Latest / Leaders In Payments / Yinglian Xie, CEO & Co-Founder of DataVisor | Episode 268

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Yinglian Xie, CEO & Co-Founder of DataVisor | Episode 268 · Leaders In Payments

• 0:01
  Speaker 1: Welcome to the Leaders in Payments podcast, where we talk to C-level leaders from across the payments landscape.
• 0:06
  Speaker 1: We'll be discussing the products and services that impact the payment space today, as well as trends and predictions for the future of payments.
• 0:14
  Speaker 1: We will also hear stories from our guests about their journeys to the top.
• 0:18
  Speaker 2: DataVisor's mission is no matter what innovation we have, we can build some foundation and solid to protect all kinds of different use cases for account lifecycle.
• 0:30
  Speaker 2: To be something a little bit more, I would say, fundamental, across use cases, rather than just focusing on isolated solution for specific use case.
• 0:39
  Speaker 2: I find that very much exciting for feeling, because that has a way to change how the industry deal with these fraud approaches in the past.
• 0:49
  Speaker 2: So I think another exciting area is we talk about our commitment toward fighting fraud in a more proactive manner than reactive manner and has a promise to also change the whole industry landscape and change the arms race, and that's something I feel very exciting too.
• 1:14
  Speaker 3: That was Inglian Chi, the CEO and co-founder of DataVisor, and she is my special guest this episode, episode 268 of the Leaders in Payments podcast, and I'm your host, greg Myers.
• 1:23
  Speaker 3: Datavisor is a comprehensive fraud and financial crime prevention platform powered by sophisticated AI and modern machine learning.
• 1:31
  Speaker 3: Inglian talks about what makes DataVisor unique in the marketplace, how they leverage both machine learning and AI, as well as her background and why she chose to create a fraud prevention company.
• 1:41
  Speaker 3: We had a great episode ahead, so let's get started.
• 1:44
  Speaker 3: Hi, inglian, thank you for being here and welcome to the Leaders in Payments podcast.
• 1:53
  Speaker 2: Thank you so much.
• 1:54
  Speaker 2: It's great to be here.
• 1:55
  Speaker 3: Great, so let's dive right in.
• 1:56
  Speaker 3: If you don't mind, tell our audience a little bit about yourself, maybe where you grew up, where you went to school, where you currently live, a few things like that, and we'll dive back into your professional journey in a few minutes.
• 2:06
  Speaker 2: Sure, yes.
• 2:06
  Speaker 2: So I grew up in China and my educational background is in technology.
• 2:11
  Speaker 2: So I went to Beijing University and finished my bachelor's degree of computer science there.
• 2:17
  Speaker 2: Afterwards I went to Carnegie Mellon University and pursued a PhD degree there, Also in computer science.
• 2:24
  Speaker 2: My specialty is the intersection of big data analysis, machine learning and security fraud and from there on, after I received my PhD degree, worked at Microsoft Research Silicon Valley and continue the journey of research topics in the same kind of domain, the industry.
• 2:45
  Speaker 2: That's where I met with my co-founder, Feng Yu, and we two collaborated there throughout for seven and a half years before we started DataVisor, and DataVisor now is a company located in the Silicon Valley, so we are based in Mountain View, California.
• 3:02
  Speaker 3: Okay, all right.
• 3:02
  Speaker 3: Well, let's dive in and talk about DataVisor.
• 3:05
  Speaker 3: So tell the audience what DataVisor does.
• 3:07
  Speaker 2: So DataVisor is a company that offers end-to-end fraud and risk platform to help a variety of different fraud attacks, and so we protect financial institutions, fortune 500, and large organizations all around the world to combat a variety of use cases including, for example, the onboarding fraud, like a new account opening fraud, account takeover that we are familiar with, where our account was compromised in the ACH wire transfer check those typical bank transactions as well as, for example, the latest more like a real-time payment fraud, and we also battle against a variety of new emerging type of fraud, all in real time.
• 3:56
  Speaker 3: Okay, and how big is the company?
• 3:58
  Speaker 2: So currently we are a growth stage company.
• 4:01
  Speaker 2: We power some of the largest say enterprises in the world.
