DAPPCON 2018: A Look Into the Fascinating World of On-Chain Data - Jai Prasad (Token Analyst)

Transcript

I'm Jay I'm the founder of token analyst and I spend a lot of time looking at addresses on the blockchain we're obsessed with it we look at you know all of you have an address and you interact with the blockchain so you transact you buy crypto kitties you participate in prediction markets you so these are all different activities or features that you do on the blockchain and we want to analyze this so we decide so we're a team of you know engineers and machine learning scientists and data scientists and so what we do is we take every address at scale and look at features of a given address so what I mean by this is that we come up with these clusters

on the blockchain that each have specific characteristics so these a cluster might you know have a bunch of send transactions or it might have a certain kind of tokens that they hold or they might interact with other addresses so essentially we use what's called an unsupervised clustering algorithm and we create these blockchain clusters of addresses the labels that you see on the top the mining pool exchange centralized exchange those actually don't exist right the blockchain pseudonymous so that kind of requires some sort of detective work we go you know scrape the web go to ether scan people contribute and so we're we're able to label these

addresses kind of the goal of all of this stuff is you know not to say that hey this address is you or this address is you it's on in general it's to make the blockchain more transparent and accessible for everyone so our end goal is to take the raw blockchain data and come up with kind of clean classified you know digestible transactions so if you look at a transaction you know that okay it was sent by like a trusted good party to you know an exchange or vice versa and this is what we've been you know working on for the last year or so we take every address on a period we run it through our ml algorithms and you

know we see patterns and behaviors and what comes from it and so you know why is this interesting there's many use cases for knowing contextual information about an address so some use cases could be like DAP developers want to learn more about their users they wanted to know where users coming from what other dabs that use are used just characteristics about that about that address without actually knowing its real identity or you know MLK YC is becoming big I was to work in fin tech so I'm very familiar with security token so what's gonna happen as the SEC is gonna say that you can only

interact with another address but if you know that it's a trusted counterparty so these are all reasons why it's important to get some sort of contextual data and information about addresses but our business today it remain lis focused on institutional investors so these are your crypto hedge funds your whale traders family offices so I just wanted to kind of give you a look into their minds and like why they're interested in blockchain data kind of metrics they look for and then go over a little demo that we built and so some of the questions that come up this the chart on the right is nineteen of the you know most popular tokens and this is kind of

the ownership of the tokens so you know genoa gnosis it's good like I think the gnosis team owns 85% of the token but we all know this because we're in the dev community but someone who's on the outside like an investor if someone asked us this wait why should I invest in this project it's actually super centralized versus you know some of the other ones so like explaining to them that this is actually the team there's like a vesting schedule they'll deliver the tokens in a certain way is important that's kind of one of the you know use cases of our data some other questions that come up are they want to know like how everyone's looking for like fundamental you know valuation metrics for crypto assets so they want to know

I'm sure you might have read about like the MV equals PQ no the network transaction ratio or whatever is coming out so these are things that we are trying to track and build for for these investors to better understand these assets why knowing about addresses is important is because we want to discount like internal transactions that occur within exchanges so we're trying to just look at you know true utility use cases or true users using an asset for its intended purpose and just some other questions that we've had over the last you know yours from investors there been how does how does

the volume flowing is it coming from OTC Dex centralized exchanges Dex is what percent of tokens are held in you know cold storage when will they be released where the funds coming from what's the geography what are some of the transaction patterns this is something that's out there like would have like a whale syndicate created a bunch of different addresses and took part in an ICO and now they control you know 50% of the tokens they could actually impact future governance of that project so these are like questions that people ask us and try to get us to figure out and so to kind of help this is just I'm gonna go through a like a quick demo that we build so this is kind of a subset of me say go token transfers

and we start with the the circles are addresses and and the the lines are like transactions between addresses so this is like a map that we built from from the ICO till today of different things that happened you know in the oh me say eco ecosystem this is very raw but like the next level is to draw insights from this sort of graph the different colors are different clusters based on the machine learning stuff I was alluding to earlier so for example here you know this is like an early eye

CEO investor these are potentially other investors that this person's interacted with this label early ICU investors something that we just arbitrarily put on on the thing like there's no you know right or wrong way to do it but that's definitely an issue but with this sort of analysis you can look at transactions so for example we were able to look at like a bit Rex I think this is a bit Rex wallet I don't have it up here sorry yeah so this was like an OTC desk that was transferring a bunch of tokens so it's kind of the goal of this whole thing is to just build more transparency into the space we're not trying to say

like this is you this is you just on a holistic level we want to know that the right type of people are participating in the space it's not being used for you know drugs or money laundering and it's also cool for Tocantins themselves to kind of take a deeper look into where their users are coming from learn patterns about them and it also so we talked to you know like institutional investors Berkeley is Morgan Stanley these type of people want to get comfortable if you want this institutional money to come into the space they need to be comfortable they need to they have these risk scores and whatnot and they need to know that what they're investing in is you know actually a decentralized asset that does what it says it does and kind of our

goal with token analysts just to just bring polite some of these nuances of the token market and took an ecosystem and yeah I guess closing remarks you know we have an API you can like query our addresses so you can just put in an address and we'll we our ml models will classify it as like a human bought or exchange we'll give you some features about the address like how often a transacted with what other addresses are transacted with et cetera so please check it out just give us some feedback and uh thank you [Applause]