IBM Roundtable discussion: A new cornerstone of big data acquisition competitive advantage

The first round table discussion was the new cornerstone of the major data acquisition competitive advantage by Ms. Cheng, IBM China's chief technology officer and chief architect of the Financial Services Division.

Cheng: I've been building it with Chinese companies, especially banking, since 1993, from scratch. In this process, large enterprises have accumulated a lot of internal data, including transaction data, operating data. In fact, what does the big data in the mobile internet era mean when the new internet age arrives?

You can see in the new internet age, IoT, car networking, social media, Mobile information, all of these external information into a very important source of data for the Enterprise class. Why? If the previous enterprise-level internal data is mine, it is in the known mine mining to the enterprise management and operation of effective information. This external large new data, the Internet on the external public data for them is "sand sea", how this one to explore new perspectives, to look at customers from another perspective, how to formulate a new strategy for the enterprise on this basis is very important.

Below I will invite three experts to discuss with me the Big Data topic. Please welcome the chief economist of Bank of China, Dr. Yuanzheng, Dean of Peking University People's Hospital Wang San, Dong Jin, vice dean of IBM China Research Institute.

Cheng: The first question to Dr. Cao, you know, after the advent of the new Internet era, internet finance has brought a very big impact on banks, almost a subversive impact. In the new internet age, what do you think is the challenge of big data to the financial world?

Yuanzheng: The core of financial institutions is the institutions that deal with risk. What do you think about risk? Is the uncertainty of the future, information asymmetry, the use of information technology is the inevitable pursuit of financial institutions. We find that changes in information technology can also bring about changes in financial institutions and financial forms. Now the internet finance is just the new technology in the new era of information technology. The important thing about Internet finance is not that Internet technology also lies in new thinking.

Yuanzheng: In the big Data age, new processing technology brings new business models. What is the biggest difference between the business model of the Internet and the traditional business model? The internet is from the demand side, the grass-roots society's various needs are automatically generated and then become a product. I used to design products, standardize and then sell to everyone, this is a standardized production, industrialized thinking. And the internet is not like this, in this case, there is a very complex phenomenon. I cannot now fully discern whether the phenomenon is right or wrong, but there have been new changes.

Yuanzheng: We use Internet thinking must be the achievement, the question, the result how. Where are the achievements of the Internet? First, because of the large data, the use of the Internet is real-time, and data processing is very timely, indicating that it is more clear on the strategic distribution, and from the financial products are all about distribution, from the probability distribution to do product hedging risk. If the customer's behavior is described more accurately, the probability is more comprehensive, the finance is deepening, and the Internet does not do that.

Yuanzheng: Second, the internet technology instead of the physical network, the cost is relatively cheap, so the permeability is very high. All the people who do the bank, the one or two-dollar business is simply impossible, because the cost is there. But internet finance is one or two dollars can be, so that financial infiltration into everyone's life. If finance is not mysterious as a general financial, then the Internet has done this. What are the problems? It's a hot topic now.

Personally, it is triggering systemic financial risks. After the internet finance model comes out, one of the biggest problems we take in bank deposits, you will keep the meal in hand, is the use of money as a deposit, the internet blurred the relationship between the deposit and the meal, Alipay is paid, all the money on the top, because a lot of money, put this deposit into balance, balance into deposits.

Yuanzheng: Deposit in the commercial bank must have a deadline, know the deposit time to know how to arrange the loan. Commercial banks are most afraid of runs. But do pay, do not know customer behavior, customers may be due to some kind of need, today this meal to eat better, spend more than usual, this behavior is normal. But payment is a hand-paid delivery. If there is another "Singles Day" turnover suddenly very large, a large number of payments in the bank, this time there is a run, if the money is a small bank, it was quickly knocked out.

Yuanzheng: If from the risk management point of view can make the agreement deposit, but cannot do t+0, cannot the immediate exchange, even if you are doing in the bank, the money that you deposit today is not able to take, the bank is also to be at the lowest date of the day. Now the development of the Internet can be said to be the emergence of such a situation, after February this year, the Internet Enterprise competition intensified, the balance of treasure transferred to Tencent Online, will certainly be large, will bring financial risks.

Yuanzheng: Back to the third question, what about the future. I can't figure it out, but I want to say one thing is to see clearly, it defines the boundaries between financial and internet businesses. What is Finance? Deal with the uncertainty problem. If we use the Internet, it can replace all the problems of certainty, pay, trade, but can not replace the problem of dealing with uncertainty, I dare not to conclude.

Yuanzheng: You can see that the future of Internet companies may be two roads, one is to make payment system in finance, payment system is the first hand to pay the delivery of money, this is the certainty of the problem, there is certainly more development potential, because your cost is lower, than the physical network cost much lower, there must be a lot of commission income. Either you become a financial enterprise, financial firms should be regulated in accordance with the Basel Agreement, and usually we call the general deposit of financial institutions, the global regulatory standard is the same, 8% of the capital adequacy ratio. At the same time, countries have the requirement of deposit reserve, China is 20% of the deposit reserve. Under such an arrangement, this is the general regulation of finance.

Yuanzheng: The Chinese government is trying to move in these two directions, has given Taobao, Tencent issued a financial licence. Make a payment, pay is completely deterministic, the central question is whether to raise interest rate? If the money is a raise, it is a financial activity, if the money does not raise interest rate, this is the payment activity. The interest rate is the most important financial activity, it is the risk premium. If a risk premium is to be made, a financial licence must be obtained. If there is no risk premium, it is technology competition. From the perspective of the future, the payment of finance from the theory can be all the physical network of banks to replace, especially the large data and analysis of the ability to significantly enhance customer stickiness, this is the design of products, which is related to the arrangement of interest rates. The above is my comment, thank you.

