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High Return, Low Cost, What Robo Advisors Bring

Robots can't take over all the tasks and they can't defeat Buffett. However, robots might win you, as long as they are reliable enough.

(Chinese Version)

Fintech has brought forth many new ideas and concepts, such as P2P and blockchain, all of which are generating great impact on the financial industry and even the world. And it seems its latest creation is robot advisor.

Similar to blockchain technology, robot advisor is in fact not something that just emerged recently. As early as in 2008, the very first company focusing on robo advisor appeared in the U.S. At present, we have famous robo advisor platforms such as Wealthfront, Betterment and Personal Capita etc.

In China, the robo advisor scene is even hotter. We have a group of fintech companies, including CreditEase, ClipperAdvisor, LicaiMofang and MiCai etc., entering this rather mysterious realm. According to Yingcanzixun’s statistics, there are over 20 Internet finance platforms and fintech companies in China that have launched robo advisor service. Besides that, banks are also catching up. TMTpost learned that on December 6th, China Merchants Bank had rolled out its robo advisor feature, Mojie, on its APP.

Earlier this year, AlphaGo defeated human Go master Lee Sedol, making many wonder if robots can defeat Warren Buffett as well since they are already that smart. Will robo advisor guarantee return? Why banks are following the trend as well?

Despite the hot scene, there are lot of things we should think about.

Robots VS Buffett

What is robot advisor? In simple term, it’s a smart investment consultant. Technologies make it smart, while consulting is a business, a service.

From the perspective of technologies, robo advisor integrates big data and AI technologies etc. into securities investment advisor business, turning the traditional one-on-one private service into a large scale service that can be massively produced. It lowers the threshold and makes securities investment advisor service accessible for the general public. Robo advisor has very high technological standards.

Looking from the business sense, robo advisor is part of the investment consulting business that involves analyzing user’s risk tolerance and providing financial products that meet the risk tolerance and the demands of the user. It also involves helping the client investing his or her asset in foundation, stocks, rights, and constant return products etc. Professional talents and organizations that engage in such business must have relevant qualifications and license.

In accordance with China Merchants Securities’ report, a typical robo advisor service includes the following steps:

1. Client profiling: Assess client’s risk tolerance and investment goal

2. Generate investment portfolio: Recommend investment portfolio to the client from the data base according to client’s preference and risk tolerance

3. Client funds trusteeship: Transfer client’s asset to a third-party trusteeship

4. Execute the transaction: The system represents the client and makes the transaction order, sell or buy asset

5. Rebalance the investment portfolio: Regularly asset the investment portfolio, and make adjustment according to the market status and the change of client’s needs

6. The platform charges management fee

Among the steps above, client profiling, investment portfolio generation and investment portfolio rebalancing in some way decide the quality of the robo advisor product.

In general, robo advisors have the following advantages compared with traditional investment and wealth management service: It lowers the service fee; it boosts the consulting efficiency, makes information more transparent and spreads investment risks; prevents the decision from being affected by personal feelings, allowing robots to execute the strategy strictly.

From U.S to China

Robo advisor originates from the U.S and China is an apprentice in quantitative Investment. Chinese innovators are also trying out new games while learning to play in this sector.

An industry insider told TMTpost that Wealthfront, Betterment and Future Advisor were once the role models of Chinese robo advisor companies. But the lack of ETF and the different investment environment have made them believe that copying America’s model will eventually fail.

An exchange-traded fund (ETF) is an investment fund traded on stock exchanges, much like stocks. It has a high return rate and therefore has become an importance indicator for American robo advisors.

Wealthfront for example picks 11 ETF, including American stocks, other developed countries’ stocks, emerging markets’ stocks etc., to diversify investment portfolio, reduce risks and achieve stable return rate.

GeekCapital once wrote that: “Robo advisor in America doesn't really need a killer technology to win over the market. It is designed to lower cost. Wealthfront helps clients make 4.6% more and charges 0.25% annual management fee. It’s natural.”

Several Chinese platforms also chose this approach. For example we have TOUMI RA from CreditEase. It focuses on ETF products and tracks the index of the stocks, bonds, and real estate of the American, Chinese market, as well as other developed and developing countries. But due to exchange control, TOUMI RA can only deal with investment volume under $50,000.

