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About enrique11

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  1. Oh sh*t! You're right...I'm a bronze member, and I don't even know what that means (1000 likes seems obvious)..lol...looks cool though. Yeah, I think as XRP investors, we'll be very, very happy in the coming years. So much news is coming in now about XRP/Ripple,and it seems to be finally getting the attention it deserves.
  2. Yeah, but Venezuela likely didn't go through a formal process like we would have here in the states. That government's corrupt. It would take much longer in countries in which there is a system with a gamut of conflicting interests among representatives trying to come to consensus on CBDCs and the extent of their use, and all other such details, and give legislative approval to that.
  3. Central Banks will most likely experiment with CBDCs for cross-border payments, although, IMO they are much better suited for domestic inter-agency payments at the federal level. This buys Ripple, its products, and XRP network more time to get itself established and potentially get a larger market share - that's how I see it.
  4. The good thing is that the central banks will likely need legislative approval to "print" (issue) digital currency, so add a few years for CBDC issuing..this buys XRP more time to establish itself as a viable, superior alternative to Swift among banks and other FIs. We got a really nice head start.
  5. Well, if Brad thinks it's going to reach critical mass at 200, let's suppose 90% of those are banks..I don't know the actual number...but anyway, assume we reach critical mass at 180 banks, then all competitors of Swift can cumulative only get 7,200 of Swift's banks to share among themselves assuming symmetry of behavior...then we capp out at 97.5% of those, or a maximum of 7,020 banks. So Swift retains about 36% of it's 11,000 bank market share in the long run and its competitors get the remaining 64% in the long run to fight among each other for market share, of which Ripple likely gets the largest share having been the earliest to the game and all other things being considered equal. This is just a hypothetical example..doesn't mean it will necessarily turn out that way...also...I don't know the actual market size of banks that participate in the activity that Swift is targeting....I was using 11,000 which is Swifts market size, not the total market size, which I don't know. Oops...I think remittance companies use Swift as well...I thought Swift was strictly for banks.
  6. Well, that makes sense...a bunch of banks got together to create this organization and it seems like they didn't have a competing group of banks or outsiders like Ripple lol doing the same thing at that time, so it wound up a monopoly it sounds.
  7. Incredible if that's true to know that after 2 to 3 years after inception 45 years ago, Swift went on to monopolize the cross-border payment industry. I wonder if they had any competition. Maybe that's why they got away with it.
  8. Now that I've got a better understand by using this "S" curve I would put exponential adoption rate tipping point at the point at which Ripple transitions from "innovation" phase to "early adoption" phase. My estimate is in the vicinity of 2.5% of banks onboarding, or 275 bank contracts. Just keep in mind this estimate is based on penetrating Swifts banking market, and because I'm using the "S" diagram and you have this basic symmetry, then the diagram's peak market penetration appears to be capped at 97.5% or that remaining 2.5% part of the diagram is missing. Anyway, the point I'm making is that if we penetrate a lower percentage of Swift's market, say 30% tops, how would this affect the values I picked (e.g., 2.5% tipping point for 97.5% market penetration), so I don't know how a much smaller value for the upper limit on Swift's market penetration would effect all these values I'm throwing around. Would these values contract proportionately, stay the same, or something else, etc.? That also begs the question that if we get increased exponential growth rate for adoption around 275 banking contracts, does that give us decent odds of 97.5% penetration of Swift's market at most in the very long term? No, unlikely, because of competitors, but what if it was only just Ripple and Swift?
  9. Well, look at the "S" curve in my previous post. Assuming that all Ripple production contracts are with banks, and Swift connects 11,000 banks globally, then 200 represents a very liberal value of 1.8% of the number of Swift's customers. This value represent 72% of 2.5% putting us almost three-quarters of the way through the "innovation phase" of the "S" curve. According to that "S" curve diagram in my previous post, we haven't even gotten out of the "innovator" phase using this very liberal estimate of 1.8% yet. So, we're still at the beginning, but close to phase of significant exponential growth ("early adopter" phase) once we go past 200 banks and enter the "early adopter" phase. I looked up "critical mass" and the term relates both to the "S" curve and a business. in the former, it's basically the point at which network effects just begin to grow exponentially and a business becomes self-sustaining. This definition can be used in various contexts : https://a16z.com/2016/03/07/network-effects_critical-mass/
  10. I have no idea..I don't know why Brad chose that specific number...my guess is it's a target/goal that Ripple set up for itself to hit. They did talk before about not announcing weekly FI signups numbers and instead opted to announce when they hit the 200 mark. Here's an interesting article on network effects: https://www.nfx.com/post/network-effects-manual Anyway, with the next data point (3rd one) we can see which of the 3 models best fits the bank-rate adoption data. Of course, it will turn out to be the the model that curves like a smile (concave up) because in the earlier days, Ripple was doing 1 or 2 banks per week on average, now it's up to 3 or 4 per week on average during the last 3 months, but I would like to actually try to get a somewhat accurate model for bank rate adoption as well as Xrapid adoption..that would be cool. The model will be an "S" curve, my guess, concave up during the adoption phase with rapid adoption as the inflection point approaches, then after passing this point adoption begins to slow down as Ripple is in the beginning phase of having maxed out their adoption rate, then concave down and flattening out horizontally as Ripple approaches their ceiling of FI adoption. We're talking years and years. Also, a cool thing if Ripple's adoption follows this simple model and we have enough data points to find the point of inflection, (the point in the center of the 'S' curve) then because of the symmetry we will be able to figure out a decent value for the ceililng for FI adoption and thus calculate roughly what market share percentage of Swift Ripple can expect to take at most in the long run. Should look roughly like this image below:
  11. I did not expect to see so many seemingly non-native to the West C-level executive at Western Union. I guess that's to be expected with the global presence they have. You mean to use Ripple's products? I think SBI will be our savior at least initially. Western Union is like Swift...they think they don't need Ripple because they are so big..and they are too set in their ways with a lot of overhead and legacy optimization...they will only use Ripple as a last resort, IMO.
  12. Western Union is too big to adapt to this new tech. We need the smaller FIs to leverage this tech to either get Western Union to take a big risk and onboard or remain with their legacy solution and bleed out their market share to smaller more adaptable competitors over the coming years.
  13. In the calculation I did over the last three months it averages to 3.6 banks per week (50 banks and FIs in the last 3 months). I agree that the growth should be non-linearly increasing, so we can expect some kind of "critical mass" by no later than early March of 2019 (the last 50+ FIs to reach 200+), assuming a conservative constant rate of adoption of 3.6 FIs per week. I expect Brad or Ripple to come out and announce that "greater than 200 production contracts" milestone before then. Once we get that third announcement, we can create non-linear models to help us better predict bank rate adoption....the more data points, the better.