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Fintech has taken the financial services industry by storm. Yet despite all the talk of disruption, fintech start-ups are just as vulnerable as those in other industries. So what separates the winners from the losers?
In the first installment of the Fintech Files series, Gregory Gibb, chairman and CEO of Lu.com, recently shared his perspective with me in Shanghai.
Larry Cao, CFA: What skills do fintech firms need to acquire to build a successful business?
Gregory Gibb: For the start-ups, you need three things to be successful. In the peer-to-peer business, you better start with at least two of them. One is you need a large flow of customers. Second is you need a large amount of data. And third is you need very strong credit risk skills. The number of small start-ups that will actually become big peer-to-peer winners is going to be a very small number. It’s going to be in the tens, not in the hundreds or the thousands.
What do you think is preventing the average P2P businesses from getting bigger in China?
Most start-ups don’t have access to good credit data. They don’t have it over time. They don’t have it in scale.
How helpful are the credit bureaus in that regard?
If you are talking about the credit bureau in Beijing under the PBOC [People’s Bank of China], it’s not bad. Is it as good as Hong Kong’s? No. But it’s 70%–80% there in terms of the broad data about the basics, such as ability and willingness to repay. It’s definitely a predictive tool that you can use, and it covers 300 million-plus consumers in China. There’s also a lot of third-party data now becoming more available in China from all the e-commerce and mobile phone users.
Do e-commerce firms actually have more helpful data compared to the credit bureaus?
I don’t think their data forms a sound basis for credit decisions. It may help you make better decisions, but if you just took e-commerce data and said, “I know that John is spending ¥5,000 on Taobao and he likes to buy shoes and whatever,” it doesn’t actually help me make a decision.
Right, you need a model to leverage the data in making a decision.
This can be done with social media data. For example, Webank has been very successful in prescreening WeChat customers to become borrowers. And here’s lots of things that I don’t know how each of these factors have ways to work in their credit model. They have correlated this to credit, but you’ll need to go through a cycle to know what’s really predictive.
Do big technology firms such as Amazon, eBay, Alibaba, and Tencent present more of a threat to financial institutions than the fintech start-ups?
The key in this game is whoever can use the interface of technology and data well to create two types of products. There are financial products which are notional. There are internet products where you see innovations in customer experience, usability, and ease of use. And you [have] to put those things together.
Speaking of offering financial products with an enhanced customer experience, financial institutions seem to have the upper hand in the robo-adviser business.
I looked at this about a year ago, wondering why robo took off recently in the United States. Why didn’t it take off 10 years ago? I think it basically [comes] down to two reasons:
One is the ETF market in the US is becoming extremely efficient and the main investment tool of a robot is allocation among ETFs. Two is that smartphones have created a user interface that makes people feel comfortable doing asset allocation in a reasonably easy way.
Robo in China will actually not take off that quickly because I don’t think you have the ETF infrastructure here in China. You don’t have low-cost advantage. You don’t have the long-term investment orientation.
Good point on the regional difference. It does have a lot to do with how sophisticated the markets are. It took the mature markets years to reach this point where more people understand the benefit of asset allocation.
In terms of value from robo, I think someone has done the calculation. You have to put your money to work for like three or four years at least to get the fee benefit. In China, the average holding period for a mutual fund is six weeks.
Looking back, what do you think was the key that made Lufax successful?
I think the answer to fintech is a cultural question. You actually need two types of people. You need financial services people who have expertise in risk management and product design expertise: People who understand the regulations as well as what the investors are trying to achieve. And then you need people from [an] internet background who understand how the online world works, i.e., customer acquisition, customer management, and simplifying products.
It’s very hard for people from internet backgrounds to work for banks. Probably the most important thing is to set up a separate arm within a major financial services conglomerate.
When we started Lufax, Peter Ma said if I just set up a department in insurance or the bank, it’s going to be hard for me to get the people. So he took a different angle on this. We hired more people form the e-commerce industry. We got people from the payment industry. These guys don’t wear ties. They wear shorts. You do have to find a way to get the expertise and get the different groups of people to interact.
So you can get the benefit of teamwork. What are some of the other critical things you had to get right?
The learning we also had was that open platform model is the superior way to build the business. Financial services still have got a lot of expertise in risk management, etc. It’s not like you hire 100 guys, you’ll get all that. We now source 70%–80% of our flow from partner financial institutions — products such as money market funds, mutual funds, and insurance products. Customers can connect their bank accounts with the platform. We have never had enough products to satisfy customer demand.
What do you think is the endgame?
Who wins in fintech? There will be a couple of start-ups. But there will also be a couple of traditionals.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
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