Blockchain-Based Re-Usable KYC ‘Particularly Valuable in Web3’ — Cheqd CEO Fraser Edward

0 14

Blockchain-Based Re-Usable KYC 'Particularly Valuable in Web3' — Cheqd CEO Fraser Edward

knife

According to Fraser Edward, the CEO and co-founder of the public permissionless network, Cheqd, one of the main hurdles faced when attempting to move data stored on Web2 servers to Web3 is “establishing a clear and scalable revenue model.” Edward however suggested overcoming this hurdle will unlock new use cases which facilitate economic activities within the Web3 ecosystem will be unlocked.

The Trusted Data Market

The Cheqd co-founder also told Bitcoin.com News that in today’s data-driven world, greater emphasis is now being placed on obtaining accurate and verified data. This shift in value from what Edward labeled generic data to trusted data is evidenced by users’ demand for data that is portable and cryptographically verifiable. According to Edward, it is this demand for assured data that has given rise to what is now known as the “trusted data market.”

Meanwhile, in the rest of his responses to questions from Bitcoin.com News, the Cheqd CEO touched on the so-called “bot paranoia” and how a decentralized reputation system can be used to combat bots and impersonators. The CEO also offered his thoughts on blockchain-based re-usable KYCs as well as how these can be used in the real world.

Below are Edward’s answers to questions sent to him via Telegram.

Bitcoin.com News (BCN): What is a Trusted Data Market and what problem does it solve for businesses and individuals?

Fraser Edward (FE): In today’s data-driven world, trust and assurance in data are critical, especially considering the increasing volume of data, the emergence of advanced language models like ChatGPT, and the rising volume of fraud. This shift in value from generic data to “trusted data” is characterized by data which is portable, cryptographically verifiable, assured provenance and traceability. Since trusted data has value, recipients will pay the issuers of the data for that value, incentivising them to provide more trusted data wherever possible.

Let’s consider the example of a Web3 lender looking to attract new users from Web2, and retain existing users in Web3 by lowering collateral ratios on crypto loans: Suppose a borrower approaches a lender, either in the cefi or defi space, seeking a loan. Traditionally, lenders require significant over-collateralization (>140-200%) due to the unknown risk associated with an individual borrower.

In a new scenario, lenders and protocols can offer appropriately collateralized loans if the borrower provides signals that support a perceived reduction of risk. These ‘signals’ are trusted data which may include on-chain transaction history, social signals and proofs like DAO contribution history, ownership of real-world assets, and even the borrower’s Web2 credit score and KYC data. The lender utilizes these signals to assess the risk of the loan. The more signals the borrower provides, the lower the perceived risk.

This enables lenders to offer competitive loan terms while maintaining their risk profile. Moreover, it enhances the efficiency of capital markets, stimulates growth through new money creation, and establishes cryptocurrencies as a viable alternative to fiat currencies. As the loan is repaid, the lender can provide prompt payment credentials to the borrower, which the borrower can share with other lenders to demonstrate good behaviour. The new lender then compensates the old lender and the borrower for these credentials.

Cheqd supports this data market by ensuring the lender (the verifier of the trusted data) can utilise Cheqd’s payment infrastructure to pay the Issuer of the trusted data (let’s say a consumer credit agency) in a privacy-preserving mechanism. The transaction (the loan) remains trustless, however, the relationship between the borrower and the lender has signals that support trust, enabling a more efficient lending market in crypto whilst retaining what makes crypto lending unique.

Lastly, let’s explore the application of credentials in the context of DAOs: A DAO commissions an anonymous artist for a specific artwork. The artist successfully completes the work and receives payment from the DAO. The DAO provides the artist with a credential endorsement stating their professionalism, quality work, and timely delivery. The artist can then anonymously share this credential with future projects or DAOs when applying for a job. In this scenario, the new DAO or project may compensate the previous DAO for the recommendation, as it helps de-risk their hiring process. By leveraging trusted data credentials, businesses and organizations can enhance trust and streamline onboarding to speed up work.

BCN: The so-called “bot paranoia” often makes users question whether the person they’re talking to in the digital world is really who they claim to be. Can a decentralized reputation system solve that problem for users? If so, how?

FE: A decentralized reputation is built on various signals that contribute to its credibility. These signals encompass a wide range, including KYC and liveness credentials, social media history (such as account age and posting frequency), and endorsements from other individuals or organizations. Users have the flexibility to combine and selectively share these signals to prove their reputation. While each signal could be manipulated individually, attempting to do so for all signals would be highly challenging and time-consuming.

Moreover, since each recipient of the reputation (i.e., the observer) can prioritize different factors, impersonating someone would require covering all bases, adding significant time and effort to the process. While impersonation remains theoretically possible, the time-consuming nature of such attempts makes it economically unviable. For instance, it would involve maintaining consistent social accounts over the years, demonstrating a regular history, and acquiring endorsements from reputable organizations and people.