Cheng: Thank you, Dr. Cao, for sharing his views so deeply. IBM in the financial world, from large data or traditional data analysis and mining, from two aspects can fully help the enterprise level, first, risk control, and how to conduct in-depth insights into customer behavior trends. Here we talk about IBM for Singapore's DBS Bank to do Watson implementation, through customer behavior reflects more targeted to provide customers with the most appropriate financial products. Next to the medical community, please Wang to share a large data analysis in the medical community.

Wang San: Today I appear to be a different kind of a surgeon in the IT Forum. I have been in touch with information for more than 10 years. Just now the money has always said that the data is a resource, and we are talking about how big China's resources are. Last year, Chinese outpatient visits were more than 7 billion, diabetes was close to 120 million, and hypertensive patients were 200 million, but resources possessed and contributed to the world's medical imbalance.

WB: That means we have the resources, but we didn't dig it deep, especially the mentioned Watson, to be able to analyze it. So much of the data is now limited to the 20% of structured data just mentioned. Now, more importantly, a large number of 80% of unstructured data, which is China's hope, the hope of Chinese medicine. But it must depend on the development of technology.

WB: My second point of view, I spent so many years with information, is entirely user, information technology is not to let people go because it is machine thinking, machine methods, but with it thinking, it methods to use, now it is the trend is to let a normal person back to nature. When it comes to big data, it's not just big data, it's actually a series of technologies such as mobile health.

WB: The pattern I'm talking about is getting the patient back to nature, how many times does it take to return to the naturally generated data now using diagnostic data, which is the challenge to the IT industry. It also poses challenges for the healthcare industry. How to get the patient home and be able to diagnose, treat and correct it in real time at home. and change the health care system. At that time not the Doctor of Peking University People's Hospital takes care of him, but the community doctor comes home, adjust according to our instruction. It can be imagined that, in fact, when large data first appeared, an important area was the field of life, and the emergence of cognitive computing, now there is a new area of tumor diagnosis. I really think that one day we make people return to the original people, not the machines.

Cheng: 7 billion medical attendance records, if digitized. Plus digital forward, these two add together, I as a future hospital users, the future may be better for me.

Cheng: Our Watson is still deepening study, the treatment of leukemia has begun to grasp, how to use medical information to help doctors and researchers to analyze the best diagnostic judgment, we deepen this cooperation in China, the corresponding solution to the landing. Next please Dr. Dong Jin to talk about the assets of the enterprise, the optimal management of assets is how to carry out.

Dong Jin: Modern enterprises have entered the post-ERP era, every day the enterprise in the running process will produce massive data. In recent years, social data, mobile data, and Internet of things have increased exponentially. Now in fact there is a very big challenge, how to apply good data, to many modern enterprises become very important. Before Cao Sum Wang has shared the financial Internet field and medical field how to apply large data analysis. I am from another dimension, in the asset-oriented enterprises such as new energy, logistics enterprises, how we better use of data such a natural resource, to help enterprises have a deeper industry insight.

First, share the first example, the New energy field. At the end of 2011 China wind power installed the world's largest capacity, basically 30%-40% of new energy wind power is not connected, wasted, the main reason is the randomness of wind power, intermittent can not be merged into the backbone, the need for very accurate small scale, very accurate weather forecast technology, To know how much wind would be produced by each wind field at what moment, this is a big data problem, need to put the entire wind field meteorological sensor data and satellite uploaded from the original meteorological data to do a good integration, using large data method real-time data analysis, and with IBM very strong computational ability to small scale, High precision weather Forecast system.

Dong Jin: With such large data technology, it is helpful to use IBM large data equipment to make new energy forecast in the Chinese national Scenery storage demonstration base. Through this technology, the country's scenery storage demonstration base of wind intervention increased by 10%, this 10% allows 14,000 users to use the wind power every year, equivalent to a full wind farm throughout the life cycle of more than grid-connected power generation of nearly 80 million dollars. Such examples we have done in China are very much, we are in more than 30 wind fields with large data technology to do the entire wind forecasting technology. This is an example of the field of new energy intervention.

Dong Jin: Over the past five years or so, IBM has done large data analysis projects in telecommunications, banking, retail and many other industries with heavy assets. Our experience is that large data is not a mirage-type concept, is true to the ground, is the real can help enterprises generate real business insights, the actual level of service improvement.

Dong Jin: There are three important factors in the actual combat of large data, and it is difficult to succeed without one. Large data projects require deep business insights and industry understanding. Need a very strong IT infrastructure with large data. Need to have very good mathematical modeling talent to help you do model building. IBM has made more than 30 acquisitions over the past five years, with 15,000 analysts based in various industries worldwide. More importantly, we have more than 400 top mathematical modeling experts worldwide. Such modeling experts have more than 50 in China. We want to use our comprehensive data capabilities to help companies and our partners face the era of large data, while embracing this era. The other important point is to lead such an era.

Cheng: Three experts provide us with different perspectives, from different industries to the understanding of large data. Overall, IBM is ready in the following three areas, with Chinese companies looking to work together to make big data more thorough in the new mobile internet age. What are the three areas? First, gain insight into your customers and make the best next move. Second, risk management, enterprise risk must be controllable. Third, in asset management, how to optimize asset management. From these three angles, we hope that the new era, IBM can join hands with Chinese enterprises to move towards a higher level.