Canton Buildcast with Fiùtur

Captions as YouTube publishes them, usually machine-generated, so names such as Daml and Canton can be misheard.

1. 0:01

   As markets move onchain, Tradfire and crypto markets are converging on Canel, the world's biggest institutions, highest quality assets, and onchain innovators already here, the first public blockchain network with privacy. Every 2 weeks, we'll showcase the applications and use cases shaping the future of finance. The ecosystem is growing, new markets are forming, and this is just the beginning. Welcome to the Canton Buildcast, where new connections create new possibilities.

2. 0:28

   This week we delve into how futures live platform on Canton is being used by major lenders and producers to bring together trusted onchain data and the connectivity and distribution power of Canton to drive sustainable lending and investment across the energy economy. Let's see future in action.

3. 0:46

   Let's go. Hi folks and thanks for joining us once again for another Canton Buildcast where every two weeks we show you the latest innovations in onchain finance and the onchain economy. I'm pumped about today's session because we're with the team from Future and they're going to be telling us all about how they're laser focused on leveraging blockchain to to really do well by doing good.

4. 1:08

   They've been delivering the trusted onchain data to support the the energy transition economy. And we're going to look at how the team is solving really hard data problems and delivering the connective tissue to power more sustainable lending and investment across the whole energy economy. So Corin, Dave, great to see you again. How are you both doing? Yes, great to be here. Thank you, Ben. Yeah, hi Ben. Good to see you again. Thanks. Thanks for joining us, guys. So, Korean, let's

5. 1:33

   start with you. Your professional path has very much been trodden through banking and sustainable finance really at big institutions and small and and what attracted you to future? Tell us what you guys are doing that that really meant you were solving the big problems uh that you were seeing in your career and that you're really addressing with DRT now. Yes, thank you, Ben. So I joined future two years ago. As you said, I have a banking and asset

6. 1:58

   management background. I've always been at the client-f facing um stage of defining solutions, especially risk management solutions for clients. And I came to future 2 years ago when I came to the realization that traditional finance, traditional data and traditional technology were not going to be sufficient to help support the um the raising of funding for the transition economy. So before we go into the details as to what is the big problem we're resolving and how we're resolving

7. 2:31

   it, I just wanted to define some terms for the audience because when people talk about the energy transition actually we take a broad definition of this and we talk about the transformation of the economic system worldwide and that includes concepts of energy efficiency. It includes concept of uh circularity adaptation of economic processes adapt climate adaptation for nature all of which could be resulting in greenhouse gas reduction. So it's a number of concepts that were capturing under the umbrella of economy

8. 3:06

   transformation and that is requiring a lot of money. So, according to the Bloomberg um new energy finance um numbers that were published last year, we've already as as planet earth have already raised a couple of trillion dollars of money to finance that economic transformation. And that might seem to be very large, but in reality, it's a drop because we need hundreds of trillions of dollars to finance the economic trans transformation.

9. 3:36

   And if you're an investor and you're thinking, I would like to invest into the future economy and I I know it's it's going to be more sustainable. I'm all for it. Um what are the friction points that is preventing all of that capital for flowing into economic transformation? So basically there are two points of frictions and everybody knows about it. It's finding solutions to it that is difficult. The loan market association actually published um at the beginning of the year a number of

10. 4:07

    reference points that are really helpful to understand the friction point. In March of this year, they published a survey of their members. So being the loan market association, their members are banks and asset managers and they asked what is preventing you from deploying capital faster or more capital. And the number one constraint that 50% of all respondent pointed to is the difficulty to prove the impact of the assets that they are financing. They

11. 4:38

    they talked about the the difficulty to justify the claims that they're making and they would be very hesitant to make claims they cannot justify because then you get caught into all kinds of regulations that uh would punish you if you if you have claims unjustified. So that's friction point number one that we resolve. We help um to justify claims that are made by the financial industry

12. 5:02

    on the impact of the assets that they're financing. So that's friction point number one. Friction point number two is um much more practical. It has to do with the way the financial system is operating today. And and that's fundamentally um it was best reflected I think in in a working group that the LMA published. It is this month actually on the syndicated market trading settlement time. So they have a working group dedicated to that.

