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In 2019, Fintech will officially join the CFA exam. The questions are not programming, multiple choice questions or trends.


Recently there is news that Fintech content will officially join the CFA exam in 2019!

The question type is not programming, multiple choice questions or trends.

Uni sauce found that this news was not recently released:

Source: CFA Association official push

As early as May, the CFA Association has proposed to introduce AI, big data, etc. into the CFA exam.

Moreover, Steve Horan, head of the CFA Institute MD and Education Co-ordination, said in an interview:

Source: Bloomberg report

The exam does not require candidates to understand how to program , but to understand how fintech works and how it affects the investment model.

Then the problem is coming

Fintech is developing so fast,

Can't stand in the financial industry without knowing programming?

01. Replaced anxiety

In recent years, the application of artificial intelligence (AI) in the investment field is profoundly changing the investment world.

  • Goldman Sachs is transforming into Google on Wall Street: Chief Financial Officer Marty Chavez is the promoter of Goldman Sachs' transformation plan. He said that Goldman Sachs has many similarities with Google's business: "Goldman's risk is like Google's search."

The essence of Goldman Sachs services is to help customers anticipate and understand risks , just as Google provides information to users. However, Google users do not consult the sales staff by phone. Goldman Sachs also hopes to provide users with a risk search engine. Currently, Goldman Sachs has begun to automate.

  • COIN, a financial contract analysis software developed by JPMorgan Chase, requires 360,000 hours of work per year for former lawyers and loan officers. COIN can be completed in a matter of seconds .
  • On May 26, 2017, PwC launched a robotic process automation solution.
  • In March 2017, BlackRock announced the layoff of more than 40 active fund divisions, including seven portfolio managers, instead using robots instead.
  • On March 10, 2016, Deloitte and Kira Systems teamed up to officially introduce artificial intelligence into accounting, taxation, auditing, etc.
  • ......

The CFA Association announced that it will add Fintech content in 2019, and many people are worried. On the foreign question and answer website Quora, there are CFA holders asking: "With Artificial Intelligence coming, what does the future hold for CFA holders? ”

A netizen answered this question like this:

The AI ​​will eliminate all manual and repetitive work, although it may take a while to train the system to have these features, but it will also take the decision-making effort in the foreseeable future. However, anomaly management must be done by humans.

(Source: Quora)

The latest report from Opimes, a financial services consulting firm, said that by 2025, global financial institutions will be down by 10%, nearly 230,000 will be affected, and computers will replace their jobs. Of these vacant positions, 40% will come from the asset management department . The chart below illustrates the impact of AI on various positions on Wall Street:

On the other hand, in addition to the technical department, the decrease in the number of investors in the banking sector is not significant. In fact, many of the projects undertaken by investment banks still require personal to person communication skills, and this part of the work is difficult to be replaced by algorithms in the short term.

02. Which positions will be replaced by artificial intelligence?

In July last year, McKinsey published an article "Where machines could replace humans-and where they can't (yet)", which mentioned the risks of various industries being replaced by robots:


As can be seen from the figure, the few posts that are the easiest to replace are:

  • Management
  • Positions that require complex expertise (specifically, decision making, planning, creativity)
  • A post that interacts with the stakeholder

The most obvious places to be replaced are: data collation and data collection .

The advantage of solving problems through technical means is that after a type of problem is solved, the marginal cost of solving similar problems is almost zero, and no manual investment is required. Therefore, in a fintech company, the number of general engineers is large, and the technical culture will be stronger. Efficiency must be one of the most important principles of the company. When artificial intelligence entered the financial sector, the industry has begun to be completely subverted.

Take Goldman Sachs as an example:

What has been eliminated is the trader who shouts in the trading floor . The buying gesture of arms hugs and fists and the sell gestures that are pushed outwards are no longer visible. Now more than just in the trading floor, the transformation has spread to investment banking . Establish a data service center that aggregates transaction data from all exchanges, suppliers, and Goldman Sachs into one location and then assigns it to customers.

The first step is to accumulate and analyze the data. The next step is to put the data in the hands of the customer.

So what is the situation of commercial banks?

