“Litentry & Friends” is a Youtube live show hosted by the Litentry team that focuses on sharing knowledge about decentralized identity. In each panel, we will invite top project partners to discuss and share their insights on the industry, the context of the collaboration, and the outlook for Web3.
In the first episode, we have invited Irene Zhao from Konomi Network and Lilly M.Dobreva from Litentry to talk about how DID empowers DeFi and unleashes its full potential.
Hi everyone, welcome to our very first episode of our brand new youtube AMA series Litentry & Friends. My name is Jacky…
We’re thrilled to announce that Litentry is joining Web 3.0 Bootcamp 2021 along with other 11 teams building on Substrate and Polkadot. The 2021 cohort has a diverse representation of Web 3 stack covering smart contract, browser, decentralized identity (DID), layer 2, privacy, Defi, and more. In collective efforts, all teams will work towards a primary goal which is to pave the way for the next phase of the Internet, Web 3.0.
Hosted by Wanxiang Blockchain Labs, New Chainbase, Parity and Web3 Foundation, the program will provide Litentry six-month training with technology, product, capital, cooperation resources in the Wanxiang Blockchain…
Announcing our strategic partnership with InsurAce, both teams will be working together to explore the application of decentralized identity technologies in the decentralized insurance use cases.
Although DeFi insurance leveraging on the blockchain technology has proven to be effective and useful, it can be further improved if more identity information can be applied to tackle some of the challenges.
Although blockchain technology can prevent the identity profile from being monitored, its pseudo-anonymous nature creates additional issues which compromise user’s experience and fail to meet legal requirements.
We are excited to announce this new collaboration with Konomi to use our on-chain Decentralized Identifiers (DID) data to better cater to the needs of Konomi’s growing borrower and lender customer base.
Under this partnership, Litentry’s on-chain identity aggregation data and credit computation model will bring value to Konomi as we explore new ways to adjust and integrate collateral rates, as well as credit scores based on a user’s verified on-chain identity.
Also, this credit score will be derived from sophisticated algorithms with variables such as average loan repayment period, leverage ratio, credit utilization ratio, net asset value, risk preference…
$LIT token listed on Korean crypto exchange Coinone in trading pair LIT/KRW. Starting from April 22th, users will be able to buy and well $LIT using KRW(currency of South Korea). Founded in 2014, Coinone is one of the biggest crypto exchanges in Korea, with a…
We are happy to announce our collaboration with Standard Protocol — a collateralized Rebasable Stablecoins (CRS) protocol. We will work together to improve the IDO whitelist selection process to ensure fairness and decentralization.
Current problem of IDO is that projects have been facing issue selecting addresses eligible for the allocations to prevent scambot and multiple accounts. This deteriorates the fairness and decentralization of the game. The selection process needs to be refined and handled with a more advanced and flexible mechanism.
As part of this collaboration, Litentry as a service provider, will provide advanced IDO whitelisting methods with identity-based whitelist…
Litentry partners with Razor Network to provide verified data for DID Aggregator
Litentry partners with Razor Network to provide verified real-world data for our DID Aggregator
Razor Network is a decentralized oracle providing data to the smart contracts using a network of stakers. And because of that, Razor’s performance is superior and more secure than traditional centralized oracle services.
In order to ensure that smart contracts can access reliable DID data, Litentry will employ a third party to undertake the DID data verification process. Centralized data providers provide this service, but such data is often unreliable, as the data providers…
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