13. 5:30

    They published that on average today the settlement time for syndicated debt trading is 42 days. Right? And so this tells you something because syndicated loans are the prime instrument used to finance the economy transition because of the size of the loans involved. And if if the trading of those loans take 42 days to settle, then you know it's illquid. And if it's illquid, it's going to by nature repel a number of participants in the industry. And 42 days tells you there's a lot of risk.

14. 6:03

    There's a lot of inefficiency and um there's a lot of cost associated to this. So friction point number two is how can we justify claims, substantiate the claims I think is the wording they're using in the LMA. How can you substantiate claims but do it on a platform that allows you to have settlement times that is faster, reduce cost, reduce risk and that's fundamentally the two friction points

15. 6:27

    that future resolves for. Yeah, it's the it really the end toend efficiency gains that you'll get through new technologies. It you know it's transforming these kind of legacy processes that have been around a long a long time right in lending. Um recent reports have really shown you know the rise and rise of private credit you know especially across the industries you talked about you know manufacturing, industrials, oil and gas. Um really the industries that are most responsible for

16. 6:51

    greenhouse gas emissions right. So is there an opportunity do you think for for lenders and corporates given that perhaps private credit is know less riddled with this legacy technology issue and infrastructure you know is that really the the kind of the big opportunity and what are the benefits you're seeing from people that are using the platform today. Yeah so for from a corporate corporate point of view the borrowers there are huge opportunities

17. 7:16

    associated to being able to resolve those friction points. Um, if you think about it, I would describe it as a as being able to capture a new value paradigm that is driven by transparency on new value being created through the economic transformation. So there are you can think of it as four quadrants and it can be in any order depending on who you are and what you prioritize. But this new value paradigm that you ex it basically means you

18. 7:46

    extract more value out of the proven verified sustainability attribute that you are realizing through the economic transformation process. So the I would say the paradigm value proposition number one is that in many countries around the world um there has been an introduction of carbon tax and and emission trading system. 53 countries around the world have those. These countries put a price

19. 8:13

    on some of those attributes like greenhouse gas. And when you have a price on greenhouse gas and you can verify emissions of greenhouse gas, then you can put a price on the value that you create through the sustainability process, through the transition process.

20. 8:29

    And putting a price on it means you can then optimize it, you can mitigate it, you can monetize it. And that's value that if you didn't know, you wouldn't have been able to capture that financial value. So the there's emergence of this appearing very quickly in countries that have implemented those mechanisms. So that's block number one of value. Block number two of value is that if you can

21. 8:54

    justify the claims, as we said, it attracts more investors. And so make attracting more investors makes your debt more appealing, makes it more liquid, and so by nature is going to help decrease your cost of debt. So that's value proposition number two.

22. 9:06

    Value proposition number three has to do with the technology that we use. We standardize the process because through smart contract what you do is that you have a systematic way of capturing attributes, the controls, the verification, the protocols and so on.

23. 9:23

    And that standardization creates liquidity because people know what they're buying and as opposed to something that is always adoc. So value proposition number three through standardization you increase liquidity. And then the value proposition number four is that since we are digitizing the um the the verification of the claims then we can create um what we call smart ids which are referencible attributes that can then be attached to any

24. 9:50

    financial instrument issued digitally on the Canton network. And that issue that native issuance on the Canton network reduces settlement time definitively reduces from 42 days and also decreases the cost because it has a lot less operational cost associated with it. So the combination of those four value blocks creates a new value paradigm because we have resolved those fiction points. I like that you talked about the circular economy and these four things kind of create that virtuous cycle. I

