currencies, financing and payments. The value added by AI to fintech is on the new business models associated with investment and financing especially. The emphasis of the derivative bonus applications should be focused on anti-fraud efforts.
AI continues to push for digitalization in various domains and drives the growth momentum of the digital economy. Generally speaking, fintech, insurance, sales, customer relationship management, information security, business, medicare and industrial IoT will be the major adopters of AI over the next few years. This has prompted many start-ups to develop solutions in their niche areas.
Digital technology is driving a digital transformation across different industries. The three pillars in this process are digital infrastructure, IoT analytics and innovative services. Smart devices are developing the communication capability for integration and collaboration as “cooperative things” and are becoming a part of the digital infrastructure. Meanwhile, digital trust has emerged as a key issue for digital infrastructure. As a cornerstone of digital technology, it has prompted the emergence of new regulatory regimes, technologies and control mechanisms.
In the meantime, systems are beginning to connect with objects and people on a larger scale in order to create value with AI. As the AI capabilities continue to evolve and the IoT data continues to multiply, the accelerating combination of AI and IoT will require more IoT analytics. The development of the digital and real economies will support more complex analytics and decision-making processes in various fields, powered by digital technology. This promises new business flows, user experiences and innovative services. The integration of AI and information security is also changing the concept of protection in the corporate world, with an increasing investment in detection and response. Going forward, information security companies will focus on AI and behavior analytics in order to enhance detection technology based on behavioral analysis.
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