• 4:06
  Speaker 2: We work with many large companies, including, for example, the Affirm, like Binau Paylater.
• 4:11
  Speaker 2: That we know is a new innovation in the world of offer a new type of kind of lending scenarios to companies like Payment, like BUILDcom, and also some of the large digital bankings, the industries, including like NeoFinancial.
• 4:27
  Speaker 2: We also help other broader companies such as, for example, tribal Industry, like bookingcom Asia, et cetera.
• 4:34
  Speaker 3: Okay.
• 4:34
  Speaker 3: So how do you say differentiate your company from your competitors out there?
• 4:39
  Speaker 2: So there are a number of areas that we are uniquely differentiated.
• 4:43
  Speaker 2: I would say all centered around the core technology and the innovation and, more forward-looking, like future, next generation, like, I would say, product.
• 4:52
  Speaker 2: For one, we actually proud ourselves into our unique patented unsupervised machine learning, which is a type of cutting-edge machine learning approach that is targeting and detecting new emerging type of fraud in real time.
• 5:08
  Speaker 2: So, instead of chasing after fraud patterns, we really stay ahead of time and to change the arms race to be more proactive.
• 5:18
  Speaker 2: In that way, we can reduce the fraud by up to 60% with many of our customers.
• 5:24
  Speaker 2: And the second area that we differentiated is that when Data Advisor was founded, we were built upon the latest cloud technology and literally targeting to protect large companies from day one.
• 5:38
  Speaker 2: Therefore, we proud ourselves in terms of high scalability and low latency and therefore we uniquely positioned, particular in today's digitalized world, to protect real time fraud.
• 5:52
  Speaker 2: And as real time payment becomes a trend, that becomes, that capability becomes really important to be able to that keep up with the velocity, the automation that we need in order to make decisions in that subsequent time frame.
• 6:08
  Speaker 2: That could lead to a 5x increase in terms of early detection of attacks.
• 6:12
  Speaker 2: And also the final area that we are uniquely different is that Data Advisor is one holistic solution, as contrast to many of other solutions that are specifically focused on isolated use case.
• 6:26
  Speaker 2: We truly are focusing on protecting the account life cycle of a variety different kind of scenarios and in the past many organizations have relied on fragmented the solution to come back different use case and might have one solution for onboarding, another solution for, for example, the traditional, like ACA transaction, another solution for cards, so on and so forth, and therefore they only get the slice of the view, which we think is not equally effective.
• 6:56
  Speaker 2: Therefore, data Advisor combines the holistic data together to serve as a platform to battle against all of this in a centralized kind of way.
• 7:07
  Speaker 3: Okay, yeah, you mentioned something there that I think our audience will definitely understand and appreciate.
• 7:14
  Speaker 3: As you know, as we move to more and more real time payments and we have consumer expectations that payments happen immediately and not take two or three days, I think that being able to fight fraud in that immediate capability is going to be more and more important as we move forward.
• 7:32
  Speaker 2: Absolutely.
• 7:32
  Speaker 2: The ability to stay on real time requires a lot of automation and also, at the same time, real time payment gives instant feedback to the customers.
• 7:42
  Speaker 2: So if the decision is not being made the right, it creates also not only like fraud loss, but negative customer experience friction as well.
• 7:53
  Speaker 3: In the payments and fintech industry.
• 7:55
  Speaker 3: Merchants and their customers have increased expectations around omnichannel commerce.
• 7:59
  Speaker 3: So, in collaboration with NMI, the fully integrated payment solution built to scale, we've launched the Be Solid campaign where, in this series, we'll explore the ability to accept payments anytime, anywhere, using any device.
• 8:11
  Speaker 3: We'll dive deep into mobile acceptance via contactless tap on phone, qr codes, wallets and more.
• 8:17
  Speaker 3: We will hear from companies like Othvia, canalote, google and more.
• 8:21
  Speaker 3: To listen to the latest episodes, visit leadersandpaymentscom or nmicom.
• 8:26
  Speaker 3: Slash resources, slash podcasts.
• 8:28
  Speaker 3: In a world full of squares and stripes, be solid.
