Nirvana in Fire: Blockchain, Big Data, etc. Who is the AlphaGo of the financial technology industry?

March 2016 was destined to be an extraordinary month. The world-renowned AlphaGo vs. Lee Sedol duel was seen by the world as a battle in which machine intelligence challenged human IQ. In the end, AlphaGo defeated Lee Sedol 4:1. After March 2016, the era of machine intelligence officially arrived.

In the past decade, the term "Internet Age" has been widely recognized. As the Internet has become more and more of an everyday tool, and as the Internet and new technologies have penetrated into all walks of life, we suddenly discovered that we have entered a technological age. The technological age is broader than the Internet age. The Internet solves problems of communication efficiency and remote collaboration. More problems can only be solved by breakthroughs in various specific scientific and technological aspects, such as 3D printing, wireless charging, smart homes, virtual reality, etc. The biggest difference between the technological age and the industrial age is the great prosperity of scientific inventions. With the help of capital, high-tech civilian and commercial applications have progressed rapidly, and the update and iteration cycle of products and technologies has been greatly shortened.

Finance is known as the first of all industries, and its huge scale is eye-catching. In recent years, with the help of the Internet, many new models and new products have emerged in the financial industry. These new things are classified by Liang Shixian, a financial technology analyst, as: innovation in transaction structure, innovation in technology integration, innovation in transaction process, and innovation in transaction channels. Here we only focus on technological innovation. "Financial Technology Observation" sorted out the latest financial technology trends at home and abroad, and selected the top 6 financial technology Langya list for your reference.

Top 1 of the Langya List: Blockchain:

Innovation index: ★★★★★

Practicality index: ★★★★★

Technology content: ★★★★

Blockchain originated from Bitcoin. It is a set of database technology designed by a cryptography geek named Satoshi Nakamoto when he created Bitcoin. When Bitcoin became popular all over the world, people found that the blockchain technology behind it had magical and unique features, such as decentralization, highly transparent information, not easy to be maliciously tampered with, and data traceability. These aspects are precisely the problems that have been prone to problems in the financial field for many years, or require high-cost investment to solve. The emergence of blockchain technology has opened a window to the world of finance, allowing us to glimpse the new look of the future world.

Simply put, the principle of blockchain is:

1. Data traceability: As shown in the figure below, a data node contains two parts: 1) block header and 2) block body. The block header contains the identity information of each block. The block height is the order of the block in the queue, the header hash is the ID number of the block, and the "parent hash" is the number of the parent block of the block. Blocks are linked one by one through the "parent hash" to form a "chain". This is the origin of the term blockchain.

The block body contains all transaction information that occurred during the period from the last block to the current block. This recording method is of great significance, that is, people can string together the transaction information of each block to form a complete transaction list, and the ins and outs of each transaction are very clear and transparent. In addition, the most important function is that when people have doubts about the "value" of a block, they can easily trace back the historical transaction records to determine whether the value is correct, and identify whether the value has been tampered with or recorded incorrectly.

2. Data tamper-proof: The information in the blockchain is distributed and stored without a central node. Each node is equal and stores a complete copy of the data (called a ledger in the industry). The computer resources of any individual or organization can be used to join the node. As the nodes continue to expand, unless 51% of the nodes in the entire system can be controlled, the database tampering of a single node is invalid and cannot affect the content of other nodes. The more nodes are added, the safer the entire system is.

Blockchain has the potential to be used for:

1. Credit investigation: Currently, the main mode adopted by our credit investigation is the central record and central query mode, which has problems such as incomplete information, high maintenance cost, and data lag. Blockchain can record a large amount of behavioral information and store it on each node. The information is transparent, tamper-proof, and the maintenance cost is low. Perhaps, when people apply for loans in the future, they can complete the approval by calling the information from the blockchain, which is a real flash loan.

