“We focus on two core segments: small business owners and the middle class for wealth management… We have over 100 million small businesses in China that make up 60% of the GDP. Personal wealth in China is $25 trillion USD; almost 40% comes from the middle class.”
Gregg Gibb is chairman and CEO of Lufax, a leading technology-empowered personal financial services platform in China.
Fintech in China is a story of first world technology meeting emerging market need. The goal is to make retail borrowing and wealth management easier, safer and more efficient. This focuses on two key groups: small business owners and the middle class for wealth management. Being part of the Ping An group enables greater financial synergies in matching the investment needs for customers, using tech and AI-powered tools. “For what’s driving demand, for small businesses it’s the availability of credit.”
Saving rates in China are very high, but the financial asset formation is still very low. A lot of Chinese wealth is still sitting in deposits and this has been driving asset managers into China. The regulations have been pushing for capital market development and the AUM in the market is greater than 25%.
LISTEN AND SUBSCRIBE
SPEAKER
Greg Gibb
Chief Executive Officer
Lufax
MODERATOR
Anthony Scaramucci
Founder & Managing Partner
SkyBridge
EPISODE TRANSCRIPT
John Darcie: (00:07)
Hello everyone. And welcome back to salt talks. My name is John Darcie. I'm the managing director of salt, which is a global thought leadership forum and networking platform at the intersection of finance technology and public policy. Salt talks are a digital interview series with leading investors, creators, and thinkers. And our goal on these salt talks is the same as our goal at our salt conferences, which is to provide a window into the mind of subject matter experts, as well as provide a platform for what we think are big ideas that are shaping the future. And we're very excited to talk about some of those ideas today with Mr. Greg Gib. Uh, Greg is the chairman and chief executive officer of Lou facts. And he's been in that role since December of 2011, uh, before joining paying on, uh, Mr. Gibbs served as the global senior director of McKinsey and company, and subsequently the operating director of Taiwan, Thai shin, financial holding company.
John Darcie: (01:01)
He has more than 20 years of work experience in both multinational and domestic companies of the financial and investment industries. He had obtained a bachelor's degree in east Asian studies at Middlebury college in Middlebury university. Excuse me. Uh, Mr. Gib was introduced to the national 1000 for an expert plan of the organization department of the CPC central committee in 2012, awarded the Shanghai top 10 financial innovation figures of 2012 award and honored as the China top 10 leaders of internet finance in 2013 for his unique and widely recognized insight about innovative financial services. Mr. Gibbs is the author of two great books, uh, banking and Asia, the end of entitlement and banking and Asia acquiring a profit mindset, which introduced bankers development opportunities in Asia. Uh, the way this talk is going to go today, Greg is going to give a presentation about the future of, uh, innovative finance, uh, in China through the work that Lou FACS is doing. And then we're going to host a Q and a session after the presentation with Anthony Scaramucci, who is the founder and managing partner of SkyBridge capital, which is a global alternative investment firm. Anthony is also the chairman of salts. And with that, I'm going to turn it over to Greg first to give a presentation about Lew facts and the FinTech ecosystem that's building in China. Go ahead, Greg.
Greg Gibb: (02:23)
Right. Thank you, John. Uh, so I would, uh, uh, move through pretty quickly here, but I, I know we have some time for questions, uh, at the end. Um, if we could just go to the next page, um, the, the really the story of, um, a FinTech in China is, is first-world technology meeting, emerging market need. Uh, it really, uh, tried to address a lot of, uh, unmet, uh, requirements of the market here. And we really try and make our retail borrowing and wealth management easier, safer, and more efficient. So that's kind of our positioning in China. Um, if we go, uh, and of look at our unique positioning, our highlights, it starts with the fact that we really focus on two core segments in China, uh, small business owners and the middle-class for wealth management. And these are two very large markets that are evolving quite quickly.
Greg Gibb: (03:15)
The way we do it is through a unique capital light hub and spoke model, which I'll go through. And the entire process end to end in all that we do is really very tech and AI driven. And this is really tech that allows us to select the right clients and match them to the right product in a totally digital environment. We do benefit a lot from the fact that we're part of the pig and group and ping on has more than 200 million financial service customers here in China. And that creates a lot of synergies for us and our team. You know, we're talking about FinTech. Our team is quite unique in the fact that we're very deep on the fin side, probably deeper than any other platforms that are operating here in China. Everyone knows China obviously has been the second largest economy since 2010.