• 8:32
  Speaker 3: We can't have a payments podcast without talking about AI.
• 8:37
  Speaker 3: So what role do you see AI playing in the payments and fraud space?
• 8:41
  Speaker 2: Yeah, so for DataVisor, we actually, from the very beginning, committed to build, based upon, I would say, the best kind of AI technology, the cutting edge.
• 8:51
  Speaker 2: We talk about the machine learning approach, including unsupervised machine learning, and the way we look at that is that in today's digitalized world, all the companies are targeting to grow their customer base and we no longer just focusing on that, I would say the low kind of rate of transactions, not isolated like events anymore, a sparse event In fact.
• 9:15
  Speaker 2: We view payments and are growing into real time and we look at the customers to be able to sign up different financial institutions that break the boundary of geographic locations.
• 9:30
  Speaker 2: We don't necessarily have to just go to the bank nearby on my street.
• 9:35
  Speaker 2: We can work with any financial institutions in the world.
• 9:40
  Speaker 2: So in that scenario, with customers, the significant growth for all financial institutions, leveraging that static knowledge and the leveraging, I would say, the business, the main knowledge alone is not enough and we got fast member growth.
• 9:57
  Speaker 2: We got a lot of data growth and how we able to leverage that data driven approach to power us, to enable that automation, that reaction speed and also that intelligence in decision is super important, and all of this based upon, I would say, latest technology in a particular, ai and machine learning?
• 10:18
  Speaker 2: Where is the technology's promise to bring a lot of value based on the data, the activities that we see every day?
• 10:26
  Speaker 3: Okay.
• 10:27
  Speaker 3: So maybe for me to understand this kind of using AI and you tell me if I'm kind of interpreting this correctly me as a consumer.
• 10:36
  Speaker 3: Let's just use a consumer example.
• 10:38
  Speaker 3: I'm logging into my bank.
• 10:39
  Speaker 3: Your system can help track all of my behavior and where I log in from and what devices, and takes all probably thousands of data points to make sure, kind of like, I am who I say I am and behaving the way I say I, like I normally do.
• 10:56
  Speaker 3: I mean, is that all part of it?
• 10:58
  Speaker 3: And then your technology just continues to learn?
• 11:01
  Speaker 2: Yes, to some extent you're touching on kind of the important, the just part of it as a company kind of grow, and that everybody must be prepared to fight fraud and the fraudsters are constantly evolving their tactics, their attacks also becoming more and more sophisticated.
• 11:18
  Speaker 2: So at the same time, kind of for us, from the defender perspective, we wanted to be able to leverage as much kind of information, intelligence, as we can.
• 11:27
  Speaker 2: Therefore, we want to be able to leverage those information where the transaction is happening, what devices coming and some of the behaviors, to be able to differentiate between the legitimate activities versus these kind of abnormal and suspicious activities.
• 11:45
  Speaker 2: And in that word, manual fraud response we talk about simply cannot keep up and this is a barrier to what the kind of innovation and therefore that's where AI and machine learning will be able to take this data holistically, looking at a variety of different dimensions, including the account profiles, the account activities, and also looking at the type of transactions and the amount of the transaction, so on and so forth, to be able to make a better decisions to protect us better.
• 12:15
  Speaker 3: Okay, okay.
• 12:16
  Speaker 3: So why is it important to look beyond just authentication tactics and known fraud vectors?
• 12:22
  Speaker 2: Well, authentication is a very important step to establish and who we are working with from the customer side, right, but authentication is just a single point of verification and we also see that attackers have many ways to get around it and so, for example, there are cases where we see account takeover, that's where when we authenticate the user and the seemingly that the request is coming from the customer themselves, but in the end, because account is compromised, it's actually the fraudsters, attackers, who we are interacting with.
• 12:59
  Speaker 2: Also, in other scenarios, there are scam cases.
• 13:02
  Speaker 2: There are scam and phishing checking kind of legitimate users off sending money to the fraudsters.
• 13:08
  Speaker 2: In this case, authentication is authenticate the legitimate customer itself, but on the other hand, it does not prevent the fraud from happening.