2. Payment: The current payment model, whether it is payment from the banking system or payment from a third-party payment company, is a central maintenance model. Transaction records, account balances, and account security management are all built around the central payment system, which presents several problems: 1) Security risk: Once the central system is breached, the consequences are disastrous. 2) Excessive cost: In order to avoid being breached, the central system needs to invest huge amounts of money for risk prevention. In addition, the central system requires a large amount of manpower to operate, and the central system operating organization, after the power is centralized, begins to make profits from this: channel fees, service fees, security fees, etc. According to reports, hundreds of items currently provided by the banking industry require service fees.

3. Points: An insurance company recently launched points based on blockchain technology. Users can transfer points to friends and exchange them with other points based on blockchain technology. Pricing for point swaps is a long-standing problem, and the market-based pricing method adopted by blockchain-based swaps has built a solid foundation for point interoperability.

Currently, the industry is exploring more possible areas for the application of blockchain technology. Here is a picture from MindMap:

Recently, many financial institutions have laid out their plans in this field by setting up blockchain laboratories and investing in related technology companies, including Nasdaq, JPMorgan Chase, Citibank, UBS, Goldman Sachs, Santander Bank, Barclays Bank, Deloitte, etc. The application experiments of blockchain technology have been launched in the securities, banking, auditing and other industries.

Financial technology analyst Liang Shixian believes that blockchain technology is still in its infancy. Although its actual applications have not yet been popularized, its innovation comes from the bottom up and is completely different from the original logic of the traditional financial system. This subversion is fundamental and provides a new way of thinking for finance to move towards comprehensive digitalization and decentralization, strengthen risk control, and resolve distrust in financial transactions.

This is the future of Internet finance .

Top 2 of Nirvana in Fire: Intelligent Customer Service Robot:

Intelligence index: ★★★★★

Practicality index: ★★★★★

Technology content: ★★★★

In August 2015, a robot suddenly became popular on WeChat. It was "Jiaojiao", the service lobby manager of Bank of Communications.

In the service hall of Bank of Communications, Jiaojiao, dressed in white and wearing a silk scarf of Bank of Communications, walked freely in the lobby. Her big eyes and naive and slightly cute appearance attracted many customers to watch. "Jiaojiao, can we take a photo together?" "Come on, I'm waiting, and you must use Meitu Xiuxiu!" "Jiaojiao, I want to deposit 500,000 yuan." "Rich man, I want to be friends with you." After a simple and cordial exchange, "Jiaojiao" will immediately enter the "role" of the lobby manager, skillfully and accurately guiding and introducing various bank businesses to customers. In the process of language communication, Jiaojiao can accurately answer various questions of customers. Its rich knowledge reserve, humorous question-and-answer method, and professional service ability have won praise from users.

Apple's Siri, Microsoft's XiaoIce and Xiaona, Baidu's DuMi, and the earlier Xiaoi are all leaders in intelligent customer service. Through machine learning, speech recognition, semantic analysis and other technologies, artificial intelligence assistants have entered people's lives, making the trend of human-machine dialogue more and more common.

Financial products are usually complex and the procedures are relatively cumbersome, so financial institutions often need a large number of customer service staff.

Intelligent customer service standardizes and templates high-frequency questions, builds a knowledge base to continuously accumulate entries, and improves semantic analysis and matching technology. It can achieve automatic processing of most questions and only require manual intervention for a small number of questions.

This is not only good for financial institutions in terms of cost savings, but also great for customer experience: you no longer have to wait in line for manual processing and your issues can be resolved immediately.

This is not a fantasy. Intelligent customer service robots have already entered our lives and are affecting our lives.

Top 3 of Nirvana in Fire: Face recognition technology:

Intelligence index: ★★★★

Practicality index: ★★★★★

Technology content: ★★★★

Ping An Inclusive Finance provides loans through facial recognition;

China Merchants Bank’s ATMs allow cash withdrawals through facial recognition;

Haitong Securities can open an account remotely through facial recognition;

......

