Smart Investment Advisor 3.0: What is the future of smart investment advice from the perspective of analysts?


Some time ago, with the rapid development of financial science and technology, smart investment advice also ushered in a brief outbreak. Under the gradual tightening of supervision, smart investment advisers have recently encountered a lot of pressure. Under such circumstances, we also need to listen. A fair, authoritative analyst familiar with the field will analyze the technology and its future.

Currently, we are in the iterative period of smart investment advice (robot financing) technology. Last week, Celent senior analyst William Trout attended the online seminar entitled “Intelligent Investment Advisor 3.0: What Is It? Where Are We Going?” The meeting will discuss the expected course of technological development in connection with this related wealth and asset management issues.

Competition is fierce. Target customers are not just millennials

The use of automation technology to provide investors with a more scientific and convenient one-stop financial experience is the success of smart investment advice and one of the main drivers of this technology. The algorithms used by these platforms can be adapted to each investor’s net capital value and investment goals, automatically test the asset allocation of the appropriate investment strategy, and ultimately generate an investment plan that meets the needs of investors.

With the advent of smart advisors such as Betterment and Wealthyfront, traditional financial institutions such as Merrill Lynch and Schwab began to realize that these new fintech companies are already serving customers that are not just the thousand (low) they have no regard for (net). Instead of grouping (value) groups, they gradually pushed the market towards high-net worth, old-age groups, etc., which originally belonged to their gold owners, and they tried to fight back (submissive) one after another. From last year, these radical management agencies successively used the original products. With platform advantages, it launched its own automated investment management service to compete in this trillion-dollar-level market.

Through the investigation of 28 financial institutions, Celent found that 71.4% of the respondents said that the rise of robots has prompted them to accelerate their upgrade of smart investment technology, and the other 50% will see it as a complement to the current business model. Only 10% of respondents believe that the heated smart investment market has no impact on technological innovation investment decisions.

Adaptation and adoption are the only ways to survive

To put it simply, smart investing has somewhat dismantled the industry because they provide a more highly customized, digital, low-cost wealth management experience that will allow them to quickly expand the market as they need it. William Trout believes that the best solution for wealth managers is to use them for their own benefit and to find a balance between scaling up and customer-customized services.

In his words, “They should provide personalized services for low-net-worth customers with less than $100 or $5 million in capital. This technical process includes how you will discover the different needs of investors and how to serve them well. ”

Smart investment needs to be strengthened

William said, “Investors still need to pay for consulting services today. With the gradual exploration of smart investment promotion, they will no longer need to pay for asset management portfolio services. The development of this area is gradually commercialized, while smart investment The exploration of Gu also needs to go deeper."

What kind of level is more in-depth? By 2020, we will see that intelligent investment advisers can provide dynamic investment management analysis based on artificial intelligence and machine learning. These "super intelligent investment advice" can rely on artificial intelligence in the pattern recognition, automatic learning and other technologies for portrait production, intelligent backtesting, and today's "if / then" these algorithms are different.

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