• 13:17
  Speaker 2: So it's very important to look beyond authentication and take an always on like a holistic approach to look after that single point of verification but into a variety of data points.
• 13:30
  Speaker 2: We just talk about those behaviors, those transaction kind of I would say amount and transaction type and the variety different areas to help us continue that analysis, to be able to make a kind of this better for our decisions over time.
• 13:48
  Speaker 3: Okay, All right.
• 13:49
  Speaker 3: So two questions about financial institutions.
• 13:52
  Speaker 3: The first one how can they stay ahead of the unknown and emerging threats as payments technology continues to evolve?
• 14:00
  Speaker 2: Well, as the technology evolved, fraudsters are also always looking for new ways to commit their fraud and attack.
• 14:09
  Speaker 2: They're constantly evolving and we are always seeing new types of fraud coming up.
• 14:15
  Speaker 2: Therefore, it's important for financial institutions to continue to evolve too, and I would say there are technologies that specifically designed to tackle the problem, particularly with the unknown and new emerging threat.
• 14:30
  Speaker 2: As I mentioned, unsupervised machine learning is one of such approaches that specifically focus on detecting and this new emerging fraud, without the needing of historical kind of loss experience or the training labels in the past, but be able to detect such novel attacks on the fly.
• 14:50
  Speaker 3: Okay, the next question is kind of like I look at it as kind of AI versus AI, right?
• 14:55
  Speaker 3: So how can financial institutions leverage AI fraud technology?
• 14:59
  Speaker 3: Obviously, like you have to fight against the AI powered deep fake threats that the new fraudsters are coming up with.
• 15:07
  Speaker 2: Yes.
• 15:07
  Speaker 2: So deep fake is an example of new emerging fraud coming up and a good example of how fraudsters are leveraging generative AI technology to implement new scams.
• 15:19
  Speaker 2: So this technology poses significant challenge to authentication methods that we also talk about.
• 15:25
  Speaker 2: They also disrupt a lot of the biometric authentication systems like facial recognition, voice recognition, as all these can be synthesized with the deep fake kind of technology.
• 15:37
  Speaker 2: So, from the defender perspective, two most important features of fraud solution must have to stay ahead of this emerging fraud.
• 15:47
  Speaker 2: A we talk about is being able to take a holistic view of leveraging a variety of different data.
• 15:54
  Speaker 2: Sometimes it's attackers can fake one or two dimensions of data we talk about with deep fake technology.
• 16:01
  Speaker 2: But well, we assess the legitimacy of a transaction using other dimensions the behaviors, the origins, the networks.
• 16:10
  Speaker 2: In different areas we might be able to see that signals that point to the level of suspiciousness of the transaction.
• 16:17
  Speaker 2: And the second area is we also must ourselves enhance ourselves with the best AI technology as well, and so when fraudsters commit these fraud, they want to commit these fraud repeatedly as they gain success.
• 16:31
  Speaker 2: So we often see fraud rings.
• 16:34
  Speaker 2: Therefore, certain technology, like we talk about the unsupervised approach, can effectively help us capture these type of fraud even when they're very much early on, like an emerging case.
• 16:46
  Speaker 2: So I was saying a summary is to really leverage AI technology to fight against these AI-powered, deeper fake threads.
• 16:56
  Speaker 3: Okay, and where do you see the payments industry?
• 16:59
  Speaker 3: And you can certainly answer this from a fraud point of view, but where do you see it heading in the next couple of years, say three to five years?
• 17:07
  Speaker 2: So we've in the past three to five years when we we retrace, that we're seeing a lot of innovations coming up.
• 17:13
  Speaker 2: So mentioned kind of real time payments across all types of transactions, making kind of financial interactions much more faster, much more convenient.
• 17:22
  Speaker 2: Also, by now PayLater have already made their mark and we expect to continue to see that in broader, I would say, areas.
• 17:33
  Speaker 2: And also we see kind of digital currency being leveraged and we also start seeing for convenience purpose in the various digital banking efforts, including digital wallets coming up.
• 17:46
  Speaker 2: So all I'm saying is we see a lot of innovations going on.