25. 10:22

    really like it. Um a really compelling argument Corin I think Dave you know we've had this you know really clear story clear business case it is sometimes I think difficult to to to understand you know um how this all works for a user how do you because it's it's a multi-sided problem right you're bringing all this stuff together into one platform we are here to see it in action can we can we get a demo from you tell us about what we're going to

26. 10:45

    see yeah absolutely absolutely before we go into the demo I mean I think it's worth um uh recognizing that this is um you know probably a new solution to the finance industry but it's not a new problem to us at future we started working on this in uh uh 2022 uh when we started our journey with DA and DAML and we built um I think probably the first uh differentiated asset registry uh on

27. 11:14

    DAML and we really lent a lot of thought about well if you're going to put data on ledger on a distributed ledger how do you make sure that the quality uh and the accuracy of the data is correct from the ground truth upwards. So we really kind of solved a lot of these problems you know back in 2022 2023 and went live uh with uh in the natural gas space and you know currently have you know greater than than uh 500 BCF of natural gas kind of registered on our platform. So this

28. 11:46

    notion of provenence, this notion of um putting data through uh a workflow that ensures this accuracy that is provable, auditable and traceable is something we've been working on for a long time. When we started future, we realized that the application of that accuracy of the data had a lot of impact in the finance world. And if we can then roll that data up into um you know these things that we

29. 12:13

    call outcomes which are these key data points these key targets those targets can then get rolled into financial instruments such as transition loans and green bonds and really kind of affect the the the economy from the from the finance going in. And this is the work that we've been doing um really with um really it's been Canton that's been able to uh enable this kind of network of

30. 12:39

    networks we call it that can really bring the finance uh world into the uh into the environmental and sustainable world. So I'd love to show you a demo um of the prototype we've put together. Let's do it. Okay. Excellent. So what what we're looking at here is a proof of concept that we uh actually co- uh wrote with um digital assets and uh what we wanted to illustrate was how a uh

31. 13:06

    completely tokenized canton flow of a transition loan through to these KPIs that we call outcomes and then all the way down to the ground truth the actual data that came from the production facility or the sensors or whatever. is is supplying the raw data. Um and so what we're looking at here is um essentially the bank node. So I am a you know a major international bank and I am uh loaning against transition loans.

32. 13:36

    Transition loans are uh loans that are ratcheted based on uh performance of those KPIs that come from our system. So in this particular example, we're going to see a loan that uh assesses itself monthly. And if um the the uh production data, the methane intensity in this case uh betters the OGCI benchmark, then the interest rate uh each month um gets ratcheted down and for every month they don't beat the uh OGCI benchmark, it stays at their base interest rate.

33. 14:11

    So very uh simple. It's it's a bank with one loan here. Um so the important thing to to consider when we're viewing this demo is that we're seeing two um canton nodes uh talk to each other via the synchronizer. So as I navigate around uh the PC, we're not seeing any API interaction. There's no concept of um a service user and tokens and logging on and using APIs. This is purely Canton and the synchronizer uh interacting. So

34. 14:43

    if I drill down into this specific loan, um what we've done in the PC to make it easy to understand is we we've kind of uh grouped the data together. Um so in the first section here on this loan details, this is kind of the bank side of the house where the loan has a title and it has a description and it has an asset ID. This is the thing that the the bank is financing and you can see technical terms such as the the party

35. 15:07

    ids and the ledger ids on the on the distributed ledger. The interesting thing to notice this base interest rate and the interest rate ratchet and this interest rate formula which basically says if we do better than that benchmark then the interest rate will go down by 1.25% each time we assess. The next section is this the section that's really uh interacting with futures node

36. 15:32

    and um this is very important because the terms and concepts that are on the future node uh need to match the terms and concepts that are on the bank side of the house. So if the bank uh is financing an asset and on the future side we call that a project those two need to be in alignment. And this is what Karen was talking about earlier with this notion of smart ids. These are referenceable ids that span uh nodes in

