Artificial Intelligence：Opportunities and Challenges

7

October

2020

5/5 (1)

Artificial Intelligence, that is AI, has already been a revolutionary technology and is going to play a more important role in foreseeable future. Recent researches find that, AI, which is based on neural net and deep learning method, can produce a potential value of around 3500 to 5800 billion US dollar, accounting for about 40% of the total value which analysis techniques can provide (McKinsey 2018).

AI may have the biggest potential in marketing and sales, supply chain management and manufacture. This is because these industries usually have a high frequency of interaction with their customers, resulting in providing large amount data that can be used by AI. For example, E-commerce companies can obtain customer information by directly observing their customers’ behavior when visiting the websites. Based on that they can provide personal pricing and recommendation strategies. Companies can also use AI to improve their working process and adjust their production and supply chain operation, minimizing the use of raw materials and utilities and decreasing the total operating cost by 5% – 10% (McKinsey 2018).

Many investors have seen the opportunities and keep investing in AI, stimulating this technology to go further. This indicates that more potential will be released in near future. However, so far only a few pioneers have the capability to truly utilize AI. According to Mckinsey (2018), only 20% can apply it in their core business. Most corporate still have the problem of lacking talents and complete procedure to maintain the database.

AI itself also has some disadvantages. There may exist some invisible mistakes. AI provides it answers by self-study, but this is not always perfect. Since some AI models are not apparent, they may hide the true mistake. Take auto-driving as an example, the models are keeping improving since the training data is increasing, but people still find mistakes in the algorithm, and sometimes the mistakes are found at the sacrifice of serious accidents.

People should also be aware of the lack of their own skills, judgment and comprehension when enjoying the benefits provided by AI. One engineer in Silicon Valley said that the use of AI made his team not invest too much to think carefully. It is really dangerous for a team if they don’t pay time to understand the basic elements and stimulus for their business.

And the problem of discrimination caused by AI cannot be ignored. Because historical data is used to train the model, and the model will naturally reflect the bias in the data. For example, in loan approval, race and gender may be considered by AI algorithm, but people using AI may not be able to detect such discrimination.

It remains to be seen how AI will develop and benefit human beings.

Reference
McKinsey, 2018. Notes from the AI frontier: Modeling the impact of AI on the world economy, viewed 7 October 2020,

Kaja Polachowska, 2019. 12 challenges of AI adoption, viewed 7 October 2020,

Ting Li, Stefan van Duin, 2020. Challenges and opportunities of AI sources, online video, YouTube, viewed 7 October 2020, .

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Digitalization in banking: a way to benefit both banks and their customers

4

October

2020

5/5 (1)

As we know, digitalization has been a trend in nearly all the industries we can think about, let alone banking. It is generally recognized that digital technology is the way to increase the profit, manage the risk and improve the experience of customers. According to Groenfeldt (2020), Covid-19 has gradually made the remote visit and mobile banking a necessity in our daily life, and we can imagine that this innovation will continue.

Actually, there have already been a lot of digital services for the customers, such as banking APPs and the mobile payment. Now banks are trying to improve their customer experience from some brand-new angles. For example, they are trying to personalize the service and products they provide to their customers. Big data is the core to achieve this goal. Banks are encouraged to use customer portraits to build their customer data platform, which is CDP, as they call it, focus precisely on the demand of different customers, decide quickly, and design the products smartly, and finally distribute them directly to the customers.

However, banks seem to be making progress from the customer aspects, but still have a lot of things to do to insert digitalization into their internal procedure. Now the cooperation technologies for employees in banks are only confined to basic communication tools, but these tools haven’t been connected directly to the business, and employees still need to repeatedly check the confirmation status and do some unnecessary inquiries. API and some micro technologies can be used in this circumstance. If we can simplify the core business procedure which occupies 15% to 20% of the cost, and improve the productivity by 8%-10% by removing the redundant work what have been mentioned above, the banking industry can create a new value of more than 30 billion dollars (McKinsey, 2020).

What’s more, it is highly recommended for the banks to build an industry resource integration platform and create a new cooperation mode. Banks can use API to realize the sharing of data with the third party, which enables customer to obtain financial service from the third party, making banks more open than before. Meanwhile, by this kind of cooperation, banks can make use of the data to innovate and develop new customers with their partners, increasing the customer base and create new business increasing point.

References:
McKinsey, 2020. How digital collaboration helps banks serve customers better. Retrieved from
https://www.mckinsey.com/industries/financial-services/our-insights/banking-matters/how-digital-collaboration-helps-banks-serve-customers-better [Accessed 4 October 2020].

Tom Groenfeldt, 2020. Covid-19 Accelerates Banks’ Move to Digitalization. Retrieved from
https://www.forbes.com/sites/tomgroenfeldt/2020/07/01/covid-19-accelerates-banks-move-to-digitalization/#78b86abf3bac [Accessed 4 October 2020].

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