• 17:50
  Speaker 2: We will continue to expect the same trend going on become an even more interconnected technology advance and the user centric for our convenience.
• 18:00
  Speaker 2: So we will see that more such kind of newer technology coming up, maybe even in different kind of industries, different verticals.
• 18:08
  Speaker 2: You start seeing kind of even more kind of newer innovations coming up and these are the areas we expect.
• 18:15
  Speaker 2: That again poses, I would say, also the challenges to us, because every new use case coming up brings new challenge, to some extent fraud as well.
• 18:26
  Speaker 2: So we must also be prepared.
• 18:29
  Speaker 3: Do you foresee AI regulation playing a role?
• 18:33
  Speaker 3: Do you expect that to happen?
• 18:34
  Speaker 3: And, if so, is that a good thing or a bad thing for your business?
• 18:38
  Speaker 2: So, like any technology, we want to understand how the technology works and whether there are areas that the process whether it's buyers or limitations, or the risks.
• 18:49
  Speaker 2: So I do think it's also a time for us to put in that regulatory kind of thought into looking at AI technology.
• 18:58
  Speaker 2: So, from a technology itself, it's very powerful, right, but many times it depends on the practical setting.
• 19:05
  Speaker 2: What kind of data, for example, we are given to AI.
• 19:08
  Speaker 2: The data is buyers, the technology, the generated output could be buyers.
• 19:13
  Speaker 2: We could capture wrong things and because of limitations of AI.
• 19:17
  Speaker 2: So there is a technology itself, but there is the way the technology being applied in the industry.
• 19:24
  Speaker 2: So we must look at all these things together.
• 19:26
  Speaker 2: So my answer is, yes, it's a time for us to also looking at the regulatory side together, but at the same time, we don't want to, because of regulatory and requirements, slow down technology innovation too.
• 19:40
  Speaker 3: Yeah, yeah, I agree with that for sure.
• 19:42
  Speaker 3: Well, let's switch gears and talk about you a little bit, so tell us about your journey to your role there and how you became a co-founder and the CEO at DataVisor.
• 19:53
  Speaker 2: Well before DataVisor.
• 19:54
  Speaker 2: My background is research, so my mission is really to advance the state of art of technology and always looking at the new ideas and innovations to power the next 10 years.
• 20:08
  Speaker 2: So when we keep doing that like to some extent, datavisor, is my co-founder's mission to take that spirit but really to materialize that and to bring immediate impact to the industry.
• 20:21
  Speaker 2: We don't want to wait for 10 years for our technology to make its mark.
• 20:24
  Speaker 2: Whenever we have innovation, have ideas, we want to bring the impact to our everyday life immediately, faster.
• 20:32
  Speaker 2: So that's what I've been committed to work on and I see it very fruitful in DataVisor, where we're super passionate about this mission and journey.
• 20:43
  Speaker 2: So that kind of brings us to really start a company and for me to work as a CEO, co-founder, but at the same time starting from technology to make it a product and business.
• 20:55
  Speaker 2: Obviously, throughout the journey there's a lot of things I learned as well and I think for me personally, I would just say I don't really try to think about the right way to become a CEO, but really to think about how we can build upon DataVisor to fulfill our mission, to empower our customers and protect everyone of us.
• 21:19
  Speaker 3: Okay, was there a certain moment in time that you and your research and thinking about the challenges, that you turned to fraud?
• 21:28
  Speaker 3: Because obviously there are a million different ways you could take technology or AI.
• 21:33
  Speaker 3: So why did you guys pick fraud and the payment space as the technology you wanted to move forward with?
• 21:39
  Speaker 2: Yes, so I would say prior to DataVisor I've worked on security, many different kinds of security topics.
• 21:46
  Speaker 2: They range from malicious advertisement, intrusion detection and toward bot attacks and fraud being a big part of it.
• 21:57
  Speaker 2: And the way you kind of pick fraud is that we definitely see a lot of great ideas and innovations going on in general in the security area.
• 22:06
  Speaker 2: But coming kind of to fraud, I think that I would say not only has an impact in general, like to the company kind of level, to those customers that we immediately work with, but the fraud is something touches upon every one of us somewhat very directly, right when we receive a scam attack, when our account gets compromised, when every transaction is being made.
