[MUSIC] Okay, thanks. I think the first question is raelly the first thing you talked about, which is that the blockchain's inherently transparent. But you've talked about ensuring privacy. Maybe you can go into a little bit more detail on how that happens. >> Sure, so I think for the most part, when we're speaking about data services on the blockchain, there's always this trade-off between privacy and searchability. In that, for example, with medical records, I may want to I may want to entirely withhold my information from other people. But in some other way, the ability to search over a range of records while providing anonymity fulfills an important service to the aggregate. And I think it's distinction to be made between data services that identify individuals and using kind of individual data in an anonymized way on aggregate to still provide insights that typically wouldn't have access to. And at Registry, I'm not going to go too deep into this, but the idea is that we create a fundamental split between what we call user data and also identifiable data. So the idea is that we can split, in this case, a student database into a kind of section that is easily identifiable. You can pick the student out, and another side that's more generalized user data and we use the blockchain as a way to intermediate between these two data sets. And allows this more generalized data set to gain access to the more personal information depending on the specific user's privacy settings. >> Okay, so that's going to be a big challenge for universities and students to fully grasp and understand. Because a university's not going to feel comfortable publishing the student's results. Perhaps the student might not feel comfortable having their results searchable on a blockchain. So anonymizing that and being able to explain it and being able to have an example that would be very critical in order to, I imagine, successfully run [INAUDIBLE]. The next question is, I guess what I'm trying to convey, is the use of third-parties. It seems to me like you're missing maybe the step between a third-party that has access to data, like overall mark data and maybe a more holistic picture of the student. So there may be students that didn't perform as well. But you may want to hire them for other reasons, they have much better soft skills they need in other areas of university etc, etc. You don't hire someone just on their marks. So how do you going to make that? >> So this is something really interesting and a big question we were asking in building Registry was how valuable is the students mark? And NetBank ready illuminated the reality here. And they said that their number one proxy, the thing they look to to indicate a how well a student will perform is their grade. And I think that's why this platform is particularly useful for students. And the use case kind of dissipates as you move out of the university environment, where your work experience speaks more than just how you performed at universities. But what we found out is the first step of screening for all employers is grades. We take like a 65% cut off, we don't look at anybody else below that. We think there's an inherent problem in that because 65% in one course or one degree is totally different from another. So this idea of relative, so we will look at the top 25%, and that's it, will be very useful information. So I think we're cognizant of the limitations, but also realistic about the value that this information has. >> I think that also just adding on to what Ryan said, I think the important thing to emphasize here is that the decision remains with the student. Whether or not they're willing to open up their personalized information file, their personalized data to third parties in this case. And also kind of the existing university system kind of has this semester based and turn based uploading. So all the university administration and all that's ever recorded on university systems is this final aggregate mark. But lecturers on their personal thesis hold that Excel sheet that has information on test one, test two an oral presentation, group project. A lot of that information is lost when that's kind of aggregated. And it's simply because there's no good, user friendly way for lecturers to upload this at a frequent basis. So we try to incentivize lecturers to upload this more granular, what we call below the line data by in return giving them a platform that's kind of easy to use, easy to upload. They get all this additional functionality, and this serves as a strong incentive for them to upload this more granular data, which then gives a more realistic picture of the student. >> Just quickly to add on to more use cases perhaps this idea of third parties interacting with the system one example is bursary management. I know that the way the system works at the moment was students go and they fill out in an e-mail or spreadsheet and send this to the bursary, whoever's providing them with the bursary. And there has to be this manual checking of grades at the end of the semester. There's no way to make sure this is reliable information. With a system like Registry, this process can be automated. So the lecturer will put in the information, and the third party, the person providing the bursary, will automatically gain access to this. So I think there's a whole bunch of ways where this data is currently being used. Just the methods through which people are using it is so inherently inefficient and costly for the universities. >> Do you anticipate any challenges or any maybe resistance from lecturers who have to input the data? So for whatever reason, they may not want to publicize their test one and test two results. The idea sort of variations flat or they don't want to go through the effort of interacting with the system. >> Sure, so I think a nimble mechanism we have we have to address that is the idea that for every lecturer and for every course there's a course convener. And there's someone responsible for the implementation of course. And typically, course conveners are in a very tricky position in that they may be a convener of a degree or multiple departments. And as a result, it's very difficult for them to, at a point, speak to each individual lecturer to find out, hey, how's the student doing in this course? How's the student doing in that course? because performance can differ across subjects. So I think by giving functionality not just to lecturers, but for conveners to actually get a kind of holistic picture of their students' performance across all of the individual courses creates a strong incentive for conveners to actually