37. 16:03

    the canton network and provide this governance that in fact the loan is uh referring to the same project the same asset. uh this concept of an outcome definition smart ID this is the governance object that governs the KPI so that the KPI is consistent uh and has a defined methodology because remember the term of this loan could span over 10 years 15 years 20 years so we can't change our concept of what average means or what benchmarks mean um and then um

38. 16:37

    on on our side technically we have a thing called a generator which creates these outcome APIs uh outcomes sorry and these outcomes have data and this is the target that the loan is looking for. So on this particular loan uh we have uh assessed three months worth of interest rates and you can see it in this table down here and just quickly in the table you can see that in the first two months we

39. 17:03

    betted the benchmark and the period interest rate went down and on the third month the producer uh did not meet the benchmark standards and so they got assessed at their uh usual interest rate. So let's drill down uh into that. So here is the smart ID again. This is the outcome smart ID.

40. 17:24

    This is the uh smart contract on the future node that is holding the KPI. And the bank is uh fully enabled through the fine grain privacy controls that Canton offers us to go look at that specific contract. So let's go down. And so now the bank has a view of well if I assessed this month to meet the benchmark why and now this is the first level of data that the the bank is able

41. 17:57

    to see and we can see uh data around here of um that backs up the the initial KPI. So we can see what the measured quantity was and what the deviation was. Really what the loan is really looking for is this absolute difference. And we can see it against a couple um of uh different benchmarks, but it's the 2025 that this loan is being assessed against. But the real importance here is

42. 18:23

    this block down the bottom, which is the verified data source. So the KPI is an aggregate is a roll up of a number of different production events. Those production events on our side are called DCUs, which are digital commodity units.

43. 18:38

    And uh we can see that we've had four uh digital commodity units that went into this aggregation and each one has a smart ID. This is the reference. This is the onchain uh ledger reference to objects on our side. And so when I flip over to the future uh UX and drill down into into the futures side of this story, um I can see all of these DCUs that came in. And for each DCU there is a whole number of

44. 19:11

    attributes. And uh this provides the provenence the ground truth of uh assessed data at the point of production that made its way through our system through smart contracts on ledger immutable got rolled up all the way through to the outcomes that you see on the bank side all tokenized uh all on ledger. And so this provides really this complete transparency, complete immutability uh and reliance for the

45. 19:42

    banks um to really um move their business into the transition economy. So we've really seen how you can you know model the entire um you know loan there with that embedded you know set of rules automating the data to really drive that kind of um automated outcomes I guess and that that that that transparency and immutability across the ledger for the customers for the bank and for the and I guess for reporting and all those other things as well right Dave it kind of has

46. 20:12

    downstream effects as well is that correct? Yeah, I mean you know to me can C can C can C can C can C can C can C can C can C can C canon is critical to how we do our business and to the success um really of the of of this initiative. Firstly, from a business perspective, I mean, it is the the DT that has the most number of bank participants. Um, and is really set up for a highly regulated market. Um, and um, and it sets the stage for complete tokenization, right, which I think we

47. 20:41

    all agree has to happen for liquidity, for accuracy, for transparency, for provenence. But as a technologist, you know, Canton is critical to me because um I can interact with uh various participants on our networks, right? Whether they be data providers, satellite data providers, producers, uh finance, insurance, you know, all kinds of sectors. Um I we can interoperate with them with uh you know, minimal development time. Uh we are uh you know, now not constrained by API contracts.