Greg Gibb: (04:01)
The areas that we focus at number one is small businesses. So we have more than a hundred million small businesses here in China that make up 60% of the GDP. So it's a big part of the economy. And then on the wealth side, you can see that the personal wealth in China, sorry on the last page is about 25 trillion us. And almost 40% of that is derived from the middle class who has very quick needs emerging as the economy evolves. Um, if we look at the underlying what's driving growth in China in these spaces, is it for the small business owner? The key issue is availability of credit. And you can see here that the leverage ratio in China is still lower than the U S small businesses in terms of their load balance to income ratio is 27% versus 41% in the U S and the availability of financing to these small businesses, particularly those that don't have collateral from the banking system is quite poor.
Greg Gibb: (04:59)
So there's actually huge unmet need, and that is really need that. We're tapping it just to be very clear. What we're doing here is we're serving the individual. Who's a small business owner, but the money that we land is used for their business. And this is really kind of a unique space here in China that allows us to grow north of 20, 25%, uh, in this, uh, in this area on the wealth side, everyone knows savings rates in China are very high. What's very interesting though, is the financial asset formation is still very low. So about 15% in financial assets of total personal savings versus 74% in the U S. And so we have a situation here where a lot of the Chinese wealth is still sitting in deposits, but that is really mobilizing, you know, you've, you've seen a lot of headlines over the last year about asset managers trying to get into China.
Greg Gibb: (05:49)
And that's really because the regulations are pushing for capital market development and pushing retail to go into those markets with a lot of new products. So you have a big shift in wealth in addition to growth. So this is a space that the AUM in the market particularly online is north of 25% growth, probably for the foreseeable future. So quite a large foundation. Um, if we go here, I just want to talk a little bit about, uh, how we play. So in our two core spaces, starting on the left here with retail credit facilitation, what we're doing is sourcing small business owners, we're evaluating them. And then through our tech platform, connecting them to more than 50 funding partners real time. So the whole process, once we contacted a customer, everything is done digitally, the evaluation and the funding of that loan takes less than 30 minutes.
Greg Gibb: (06:43)
And that is all connected through a network of more than 50 partners that we work with to get that done. And again, through the sourcing, the, the, the underwriting, and eventually the collection, all of that is done digitally. And we're what we're doing here is really providing larger tickets, longer term loans to this, this group of customers. And we benefit a lot from the fact that we've been doing this for 15 years. So we've accumulated a lot of proprietary data that really allows us to make those risks decisions. On the right hand side here, we have our wealth management hub here. What we're doing is connecting the rising middle-class investor to more than 400 product providers adhere. The tech is really about doing the matching is getting the customer into the right product. And increasingly those products are all capital market driven. So as they have daily volatility, then following up with content to give customers the right direction.
Greg Gibb: (07:39)
So they're building the right portfolios for themselves. And so this whole process is done and recorded on blockchain to really make sure that customers in terms of suitable selling and everything is well tracked. And you could handle any, anything that happens as the markets evolve. If we go to our market position. So at retail credit, this space, we're number two in the market. And this goes back to June last year, where we had about 500 billion renminbi in loans that we had helped facilitate. And that was the first half of last year generating about 24 billion renminbi. I'm sorry, 20 about 24 billion. Maybe what's interesting. Here is everyone always asked us, how big are you next to ant because we're number two and it answers number one. So ads is roughly four times our size at the same time period here. What's interesting though, is we were generating about 80% of their revenue.
Greg Gibb: (08:34)
And so this starts to speak to the dynamics of the segment that we're serving and the way we do it. It generates a very high profit margin on the wealth side. We're number three in the market, that period last year of June 375 billion in AUM, and that's about 500 billion and trading volume on the platform. So we're in a very strong market position to the space that continues to grow quite quickly. If we go to page 10 here, again, the comparison with ads, because then whenever I have a chance to talk to investors that, you know, half the questions are, how do we compare with ant? And so I'll just take a second here. If you look at the borrowers that we serve, our average ticket size is roughly 20 to 30 times the average ticket size that ad served. So we're really helping small business owners provide them funding to manage their business and has really built themselves around a small ticket, shorter duration consumption loads.