BCN: Your company is said to be building a marketplace where holders, issuers, and verifiers can exchange and monetize verifiable data. Can you tell our readers who these holders, issuers, and verifiers are as well as how the exchange and monetization of data works?

FE: Absolutely. One nuance here is that “holders, issuers, and verifiers/receivers” are roles and therefore often overlap, especially for organizations. Let’s consider an example: An investment DAO employs someone to analyze companies and projects for potential funding. The DAO gives the person or people credentials so they can prove who they work for to the companies and projects so they can be trusted and prevent scamming.

In this scenario:

  • Issuer: DAO
  • Holder: Person
  • Verifier/receiver: Bank

Then, once the DAO has invested, it issues credentials to the company or project so that it can prove they are trustworthy and reputable to other investors or potential business partners without needing to involve the DAO all the time.

In this scenario:

  • Issuer: DAO
  • Holder: Company or project
  • Verifier/receiver: Other investors or potential partners

BCN: Much of the world’s data is still stored on Web2 servers. Bringing them to Web3 in a verifiable and privacy-preserving manner could help unlock new use cases or at least improve the existing ones. What are the challenges of bringing verifiable Web2 data such as credit scores to the Web3 ecosystem to facilitate economic activities?

FE: One of the primary historical hurdles of releasing data to the control of individuals has been the commercial aspect. Traditionally, companies collect, aggregate, and analyze data, generating revenue by selling either aggregate data or insights derived from their analysis. Transitioning to the new data paradigm, where individuals have control over their own data, requires new technologies, which entail costs for businesses. Without a viable revenue stream associated with these changes, commercial feasibility is limited unless mandated by regulations.

Therefore, the key challenge lies in establishing a clear and scalable revenue/commercial model, which is precisely what we at Cheqd are directly addressing. Our focus is on incentivizing the release of data from existing servers and silos back to the control of the individuals to whom it pertains. By solving this challenge, we can unlock new use cases or improve existing ones, facilitating economic activities within the Web3 ecosystem.

BCN: The KYC process is sometimes seen as a major stumbling block in the financial services sector. It can be time and resource-consuming and the data can be fraudulent. Do you think a so-called blockchain-based re-usable KYC can solve this problem and potentially improve the user experience?

Absolutely, re-usable KYC is particularly valuable in Web3, where users are highly mobile and prone to switching between multiple exchanges or marketplaces. For example, the European Commission found 21% of survey respondents had switched providers, i.e. exchanges or marketplaces within the last 5 years, higher than for any other product or service, e.g. current accounts or fiat investment products. It did not ask about switching multiple times within this period or using multiple providers which anecdotally we know most people do.

Currently, many financial service providers outsource their KYC requirements to third-party providers like Onfido, Jumio, or Trulioo, who perform the checks and provide the results. As a result, users often find themselves repeatedly providing their information to the same third-party provider when registering with different financial service providers.

By undergoing the KYC process once and obtaining re-usable credentials, users can utilize those credentials with different service providers multiple times. Implementing such a system would significantly expedite onboarding processes and enhance user satisfaction, particularly when compared to the current approach. It also allows people to use parts of those digital credentials for other purposes, like proving they are over a certain age to buy alcohol, tobacco or lottery tickets for example, without exposing everything in the credential.

What are your thoughts on this interview? Let us know what you think in the comments section below.

Leave A Reply

Your email address will not be published.