China also has ETF products, why not choosing Chinese products as the indicators? Firstly, China falls short of index investment. Statistics from wind show that, take American robot advisor’s main ETF products as example, in June this year China had 130 listed ETF in total with a scale of ¥472.9 billion. Compared with that, there are 1,600 ETF in the American market with a total volume of $2.15 trillion.

Under these circumstances, publicly offered funds in the country became the main targets for local robo advisors when it comes to investment portfolio. Open data shows China has 3,400 publicly offered funds covering fundamental assets, overseas and domestic stocks, bonds, merchandise, gold and oil etc. Besides, publicly offered funds have higher transparency on transactions, stricter management, and lower threshold. In this case, publicly offered funds are better investment choices compared with the private ones and trust fund.

High return?

Similar to other vertical sectors related to AI, robo advisor’s performance is powered by the algorithm and data. TMTpost learned that the common sense in the industry is: The algorithm matters in the industry, but data and experience are the game changer at the end of the day.

The thing is, it’s not easy to acquire data on investment. Wang hongdong, general manager of the wealth management department at China Merchants Bank, believes that there are barriers among publicly offered funds when it comes to finding data.

“Publicly offered funds has a bilayer structure: One is fundamental assets like stocks, rights and merchandise, while the other one is the fund manager and the director. So the two layers give out two sets of data,” Wang said.

The data of the first layer is the basic return data on financial products that are open in the market. This set of data is massive and can be used for machine learning. The other set of data is not structural. And the open data of this layer is about the capital fund and register information etc. It’s incredible hard to get complete and useful information.

Investment portfolio is not merely a matter of computing structural data, but of collecting, managing, filtering, and describing non-structural data.

From Wang Hongdong’s perspective, Mojie Robo’s advantage lies in the fact that Merchants Bank is a powerful public and private placement sales organization.

So, can startups that are short of transaction data and investment experience still find a shot in the robo advisor scene?

Zeng Gang, director of the bank research center at the Chinese Academy of Social Sciences told TMTpost that most robo advisor products are still controversial among investors. “How can you trust a robo advisor that is made by people without data and clients?” An industry said to TMTpost.

To attract users, some Chinese robo advisor startups tend to emphasize on high return rate and attribute it to the magical AI. Hengfeng Bank’s research center executive director Dong Ximiao stated that such slogan could be a marketing trap or even a fraud.

President of Merchants Bank’s retail finance department, Liu Jialong, told TMTpost: “The golden era of banks has officially come to an end. It’s commonly accepted that this year will be the year in which AI becomes a widely known term. During this process, most of the AI applications will take place in the financial sector. We believe that the only feasible way to fuse AI with finance is the human+AI approach. We don’t advertise that AI will take control of everything.”

Regulation and supervision are coming in place

Meanwhile, some P2P companies that are seeking transition are trying to make some profits out of this hot scene while it’s still chaotic out there. Some on the other hand use robo advisor as a distraction to cover the fact that they are building their own fund pool, covering the track of the fund.

Not long ago, China Security Journal reported that the authority is studying to make a licensing system to regulate and supervise the robo advisor scene. Compared with innovative finance companies, mid and large-scale foundations and asset management organization could get the license through procedure easier. Industry insiders believe that a group of robo advisor companies will be eliminated out of the sector.

This is what set an innovative sector on track. And it’s actually a live or die moment for startups in this sector that seek improvement. But for those big players like the Merchants Bank, the coming regulations are an opportunity.

The ultimate answer to the question mentioned above is quite obvious now: Robots can’t take over all the tasks and they can’t defeat Buffett. However, robots might win you, as long as they are reliable enough.

……………………………

(Like our Facebook page and follow us now on Twitter @tmtpostenglish and on Medium @TMTpost and on Instagram @tmtpost_english and on Apple News@TMTpost.)

[The article is published and edited with authorization from the author @Cai Pengcheng, please note source and hyperlink when reproduce.]

Translated by Garrett Lee (Senior Translator at PAGE TO PAGE), working for TMTpost.

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