Greg Gibb: (09:33)
And so there's a very different in terms of segment and size. And there's a similar story on wealth management where our average investor is about four or five times the size of an investor. And so that's one big difference is really segment. The second is we really are deep in our focus for the retail credit and for the wealth management in Anta obviously is a super app. So they're covering a broader space. We're very focused where, whereas they're broader. And if you look along the bottom here at pre-tax margins over the last couple of years, we've, we've always been north of 30%. So we grow at nice double digit levels, but we've always sustained that 30% plus pre-tax profit margin. If you look at the right here, Andrew is obviously grown very quickly, but as they have many different businesses ranging from payments to insurance, to other super app functions, they have to double down and invest often as they build their businesses.
Greg Gibb: (10:27)
So they've had a much greater degree of volatility in their net margins over time. So there is a difference of profile in terms of how we, how we've grown over the last couple of years versus apps. If we go here, I just want to go a little bit deeper into how our platform works. So we're talking about small business owners. These are, these are customers that we're serving as individuals. So all the lending is to the individual. They typically will have five to 20 employees. Their typical annual revenue would be one to 2 million us dollars or less. So these are really kind of micro businesses, but these are very interesting individuals in the sense that a lot of them have life insurance policies, you know, 60% of them own one or two properties, individual properties, but 60% of them also have not been able to get an unsecured loan from any bank in the last five years.
Greg Gibb: (11:23)
Banks in China really only want to serve customers who have collateral. And obviously Jack had his famous comment about how he saw the banking sector, which I won't repeat here, but it is an issue that these small business owners really don't have access to, to capital without collateral. And so we're really serving them mostly in an unsecured with an unsecured product to meet their needs. And the typical loan size is about 25,000 us. And the typical duration is about two to three years. So we source these customers. We have this, we do actually have a very large offline Salesforce of about 60,000 people around China. We also work with ping on who obviously has a very large set of insurance businesses that helps Reaper customers offline to our online platform. And then the hub in the middle here basically does all the analysis, does all the connection to the funding and then follows up on collections and I'm to the right here or our funding partners.
Greg Gibb: (12:18)
So we work with more than 50 bags, more than five trust companies, and a number of insurance companies will provide part of the credit enhancement in the model we take about today on new loans, about 20% of the risk. And the other 80% of the risk is born by either our credit enhancement partners or our funding partners. Just to talk a little bit about the data side of this. So we spent a lot of time really evaluating that individual, and we also spend time evaluating their business, and we built up 15 years proprietary data to do that. And that's all going in obviously to our database. And we're constantly using machine learning to refine how we judge risk for these individuals. We priced the loans today, anywhere between 15% and 24% APR. And again, those credit decisions with our models today are all made. Now, in a matter of minutes, we actually don't take any information, physical information from the customer.
Greg Gibb: (13:16)
Everything they do is authorized through the app. We then scan all of the data that we have and then make a decision. And increasingly if there's an interface with the customer to ask them a few more questions, if we need a little bit more understanding, that's all done with AI robots today to drive that interaction, our Salesforce obviously very large offline, but we direct them to where we think the best customers are, uh, to help get the right quality. And then when it comes to collections, a lot of that is done today by chatbots and differentiated with the data. So maybe just giving you a feel of how this kind of looks today from the perspective of a customer, a small business owner, applying for a loan. So we'll play a short video here, so you can see how the process works
Speaker 3: (14:05)
As the retail credit facilitation platform of Lew fax holdings. Hang on. Kuwait always strives to provide innovative solutions to our massive client base ping on Pook. We introduced the first AI plus video loan application experience in the world by leveraging several technologies to create a redefined borrowing experience for every customer
Speaker 4: (14:23)
[inaudible] [inaudible] [inaudible] [inaudible], [inaudible]
Speaker 3: (14:39)
Seamless credit approval supported by our personal and SME big database credit inquiry platform, making loan applications more efficient.
Speaker 4: (14:47)
[inaudible]
Speaker 3: (15:03)
Our intelligent voice recognition technology frees our customers from any text input, our multiple cutting edge anti-fraud technologies and AI instant approval help achieve a frictionless customer credit application process and zero waiting time for every customer
Speaker 4: (15:16)
Employee do Tony [inaudible]
Speaker 3: (15:23)
Our AI customer services able to provide real-time assistance and give customers a secure application process video 3.0 ping on poo quick redefining the loan application process with AI plus video technology, loopback holdings, better technology, better financial life.