The scenes that appear in science fiction movies have inadvertently floated around us.

The future is here!

Because the face, like other biological features of a person such as fingerprints and irises, is unique and cannot be replicated, it can be used as identity verification.

Face recognition technology uses a camera to collect face photos or videos, automatically analyzes the face images, and matches them with the face database stored in the system to verify the true identity. Face recognition technology has the following advantages:

1. Easy to use: The face scanning process is a very good experience. There is no need to hide the password, and there is no need to try again if you make a mistake. You can just show your face and it’s done. It’s really cool.

2. Security: Problems such as credit card copying and password leakage will be completely solved. You will no longer need to use a thick notebook to record hundreds of passwords.

3. Remote acceptance: Due to concerns about fraud risks, many financial services have insisted on face-to-face interviews and face-to-face signing for many years. Sometimes, it is really troublesome to prove that you are who you are. Now face recognition technology can solve the problem of proving that you are who you are, and non-site financial service acceptance will become a trend.

The user authentication model based on "id+password" has been used for decades, and it now seems that there is a chance that it can be broken through by facial recognition.

Top 4 of Nirvana in Fire: Big Data

Intelligence index: ★★★★

Practicality index: ★★★★★

Technology content: ★★★★

Different from traditional sampling survey methods, big data conducts multi-dimensional analysis of all available data, explores the logical relationships hidden under the data, and uses it in business scenarios.

Specifically in the financial industry, big data is mainly applied in the following directions:

1. Customer portrait analysis and precise service:

Big data is gradually being used by financial institutions to analyze customer historical data, label customers with various types of tags, form customer profiles, and accurately recommend services or products to customers. For example, by analyzing the customer's stock trading behavior, it is found that the customer has repeatedly bought high and sold low, and likes to chase ups and downs. The customer can be labeled as "high-risk preference", "short-term", "emotional", "novice" and other labels. Basically, we can understand that the customer is a more emotional, likes to take a gamble, and does not have a set of suitable operating methodologies. Then, we can recommend some basic knowledge of stock trading to the customer to guide the customer to become a qualified investor. In addition, we can recommend stock funds to the customer, which are in line with the customer's risk preference, but the funds are managed by professional institutions.

2. Credit Analysis:

The Internet credit sector has begun to try to use big data for credit analysis because, firstly, there are still many people in China whose credit reports are blank, and these people are exactly the target group of consumer finance. Secondly, data-based analysis can give a more three-dimensional understanding of a person's social characteristics, which are closely related to the "repayment ability" among the important elements of credit. For example, Wei*dai, a social application, has accumulated a lot of data due to the high frequency of use of customers in its social application, such as the number of friends, the level of friends (friends' credit limit), friend interaction (more interaction with friends with good credit or with friends with poor credit), location information, daily movement routes (to measure life stability), etc. I believe that these have a good chance of entering its credit analysis model for credit reference.

3. Anti-fraud:

By analyzing the behavioral characteristics and result characteristics of historical fraud customers, when new customers come in to apply for loans, credit cards, and insurance, they are automatically matched with the anti-fraud model, and those with a high degree of match are transferred to manual judgment or directly rejected. Fraud is an important cause of loan losses, and there are already several companies specializing in this field, such as Tongdun in China.

4. Prediction:

Kensho, a financial technology company in the United States, is a representative in this field. It scans all possible macro and micro big data that can be found in the world market and directly or indirectly affects the financial stock market, such as political events, economic events, business events, social events, etc., and uses extremely complex statistics, artificial intelligence, machine learning, big data algorithms, quantitative economics theories and models to deduce the most likely change trend and probability of a specific type of stock (even individual stocks) associated with a certain event, and finally presents it in a popular way. For example, which stocks will benefit from the release of iPhone 6. This experience is similar to the experience of Google search: ask questions and get answers. Very cool. Fortunately, Kensho is currently only open to institutions, otherwise various securities analysts, fund managers, etc. may lose their jobs.