Citi has made a matrix of the business most vulnerable to FinTech. The higher the number, the more vulnerable these businesses are to FinTech threats; the farther to the right, the closer these threats are. From the picture, banks that are vulnerable to threats and are often threatened are: Personal Loans, SMB loans, Digital pmts, and Wealth Mgmt. .

Another robbed business of the bank may be the lending market.

In 2015, investment in FinTech has grown to $19 billion , an increase of nearly 60% compared to 12 billion in 2014 .

Where did the money go? According to Citi data, nearly half of the investment funds have chosen the lending market, which is FinTech's number one gold medalist.

03. The demand for AI talent in the Internet finance sector has soared

In August, released the “China Internet Remuneration Report 2017”. Based on its platform users, it summed up the average salary of different fields and positions from January to July. It was found that the demand for AI talents in the market increased sharply within half a year.

The big data talents in the Internet field are far ahead, with an average monthly salary of 21,200 yuan. In 2011, McKinsey's "Big Data" concept in the "Big Data: The Next Frontier Area of ​​Innovation, Competition and Productivity" was the first to systematically explain the concept of "big data", and "big data" gradually became the mantra. Realizing the value of big data and putting it into use is a problem that all Internet companies, venture capital institutions and even traditional industries are solving.

In addition, under the same working years, the average salary of AI talents is ahead of other fields . In the first half of the year, the demand for talents in the AI ​​field increased by 4.2 times, the salary increased by 24.5%, and the average salary of graduates reached 8,400 yuan. The Internet finance industry first absorbed it as a force for change. The average monthly salary of wind control, data research and development and angel investment technicians reached 23,800 , 22,600 and 21,700 yuan respectively .

Talents who understand AI and big data have become new darlings. However, for technology finance, what is more needed is to use good technology to develop financial talents.

Recently, the State Council issued the "New Generation National Artificial Intelligence Development Plan", and the plan also specifically mentioned smart finance.

04. Want to stay in the financial industry? Be a compound talent

I have to say that if you want to engage in the financial industry, the convergence of technology finance and financial business is the general trend. Artificial intelligence, big data, etc. are definitely the focus you need to pay attention to! However, it is not that you can't enter this field without programming!

  • If you are now in a financial services company

Then you should start to pay attention to the company's internal artificial intelligence innovation project . Most multinational financial companies will have similar funds/funds to support such projects, research departments within investment bank brokers or independent data analysis teams.

  • If you are still a non-tech major

A minor computer language, but the key is to understand what the algorithm is . When many students find Uni sauce, there is a huge misunderstanding: that is to say that arming yourself is equal to learning a programming language. What exactly is the advantage that the code brings to me?

In fact, it is a way of thinking about problems, logic is classified (because we are used to drawing logical trees), logic is optimized, whether it is time or space use improvement, always thinking about whether there is a better way to solve problems , language In fact, all of them are connected, but their inner connection and essence require children who want to advance to the compound talents through minor language. They should carefully study the performance characteristics, which is more important than knowing the grammar of the language.

  • If you are a non-financial practitioner, but want to develop towards AI financial practitioners

This article also applies to students who are thinking about whether to continue reading . It is recommended that you read a Master in Business Analytics or Master in Data Analytics , which is a Master of Business Analysis or a Master of Data Analysis . This major belongs to the profession that has been popular in the past two years. The main content is how to apply data analysis to business . Such degrees generally cover basic data analysis and machine learning, but are more focused on applications than on theoretical development.

From this perspective, the application is less difficult and the threshold is not as high as the master's degree in science and engineering. Of course, we can't expect to open the door of financial institutions after reading this degree. It just means that we can use the AI ​​model in future work, and we can have some understanding of modeling.

At least understand the use of AI in different areas, as well as trends . AI industry is no shortage of technology Daniel in the general sense, a big vote of the company's scientists are overcome AI the bottom, so the requirements of the programming is not too high, but now the technology has matured, the reason is not widely used, is in The application does not reflect the commercial value of the underlying technology. What the industry lacks is a highly creative and insightful business talent that leverages the commercial value of technology.

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Part of the content source: CFA official push, McKinsey, interface news, etc., UniCareer comprehensive finishing release, please indicate the source.