Greg Gibb: (15:42)
So what you saw on the app, there was actually our chat bot. So that's not a, that's not a real person. Um, who's really driving interaction. Cause what we wanna do increasingly is just be able to ask customers a series of questions that we then validate with more than 50 million data points in the background, in terms of this proprietary capability we built up over the last 15 years to help make a credit decision. What are the, what are the technologies we do apply while they're interacting with the app is when we ask them questions, is, is facial recognition and lie detection. So, you know, if the, if the question is being asked that the answer looks a little bit strange in terms of their facial recognition, that goes into the credit decision. So it's really a very tech driven application and that really flows through also to how we source the customers, how we drive our Salesforce to go into various cities in the various parts of the cities to try and find customers that have those needs, who we think will also be good credit.
Greg Gibb: (16:39)
So we kind of start that from the, from the upfront and then collections, we do have 9,500 collectors in nine centers, but most of the collection is driven up front by chatbots. And then for the harder cases, a human will come in as needed. So really the end to end processing here is all driven off of our, off of our platform. You know, a point here on data, there's a lot of debate about what types of data could you use today to really make good credit decisions. And we break data into two types. We break it into sort of what we call a hard credit and financial data, which gives you some sense of the person's background and how they've bought insurance over time, how they paid their bills over time, but what we call financial data. And then there's behavioral data, which is e-commerce data, social data.
Greg Gibb: (17:29)
And when you're, when you're making a credit decision, you're really looking at two angles. The first is the person's willingness to repay. And the second is their ability to repay and what we find. And you see these two bars here on the lap when we're baking the first part of the decision on willingness to repay both financial data and behavioral data are very useful in the model. Financial data here is weighted at 58% and social and other data at 42%. But given that we're making longer-term loans for larger amounts, when it comes to the predictiveness of what is going to, you know, this person's ability to repay, then the financial data in our model gets weighted at 92%. And so this is really unique because very few or really most of our competitors do not have the degree of financial data that we have over these 15 years refined around this customer segment.
Greg Gibb: (18:21)
Our other tech platform competitors do have a lot of behavioral data, but we found that that behavioral data is really only effective for small short-term lows because when you're making a large loan, what really matters the ability to repay. And so that's really our unique underlying capability here to serve this segment. And it's very hard for others to replicate what we built in terms of that offline to online sales capability, then having the data to really make the right credit decisions and then having funding partners who, who trust your data, capabilities and analysis to then fund those loans or in the case of our credit insurance partners to provide the credit enhancement. So this is really what we've been able to tie together over a number of years. If we go to the wealth side, what we're doing here is the middle-class in China is a population of about 150 to 200 million people.
Greg Gibb: (19:17)
And the customer where they were serving typically has investible wealth of anywhere from $5,000 up to about 500,000 us dollars. So they don't quite fit into the bucket yet of being high net worth. When they go to a bank they're not getting served by a private banker, they're still really only having access to counter services. But these customers, when they start to have a couple hundred thousand us dollars, they actually need to figure out how they're going to invest for their retirement. There's been a lot of change on the regulatory side in China, where the whole wealth management market has shifted and is shifting from purely fixed income to customers, really having to start to explore equities and build portfolios and get the right diversification. And it is a challenge because today, when people buy mutual funds in China, if they buy a fund directly, the average holding period is about a hundred days.
Greg Gibb: (20:10)
You know, when you start to get them into portfolios, we can get that up to 200 days, 300 days, which is obviously critical to generate a healthy return. So what we're doing on our platform is connecting these customers entirely online. And then we have 400 product providers in the background, and it's really using the data on the customer and the product and the markets to drive matching to really get them to the right product and the right portfolio over time. So they can start to generate those sustainable returns because in China, fixed income and interest products, a lot of the money's still 50% of it being a deposit today in China, obviously the rates are going down. And so if a Chinese retail investor wants to beat inflation, they have to nail gain exposure to capital markets. And so that's what we're really doing here is driving the reallocation of that wealth and giving the customer a service level that they would normally get by the time they were a private banking customer, but we're giving them that expertise in an online environment at a lower entry point.