48. 21:16

    We're not constrained by the traditional ways that computers talk to each other. So that means innovation goes faster, but more importantly, it it it it goes more accurately and we get a more reliable product. Yeah, I I think it's fantastic. You obviously thought very um clearly from the beginning about the smart contract level, the data model, and then really thinking about that, you

49. 21:37

    know, the whole point of blockchain, which is distribution and and having that connectivity across an ecosystem. So um yeah really really good to see you go on that journey and and start you know start where it makes sense to begin and then evolve over over time and maybe you know Karen could you um talk a little bit more about you know what what's possible in that kind of broader canton network ecosystem now you talked

50. 21:58

    about settlement other financing workflows I guess this is kind of how you start to think now once you have the data model really strong like what else you can do in in a network like canon today yes so we can imagine a world where um you've priced and you can trade and uh and you can trade with the investors and you can trade between banks those sustainability attribute and we starting to see this because in a regulated market I was mentioning carbon

51. 22:26

    market right you already have registries that are forcing you to register verified attributes and that put a price on it. So if you interconnect the regulated component to a more voluntary component of trading those um attributes between banks between investors the creation of liquidity the transparency that the system provides allows an investor to say well I was all for um investing into um reduction of water usage but really now I have too much

52. 22:57

    reduction of water usage. like to have more reduction of greenhouse gas as well and you can then trade the attributes that you have in your portfolio against other attributes because you want to balance the environmental profile that you're aiming at. For instance, this type of technology allows you to do this and that's something that is not possible today unless you actually um do this in a very complex and and expensive

53. 23:22

    way. So it creates a lot of possibility for participants to then assess value and trade it um and create liquidity in that market and that's really what we're aiming at. Oh Dave, are you looking at other assets other things now that are available in the broader network? You know, as you kind of look beyond just your wars and your your initial ecosystem, what we talk a lot about onchain convergence between kind of traditional markets, crypto markets, what what are you seeing in that respect

54. 23:48

    in terms of the innovation that you could bring to to future? Yeah, I I um I think that's the next big uh challenge for us is um to enable interoperability between different um uh uh different blockchain technologies, right? And traditionally it's been it's been a pretty clunky affair with um strange bridging solutions and things like that.

55. 24:13

    And I think what Canton can do is kind of simplify that model out. Um you know and and I think that enables uh all kinds of interaction between you know uh stable coins for example. Um but just generally the the the interoperability of these smart contracts and the and the thing that DAML um provides is is this kind of uh smart contracting uh at the application level logic which is where

56. 24:43

    we all live and you know we don't really live down at that transport layer of the you know the cryptography of of the blocks right we live up in the in the application world and so that in interoperability and being to bridge between different uh networks uh I think is is critical and I and I think it's the next big challenge and I'm looking forward to to solving that.

57. 25:06

    Well, we're we're really pleased you're solving those challenges with uh with with Canton and with the the software stack from digital asset and great great journey that we've been on together. I'm really looking forward to see this grow and grow. Um obviously we have customers now using the platform and and sharing data. So um there's only only one way from here. um where can people start to interact with future and start to connect to the network uh what's what's

58. 25:30

    the path for for getting started both you know just just literally getting onto the network but just contacting you guys what's the best way to get in touch so the best place to find information on us to start with is our website um futurex.com you can contact us um through the generic email address sales@ futurex.com Um we are on LinkedIn so you will find us on LinkedIn under the future logo. Um we are also individually on LinkedIn um conveying um thought leadership and so

59. 26:05

    we um are expecting lots of feedback. We would love to interact with your audience and uh we hope to innovate with them very soon. I I've learned a lot from your thought leadership on on LinkedIn Karin. So I I follow that avidly. Um you always have really good insights into what's going on. So you keep keep that coming and keep keep developing Dave. Keep bringing the innovation that you and the team bring.

60. 26:26

    Um we'd love to have you back again another time. Thank you for a demo. It's always always a challenge giving such a complicated demo and making it kind of seem simple and understand the value prop. So I think really really appreciate you taking the time with us today. Thank you Ben. Thanks man. That was great. Thanks.

61. 26:42

    That's a wrap for this episode of the Canton Buildcast. Want to dive deeper? Check out the links below to learn more. Connect to app or bring your assets and use cases to Canon. And don't forget to hit subscribe to stay on top of the latest apps and opportunities shaping institutional grade onchain finance. Bye for now.