prompt lectures and say, hey, we haven't uploaded your marks. What's going on, is there something we should speak about? So I think in the kind of uploading and the idea that we have different tiers of usage, so a lecturer, a course convener can view all the lecturers in his degree. A university administrator can view the course conveners, that kind of creates a natural enforcement. >> And then to just expand on two more incentives at work in our favor. The first is this idea of having an early warning system. At the moment, the yniversity has no idea what's happening with the students other than twice a year. Only at the time when the transcripts are created. Another example of this is this idea to create a system that students really get excited to use and want to use and want to understand. So use a couple of simple behavioral economics theories with them. So do you know you need to get 60% in your exam to pass? And then create a dashboard where you can visualize the students performance and set it as their default engagement mechanism. Then it becomes as pressure from the students onto the lecturers. Why aren't you uploading my marks, I can't see how I'm doing? In my other courses, I've got such a clear picture. So I think we're very much aware that the fact there will always be resistance to try or implement new technology. But to try and build in as many incentives as possible to sort of promote our success. >> Maybe sort of just one last comment which is that your business model relies on these third parties paying for the system, right? A lot of the system is actually benefiting the university. And I get the fact that it benefits the third party [INAUDIBLE] that is being taught well is going to be productive in their company. But do you feel that this is going to be able to sort of replace their current costs for hiring somoneone. because the current costs are a normal sort of HR and what rages raises costs for a company?. >> For th emost part, they’re charging really similar rates inside of that in terms of the cost of the first year cost the company as well. >> So, do you get that I’m saying that this new places and aspect of it but not the whole process? >> True, I mean for the most part, I think human resources agencies can kind of plug into this as well. I think the big advantage here is that we're offering for the first time this idea of the universe of all graduates. And for the most part, human resources departments and recruiting agencies are always bias in terms of the kind of sample that they bring to the employees. They may have certain relationships to specific degree programs, but I don't think employers necessarily, always aware or always able to kind of search this for graduate marketplace. And you know, for the most part, employers will kind of look at this and go it's far too much information. But the idea that we can make search functionality, that kind of granular that employers can really find candidates that they're looking for in a way they that maybe can't do with existing recruitment methods. >> So the way I like to think about it is the graduate or each graduate is an assett to us for one year. Once that student graduates and gets a job their value to us dies. So we got an asset that we can use for pretty much one year as much as possible. And how do you use a graduate? The idea is to get that graduate and how they perform to as many people as possible. So if Nedbank for example, wants to find out who are the top performers at the university, and we can get into how the mechanism works that it remains anonymous. But they are able to find out or contact these graduates. What about Standard Bank? What about what? What about all these other banks, they all now are dealing with inferior data to ordinary bankers. So now they're incentivized just as Nedbank was, okay, well, I also want the best data and so they pay for it. And the next person pays, and the next person pays. And once they graduate leaves, we can't sell that graduate again. They get passed on and again, we inherit a new asset and we able to sort of extract some value from it. >> Just just bear in mind that that's increasing the cost to Nedbank, obviously decreasing because the effects can have to interface with them. So HR personal data to pop in and as well as paid this I'm not saying that it's not going to work. I'm just saying that that's obviously very closer to the innate benefit. Or that for them they see immediately the significance and cost maybe they'll see a decrease of time because these characters have been suited. To back to the company, but that's, that's what you need to be able to sell to them. That's not necessarily the easiest sell. So we need to maybe go into the whole, go into market strategy. And also, the team that's going to drive has many experience in the HR industry and has experience in running graduate programs that can really sell that this is beneficial to a company. >> So on that point there, I'd just like to take a minute to explain the engagement we've had so far. One of the stakeholders that we engaged, they had 1,000 applicants. From those 1,000 applicants, they'll only interview 80. Which means they have to screen that massive volume of students using just the information on their transcripts and on their applications online. This is an extremely tedious and manual task at the moment. For example, the one thing students do often is over overstate their marks. We were really shocked to find other students actually do this and then want to get employed but this is what happens all over the place. So with Registry, there's no more manipulation of marks, which means that someone else has to go and take a transcript add up all the grades and see if they really are who they say they are. It's an enormous amount of work that we're able to reduce off the system. Another thing that's been very frustrating for employers has been this idea that their degrees in their system are not up to date that match with the university system. So what happens when you can't find a degree, you just select anything. Well, it sounds close to be common all I'm kind of doing data science. That sounds right but this is not the degree they've done. But they're screening candidates according to these degrees. So this gives them just the best day to go from 1,000 to 80 with with like a lot less pain points. But I think it's a very good point that it's not going to be just automatic by at least our research and engaging with these employers there has been strong interest. >> Thank you, thank you. >> Cool. >> Thank you very much. >> Thank you. >> Thank you so much. [MUSIC]