Greg Gibb: (21:11)
And there's really relatively few platforms that focus on this segment to our large competitors, typically who have a larger, broader customer base are typically serving the more mass market. And it's really through expertise that we're differentiating for our target group. The entire process that we have on the wealth side has a lot of data on the customer to really figure out what their wealth level is, what their risk tolerance is. And then we're matching that with a lot of data from the product side. And then we're doing AI driven, matching. We have 8,000 products on the platform. Customers don't want to see 8,000 products. They want to see the two or three products that are relevant to them in the current market condition. And increasingly we're using that data and our knowledge of the customer to get them into portfolios so they can get more diversified.
Greg Gibb: (22:00)
They can drive up those holding periods. And once a customer goes into a product, we have chatbots that will nudge them, which will remind them of things they should do or not. Do we also do social comparison to say, you know, what you're doing is similar to people that are similar to you, you're better or worse in certain ways, right? You're you're, you have too much concentration risks. You're actually doing a better job in certain areas to really educate the customers on how to better invest in the whole process, what the customer does with us on the app, everything that they see, every box that they click, every contract that they agree to is all recorded on blockchain. And this really helps us ensure suitable selling throughout the process. You can place a situation where a customer buys a product, six months later, they lose money.
Greg Gibb: (22:46)
And they said, I didn't know. And so really having that capability as an independent verification is critical in the regulatory environment as well. So all of this is done in, in, in lieu facts, but we do benefit from being part of the pig ecosystem and ping on obviously is a, is a huge financial platform in China with insurance banking, securities, et cetera, and invest very, very heavily in technology, facial recognition, voice recognition, AI chat, bot development. And so we, we have early access to that technology. We have our own everything we do with the customers, our risk, our interfaces developed by ourselves. But behind that, we'd better put a lot for the big investment that God has in technology. Obviously being associated with ping on from a brand perspective is very, very helpful and helps drive down our acquisition costs for both borrowers and investors.
Greg Gibb: (23:43)
And then given the amount of data and the pig has, we can test our models against, against a broader base of customers by the time that we rolled about on our platform. So the synergies we gain here out of analytical insights that we gain here are substantial and a big benefit for us politely on page 18 here, obviously regulation in China, FinTech is a big issue. And I think what distinguishes our team was we do have very strong technology, but we probably have the deepest bench in terms of financial DNA of having that expertise internationally, domestically to continue to revise our strategies, the way we operate to meet the market needs, but also to really anticipate the regulatory environment. So maybe I will stop here and we can, we can move into questions.
John Darcie: (24:36)
All right, fantastic. I'll let Anthony, uh, start off with the questions, but I have a lot of questions for you as well. It's fascinating stuff that you guys have
Anthony Scaramucci: (24:42)
Built. Listen, it's a terrific presentation, but also congratulations obviously on the company, but my first questions or somewhat us centric, if you forgive me, because we, we really want to make this introduction, Greg, to the U S investors as among, among other investors, of course, but how has the Chinese economy evolving? How is it evolving in terms of small business formation and household affluence, even prior to COVID-19 and what impact has the pandemic add on those trends? Oh,
Greg Gibb: (25:20)
The, the issue for small business owners in China, pre-crisis pre COVID and today remains very large the same, which is they're a very big part of the economy, but a lot of them just cannot get funding from banks. And the what's happened as a result of COVID is the policy push around small businesses has increased. So what we're seeing from our funding partners is a lot more demand for more asset, particularly in that small business space, because policy is driving them to do more. But our funding partners here, Anthony are small, medium sized banks. They don't necessarily have the national footprint. They don't necessarily have the scale. They don't necessarily have the data in order to be able to serve these customers without our cooperation. So the COVID impact has been that the banks given the policy changes, want to do more business with us.
Greg Gibb: (26:15)
What we've also seen, particularly on the wealth side, you know, that, that wealth formation with all this, all the things that people typically talk about with tied up, right, the growing urbanization, the growth of the middle-class, all that stuff. What we saw happen in COVID of course, was a much accelerated move to online. You know, there was, there was in China as well, a couple of buds where people couldn't go to banks didn't want to go to banks and they have come to us much more dramatically. Obviously the stock market in China, despite recent days, being down over the last 12 months, you know, the average mutual fund returned last year in China was north of 40%. So you've seen a real drive again with the stimulus packages, but going on around the world, accelerated online trading and investment behavior. So I think things that were true before COVID are still true, but there was an acceleration of some trends there,
Anthony Scaramucci: (27:10)
You, you, uh, you talk a lot about the differences between the consumer and fit and household financial behavior related to debt and investing. So how would you compare that between China and the United States? And are there, are there cultural forces that are unique to each country?