bitcoin
Bitcoin (BTC) $ 67,955.21
ethereum
Ethereum (ETH) $ 3,256.66
tether
Tether (USDT) $ 1.00
bnb
BNB (BNB) $ 579.37
solana
Solana (SOL) $ 182.86
usd-coin
USDC (USDC) $ 1.00
xrp
XRP (XRP) $ 0.596746
staked-ether
Lido Staked Ether (STETH) $ 3,254.79
dogecoin
Dogecoin (DOGE) $ 0.134149
the-open-network
Toncoin (TON) $ 6.70
cardano
Cardano (ADA) $ 0.41616
tron
TRON (TRX) $ 0.137342
avalanche-2
Avalanche (AVAX) $ 28.76
wrapped-bitcoin
Wrapped Bitcoin (WBTC) $ 67,787.16
shiba-inu
Shiba Inu (SHIB) $ 0.000017
chainlink
Chainlink (LINK) $ 13.54
polkadot
Polkadot (DOT) $ 5.84
bitcoin-cash
Bitcoin Cash (BCH) $ 379.01
near
NEAR Protocol (NEAR) $ 5.68
uniswap
Uniswap (UNI) $ 7.65
leo-token
LEO Token (LEO) $ 5.83
litecoin
Litecoin (LTC) $ 71.36
dai
Dai (DAI) $ 1.00
pepe
Pepe (PEPE) $ 0.000012
wrapped-eeth
Wrapped eETH (WEETH) $ 3,398.15
matic-network
Polygon (MATIC) $ 0.513638
internet-computer
Internet Computer (ICP) $ 10.10
kaspa
Kaspa (KAS) $ 0.182131
ethereum-classic
Ethereum Classic (ETC) $ 22.85
aptos
Aptos (APT) $ 7.02
ethena-usde
Ethena USDe (USDE) $ 0.99977
fetch-ai
Artificial Superintelligence Alliance (FET) $ 1.27
stellar
Stellar (XLM) $ 0.102532
monero
Monero (XMR) $ 162.75
blockstack
Stacks (STX) $ 1.87
mantle
Mantle (MNT) $ 0.844667
filecoin
Filecoin (FIL) $ 4.60
dogwifcoin
dogwifhat (WIF) $ 2.61
render-token
Render (RENDER) $ 6.60
injective-protocol
Injective (INJ) $ 25.61
bittensor
Bittensor (TAO) $ 347.05
okb
OKB (OKB) $ 41.15
hedera-hashgraph
Hedera (HBAR) $ 0.068711
crypto-com-chain
Cronos (CRO) $ 0.09146
maker
Maker (MKR) $ 2,631.47
immutable-x
Immutable (IMX) $ 1.58
arbitrum
Arbitrum (ARB) $ 0.726007
cosmos
Cosmos Hub (ATOM) $ 6.17
vechain
VeChain (VET) $ 0.028678
first-digital-usd
First Digital USD (FDUSD) $ 1.00
bonk
Bonk (BONK) $ 0.000029
arweave
Arweave (AR) $ 30.38
sui
Sui (SUI) $ 0.781144
optimism
Optimism (OP) $ 1.72
the-graph
The Graph (GRT) $ 0.200346
rocket-pool-eth
Rocket Pool ETH (RETH) $ 3,645.73
floki
FLOKI (FLOKI) $ 0.000181
renzo-restaked-eth
Renzo Restaked ETH (EZETH) $ 3,302.53
thorchain
THORChain (RUNE) $ 4.71
mantle-staked-ether
Mantle Staked Ether (METH) $ 3,380.22
bitget-token
Bitget Token (BGB) $ 1.12
theta-token
Theta Network (THETA) $ 1.50
whitebit
WhiteBIT Coin (WBT) $ 10.10
notcoin
Notcoin (NOT) $ 0.014212
aave
Aave (AAVE) $ 97.77
jupiter-exchange-solana
Jupiter (JUP) $ 1.07
ondo-finance
Ondo (ONDO) $ 0.994054
pyth-network
Pyth Network (PYTH) $ 0.390352
jasmycoin
JasmyCoin (JASMY) $ 0.029083
lido-dao
Lido DAO (LDO) $ 1.56
fantom
Fantom (FTM) $ 0.460232
based-brett
Brett (BRETT) $ 0.129209
coredaoorg
Core (CORE) $ 1.38
celestia
Celestia (TIA) $ 5.97
algorand
Algorand (ALGO) $ 0.143033
sei-network
Sei (SEI) $ 0.368989
ether-fi-staked-eth
ether.fi Staked ETH (EETH) $ 3,250.88
quant-network
Quant (QNT) $ 72.71
flow
Flow (FLOW) $ 0.667795
gatechain-token
Gate (GT) $ 7.65
mantra-dao
MANTRA (OM) $ 1.19
msol
Marinade Staked SOL (MSOL) $ 219.62
kucoin-shares
KuCoin (KCS) $ 9.70
popcat
Popcat (POPCAT) $ 0.941066
beam-2
Beam (BEAM) $ 0.018235
elrond-erd-2
MultiversX (EGLD) $ 33.32
axie-infinity
Axie Infinity (AXS) $ 6.06
bitcoin-sv
Bitcoin SV (BSV) $ 45.37
helium
Helium (HNT) $ 5.30
gala
GALA (GALA) $ 0.023601
ethereum-name-service
Ethereum Name Service (ENS) $ 26.53
bittorrent
BitTorrent (BTT) $ 0.00000089644018
eos
EOS (EOS) $ 0.577914
flare-networks
Flare (FLR) $ 0.01934
tokenize-xchange
Tokenize Xchange (TKX) $ 10.38
neo
NEO (NEO) $ 11.69
kelp-dao-restaked-eth
Kelp DAO Restaked ETH (RSETH) $ 3,314.28
ordinals
ORDI (ORDI) $ 38.64
akash-network
Akash Network (AKT) $ 3.30
dydx-chain
dYdX (DYDX) $ 1.29