Top 5 of Langya List: Quantitative Trading:

Intelligence index: ★★★★

Practicality index: ★★★★

Technology content: ★★★★

Quantitative trading refers to analyzing historical data and observing the returns of the target (or combination) after a certain type of "event" or "signal" occurs. When the return exceeds the benchmark return, it will be used as a model to formulate strategies and guide subsequent investments. In addition, subsequent investments will be led by machines, which will avoid the human weaknesses of greed and fear to the greatest extent.

The advantages of quantitative trading are:

1. Learn from history: Analyze as much historical data as possible through big data to find models that can bring excess returns.

2. Automation: Using programmed trading, based on the model, when a preset signal appears, buy or sell, completely automatically.

3. Fragmented profits: Each transaction does not pursue high returns but rather success rate. The profit may be small each time, but accumulating small profits will bring considerable returns.

In recent years, the proportion of programmed trading volume in the New York Stock Exchange has remained at around 30%. It is also booming in China.

People who use quantitative trading to invest have a fancy name, Quant. Remember, if you want to show off, you can tell others: I am not a stock investor, I am called Quant!

Top 6 of Langya List: Smart Investment Advisors:

Intelligence index: ★★★★

Practicality index: ★★★

Technology content: ★★★★

Most people don’t know what an investment advisor is.

If you know that, then congratulations, you have already beaten 95% of the people on earth.

Private investment advisory services are usually only provided by the private banking department of a bank, or by securities companies or fund companies when facing large clients.

Private investment consultants usually have high education, good resumes, well-dressed, polite and stunning appearance. They are eloquent about the global economic situation, well-informed about the current situation of different economies, and well-informed about overseas asset allocation. They can conduct global asset screening, risk matching, proportion allocation and liquidity management based on the risk preferences and asset size of the clients, ensuring the safety of the VIPs' assets while ensuring reasonable returns.

However, this kind of VIP service is only available to clients with assets worth millions, because: the cost of human services is too high (think about the annual salary of investment consultants), and the service efficiency is too low (think about how many clients can be served in a day).

Now, financial geeks want to break this status quo.

Taking Betterment as an example, let’s take a look at smart advisors:

First you need to set your investment goal, and then Betterment will ask a series of questions based on your goal. Betterment will analyze your answers and give corresponding investment portfolio recommendations, including stock fund (ETF) portfolio recommendations and bond fund portfolio recommendations. You can also invest directly through the Betterment platform. It is bound to the user's bank account and automatically deducts money from the current deposit account. Users can also refer to the investment plans of other users with the same income and occupation. Betterment currently manages $3 billion in assets.

Financial technology analyst Liang Shixian believes that smart investment advisors have several core values:

1. Professional selection: Most users are not professional. When faced with numerous products, they have information asymmetry, lack of knowledge and other issues, making it difficult to choose. Behind the robot model are financial product experts who complete the product screening work for users.

2. Dynamic tracking: The combination can be set to enter the model and exit the model. When the preset threshold is reached, it will be warned or even automatically operated. It is your loyal servant, watching over your money 24 hours a day, 7 days a week.

3. Automation: After the portfolio starts running, it also needs to be adjusted as the market changes, such as position adjustment, asset allocation adjustment, and portfolio target adjustment. Human power cannot track and operate in real time, so machine intelligence comes in handy.

Foreign financial technology institutions have been exploring this field for many years, among which Wealthfront, Betterment, Personal Capital, and FutureAdvisor are leaders in this field.

According to AT Kearney data, by 2020, the amount of assets managed by smart advisors in the United States will reach 2 trillion.

Author: Liang Shixian, head of the Internet financial platform of a listed company, worked at the headquarters of Ping An Group for 13 years and witnessed many innovative financial technology and Internet businesses of Ping An Group. He also participated in the entrepreneurial process of a certain p2p as one of the first batch of Internet finance entrepreneurs in China.