Greg Gibb: (27:32)
I think it's harder to say that it's there's cultural differences. I think as, um, you know, as people get wealthier and as people have more businesses or they have more retirement concerns, uh, you know, China's regulation and people's behavior does look more and more like rest of world over time. I think that the biggest differences are with the small business side is that in the U S retail banking, small business related banking has developed over the last what, 50, 70 years, right? It's, it's quite, it's quite well developed in China. You know, retail banking is kind of 20 years old or less. Um, and most banks really don't specialize around small businesses. So it's really a supply side difference. I would say in China for the small business side on the wealth side, the biggest differences is really this. Most of the, of the, of the wealth product in China over the last decade was essentially debt to real estate companies repackaged as wealth product.
Greg Gibb: (28:37)
So it was a fixed income market in the last two years under the central bank, all these policies have come out to really make all products standardized and to basically be tradable on the exchanges. And so wealth is being pushed from the debt side really to the equity side. And so this is driving a huge shift in, you know, if you look at the United States, you know, what percentage of savings are in equity or mutual fund products? I guess it would be north of 30, 40% in China. That number is less than 10% today. So there really is this huge shift that's being driven by policy. And frankly, what China's trying to do, what the overall regulators are trying to do in China is improve their debt to equity ratio. And given the retail money is such a big part of the equation here. You know, they're trying to get less debt on the books and really build up more of the equity side. So there's this huge shift in the way that wealth is being driven.
Anthony Scaramucci: (29:33)
Talk about, talk about AI for a second and the role that it plays in the underwriting process and what conditions in China make it a leader in the development of AI.
Greg Gibb: (29:45)
So really over the last decade, particularly with the huge penetration of mobile and mobile phones, there's obviously been a huge amount of data that's been acquired throughout the society, obviously huge, fast growing e-commerce behaviors and the rest. And that data has been increasingly used and tested against very important decisions on about customers and product at risk. And so the huge availability of data on a very huge population now acquired over a decade, has really allowed platforms like ourselves to use a lot more variables that allow you to judge risk in an online environment or a mobile environment that wouldn't have been possible, you know, seven, eight years ago. And so, but also this data is changing, right? China is obviously a huge place. The provinces are very different, right? The economics across the provinces are very different. So you have to be able to tune for different geographies. You have to be able to tune for different customer segments and be able to do that dynamically so that the availability of data, the deep penetration of mobile, and then really the experience now to be able to do that in a totally digital way with very high efficiency, just keeps, keeps turning on itself. And so with the machine learning and everything, you're getting a lot of optimization.
Anthony Scaramucci: (31:14)
You, you talk about, you know, how does the relationship with ping and make you well positioned to tackle the financial needs of the Chinese consumer? Does that tell us a little bit more about that relationship? Sure.
Greg Gibb: (31:27)
So pig out, as you may know, his started at about 30, 33, 34 years ago in China, one of the largest insurance companies in the world now, but it has 27 different financial licenses as a recent count. So it's very deep and broad across the market. You know, people that have ping on insurance and the like are typically these middle-class consumers, a lot of them are small business owners. So that foundation gives us a lot of access to very good customer. Given they've been operating in these spaces for 2030 years. It also gives us a lot of good data to tune our models. And it also has a very strong brand, but increasingly in FinTech, the issue is also regulation, right? So the relationships that ping on his builds over the last 30 years with regulators as a trusted party, the way that it handles all kinds of compliance risks and credit risks is also very important to earning trust of those that you're working with. So ping on is a, is a, is a huge brand advantage. It's a huge technology advantage. It's a big source for efficient acquisition of customers, but also increasingly it's a very important base of trust as you deal with regulators, as they're kind of redesigning how they want the future to look,
Anthony Scaramucci: (32:48)
Chinese regulators have recently adjusted rules around micro loans and bank, internet lending, which most notably shell, the IPO of ant financial, which we both know. But can you explain the reasons for that regulatory decision and what impact if any, it has on businesses like Lou Fox. So
Greg Gibb: (33:11)
Basically over the last five years platforms like ourselves have started to provide a lot of the facilitation for credit and China for retail, for small business owners. And the regulators were looking at this and saying, okay, so you guys are sourcing the customers. You claim to have great data models. You claim to have the risk under controls, but the funding is coming from our banks and do our banks really know enough about what's in the black box at the end of the day, the banks and the ones that have to hold the capital. It's the financial institutions that are bearing most of the risk. So, you know, this has been an issue that the regulators would watching for a couple of years, but really September last year, the regulators started to signal to people like us, that we want you guys to have skin in the game, right.