• 22:29
  Speaker 2: And therefore I feel working on that topic as immediate, kind of very closeness to us as consumers.
• 22:38
  Speaker 2: And at the same time I have seen the challenge of this industry like we talk about there are a lot of new innovations coming up.
• 22:46
  Speaker 2: Every time come with a new innovation.
• 22:48
  Speaker 2: For example, when we started having kind of, for example, the new real-time payment, we saw seeing we don't have good legacy solutions right, when we suddenly have kind of maybe the buy now, pay later, we need another new solution.
• 23:04
  Speaker 2: So constant seeing a lot of the challenge.
• 23:06
  Speaker 2: Therefore, the advisor's mission is, no matter what innovation we have, we can build some foundation and solid to protect all kinds of different use cases, for account lifecycle to be something a little bit more, I would say, fundamental across use cases rather than just focusing on isolated solution for specific use case.
• 23:28
  Speaker 2: I find that very much kind of exciting for feeling, because that has a way to change how the industry deal with these fraud approaches in the past.
• 23:39
  Speaker 2: And also, I think another exciting area is we talk about our commitment to what fighting fraud in a more proactive manner than reactive manner and has a promise to also change the whole industry kind of landscape and change the arms race, and that's something I feel very exciting too.
• 23:58
  Speaker 3: Okay, well, what are some things you're passionate about?
• 24:01
  Speaker 3: Maybe, if you can pick one work related to passion and one personal passion, that would be great.
• 24:06
  Speaker 2: For the work related we talk about that.
• 24:09
  Speaker 2: I've been always kind of a technology frontier and been working on innovation, and so I'm really passionate about not just inventing new ideas, come up with new ideas and so publishing, for example, the research papers and the best conferences, but I'm super passionate about bringing it to our real life impact and then making it something that immediately that protect us and to be more game changing.
• 24:38
  Speaker 2: But that's something definitely from a work perspective we have been keep pursuing and it's very fulfilling to me.
• 24:45
  Speaker 2: I think of off work, and so I'm also kind of very passionate about, I would say, in general, like my family, like my kids, spend time with them, and I also enjoy cooking, I enjoy reading and going out there a lot of things, fun things.
• 25:03
  Speaker 2: So I would say, having this fun time with the family and growing with the kids together, growing up with them together, having that full experience for me and my husband, that's something I'm very passionate about too.
• 25:18
  Speaker 3: Great Well, thanks for sharing that.
• 25:19
  Speaker 3: Well, we've covered a lot of ground so far about, obviously, the company and what differentiates you in the marketplace, about fraud in general, and then obviously a little about you and your background.
• 25:29
  Speaker 3: Is there anything else that you'd like to cover before we wrap up the show?
• 25:33
  Speaker 2: I would say we are in a time era.
• 25:35
  Speaker 2: You can see innovation is accelerating right, and they don't just stay on the paper or just fantasy ideas.
• 25:44
  Speaker 2: We see many of them come true and many of them impacting our lives.
• 25:48
  Speaker 2: So I want to encourage all of us to keep that kind of open mind and embracing us as this technology is transforming every area of our life, from biology right To going to mass and to fraud detection.
• 26:04
  Speaker 2: We talk about the ways we drive things like that.
• 26:07
  Speaker 2: So I think we are in an era seeing a lot of exciting things going on because of the innovations happening around us.
• 26:17
  Speaker 3: Okay, well, great.
• 26:18
  Speaker 3: So, inglian, thank you so much for being on the show today.
• 26:20
  Speaker 3: I know your time is very valuable, so I really appreciate you being here.
• 26:23
  Speaker 3: Thank you so much.
• 26:24
  Speaker 2: It's my great pleasure to be here and to all you listeners out there.
• 26:28
  Speaker 3: I thank you for your time as well, and until the next story, thank you for joining us this week on the Leaders in Payments podcast.
• 26:35
  Speaker 1: Make sure you visit our website at leadersinpaymentscom, where you can subscribe to the show and where you'll find our show notes.
• 26:42
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