Greg Gibb: (34:04)
You know, yes, the funding can come. You know, majority of the funding, 70, 80% could come from financial partners, but you as a platform need to bear 20 to 30% of the risk. And you know, you've got to bear the right capital behind that risk as well, because if you get it wrong, we want you guys to, you know, to share the pain and make sure that there's therefore no moral hazard, that as a platform developing very quickly, that, you know, you basically grow very quickly and then someone takes someone else has to take care of the problem.
Anthony Scaramucci: (34:32)
What did I miss? John Dorsey? Anything pretty exceptional story.
John Darcie: (34:36)
Yeah, I got, I got a few questions myself. Uh, Greg, if you don't mind, you talked about blockchain, how you guys are at the front of so many different movements across technology and FinTech specifically, whether it be, um, you know, using AI, using facial recognition for credit worthiness as a, as a variable under credit worthiness, but blockchain, the blockchain piece of it is very interesting to me. And in China, you know, there are certain restrictions on things like Bitcoin, but China is very forward-thinking as it relates to central bank, digital currencies, they're digitizing that you on as, as most viewers probably know, how did you guys think about a development of blockchain? Why is blockchain technology for, for you guys, the best solution, and what do you think the future of digital assets and blockchain and Oregon and technologies are within China? So
Greg Gibb: (35:24)
As you move to a world where everything is, is being done through a mobile phone, and you're, you're dealing with transactions in the, in the, in the tens of billions and hundreds of billions of dollars, and you've got contracts and you've got verification items that are very important, both in terms of verifying that the customer is who they say they are, that the money is from where they say it is. And that those contracts are agreed as they say, you know, if it was just left to us as a private company to say, listen to us, we've, we've started all in our database. If there's any issues, just check our database. You know, people are going to challenge that heavily. And so really having the ability to not only as your data comes in that you're using to make decisions, but everything that happens on the platform to put that back into an independent place that anybody can go look at, right.
Greg Gibb: (36:16)
If the regulators want to know what's going on, it's always there. And so that independence and the certainty that brings therefore the trust that it brings to a purely digital world is very important. And obviously China is a big and fast changing place. And there's a lot of physical paper that you just would never trust. Uh, you know, we, uh, if you went back five or six years ago, part of our credit processes, people had to bring it income proof and house ownership prove all that sort of thing. And there was just a huge amount of fraud, right? And it really wasn't efficient. And so once you're moving to that blockchain to build the trust, to have that independence, and then to really enable the processing and all kinds of ways down the path just basically helps create that essential trust across Chinese commerce. That just is not as easily occurring in the physical world.
John Darcie: (37:05)
Yeah. It's fascinating stuff. In terms of the products that are on your platform, you talked about how you have a wide suite of products, but you don't, you don't want to inundate people with, you know, questions about what type of products they should be allocating capital to and use AI to match them. What types of products are on your platform? You talked about, uh, you know, less yield oriented products, fixed income products and more equity type of products. What are the, what's the product suite that you have on your platform? What are you looking for in a product in terms of onboarding and onto the platform, and how does that matching engine work in terms of identifying what's right for an individual?
Greg Gibb: (37:42)
So there really are two parts to it, but starting with the product side, we have a broad range of product. So, you know, at the high end, you've got a private equity, uh, product on the platform. Uh, you've got, you know, 4,000 mutual funds or more on the platform. You have a growing number of insurance products on the platform. You've got structured products at various levels. So we were really looking at how to drive a rating of those products. And here we're looking at who's the provider at the fund manager level. We're looking down to the level of who is the fund manager, right? Maybe a great fund fund manager change yesterday, someone else was running. It, that's something you want to know. And so having the data and being able to update that is what we really call you to know your product at multiple levels.
Greg Gibb: (38:31)
And then on the other spectrum is the customer, uh, and the early the KYC, which has kind of a broader KYC, which is really knowing what their background is. You know, when we used to do this in the beginning, we would like customer pill and surveys. They still do. But what they were saying in the surveys and what we found through third party data was, was generally not true people who said they didn't have money off and had money and vice versa. And so really being able to try and get a firm understanding of a customer's experience, then determines what we show them on the platform. So if a customer really comes across to us as conservative, they're only going to see products that are right for a conservative customer. You know, if we can get comfortable that the person is a qualified investor, does have substantial net worth that they could maybe see private equity products on the platform.
Greg Gibb: (39:21)
So it's really a screening process. It's then really a matching process. And of course, what product is right for the customer depends on what's already in their portfolio. It depends what's happening in the markets in terms of what to put forward or suggesting other matches they need to have to get the right balance. So it's a very, very real time processing to get you to those three or four products that really matter the most to you today. And it's really getting China to probably leap frog a bit from being purely fixed income in the past to moving to kind of, you know, the right portfolio strategies today. But a lot of that is happening in an online environment rather than a counter by counter visit.
John Darcie: (40:02)
Right? Last question from me. So we have a friend of ours name is Winston ma. He used to work for CIC, uh, sort of in the venture capital wing of that organization. He wrote a great book about the phenomenon you were talking about earlier, where the explosion in mobile devices and the penetration of mobile devices within China gave rise to this massive dataset that has enabled the rise of AI and this data-driven economy. Those are two sort of macro trends that have developed over the last decade. As you look out over the next decade, what are the major macro trends that you're looking at in terms of continuing to see around corners, uh, for Lu facts? Is it something like quantum computing? Is it deeper penetration into something like blockchain, but what are the big technology trend that you have your eye on or multiple trends, uh, in China and around the world right now? So,
Greg Gibb: (40:51)
You know, I think at the end of the day, um, with financial services, customers still want a personal touch. They want the tailored advice as products get more complex as capital markets become more part of the solution and there's more volatility. You know, they still want someone to hold their hat and we have to be able to in an online environment, we have to be able to provide that increase touched over time, that increased expertise over time. And in our view, the only way to do it, we think the biggest driver, at least for the next three to five years is advancing your AI so that you can make your interactions, that you can make your chat bots or how chat bots evolve into other service forums to just make it very directive, very personalized, and to make customers as comfortable as possible with the process.
Greg Gibb: (41:40)
You know, and if you think about how that's going to change the traditional financial industries, which are still heavily counter based in individual driven, right? Your ability to drive central control to really make sure customers are getting the best advice that it's standardized, that it's tested. And then it's rolling out consistently in doing that with a very high touchpoint at very low cost is where we see, you know, that's going to be a huge impact. It's gonna be a huge impact because some companies will do it well. And there'll be a huge impact because the other companies who don't do it well are going to find margin changing very quickly. They're going to find customers expectations on service levels, changing very quickly. So, you know, we, we, we do like the technology angle. We do like to invest in technology, but for us, it's really the application at the end of the day, it's about service and it's using that technology to create that personal service at a much lower cost point.
John Darcie: (42:34)
Greg, it's been a pleasure to have you on salt talks and they do have a final word before I, uh, I read us out here.
Anthony Scaramucci: (42:40)
Listen, I think it's an, it's an amazing business. You're intersecting a lot of things that are going on at the same time. You're, uh, innovating through with AI. Uh, you're making things, uh, easily available over the blockchain. And, uh, you're obviously prepared for the future. And I would say that a lot of financial services companies, Greg frankly, are Napa prepare for the future. They're operating off of an older model. So it's an interesting vision and a great business plan. Thank you so much for joining us on salt talks. Thanks very much.
John Darcie: (43:13)
And thank you everybody who tuned into today's salt talk with Greg Gib of lieu facts. Just a reminder, if you missed any part of this episode or any of our previous episode of salt talks, so you can access them on our website@sault.org backslash talks, and also on our YouTube channel, which is called salt tube. We're also on Twitter, we're most active, uh, at salt conference there. We're also on LinkedIn, Instagram and Facebook. And please spread the word about these salt talks. I think it's fascinating to have people like Greg on, uh, on the show who are in different parts of the world, doing really exciting things and disrupting the traditional finance ecosystem, but on behalf of Anthony and the entire salt team, uh, this is John Darcie signing off from salt talks for today. We hope to see you back here soon.