DCC (DistributedCreditChain)是一项基于区块链技术的信贷信息服务,它基于区块链本身去中心化、不可抵赖、不可篡改的特点来提供一套服务生态,让信贷参与方共同加入去解决传统中心化交易模式下存在的问题。 DCC 是一条基于区块链技术的主链,在这条主链上为各种不同的分布式金融业务建立业务标准、达成账本共识、部署业务合约、执行清结算等服务。

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DCC / ETH = 0.000085
1 ETH = 13700 DCC
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ABOUT THE PROJECT


Accelerating digitalization, faster Internet transmission speeds, continuous accumulation of distributed computing resources, the application of mathematic and cryptographic technologies in the digital era: these are the factors that lead us to foresee that in the future, we will see an underlying public chain based on the features of Blockchain (including but not limited to: decentralization, openness, autonomy, irreversibility, and privacy protection). This underlying public chain will be utilized for distributed credit reporting, debt registration, wealth management, and asset transactions. It will enable business participants in different countries and regions around the world to provide financial services in a much more convenient way. A new type of virtual agency based on blockchain technology—"Distributed Banking"— will emerge. A Distributed Bank is not a traditional bank, but rather an integrated ecosystem of distributed financial services.

The concept of Distributed Banking is to break the monopoly of traditional financial institutions through fair financial serviced and return earnings from financial services to all providers and users involved, so that each participant who has contributed the growth of the ecosystem may be incentivised, thus truly achieving inclusive finance.

Through decentralized thinking, Distributed Banking will be able to change the cooperation model in traditional financial services and build a new peer-to-peer and all- communications cooperation model across all regions, sectors, subjects and accounts.

As it pertains to business, Distributed Banking will completely transform traditional banking's debt, asset, and intermediary business structure through replacing liability business with distributed wealth management, replacing asset business with distributed credit reporting, debt registration and replacing intermediary business with distributed asset transaction with . The tree-like management structure of the traditional bank will evolve into the flat structure of Distributed Banking, which will establish distributed standards for various businesses and improve overall business efficiency.

Benifects:

1.Eliminating Monopoly and Profiteering

Everyone will be able to choose their debtors, and in a decentralized market with numerous competitors, pricing power will rest with the market rather than intermediaries. Instead, market participants will get returns and reallocate the data value by providing algorithms and computation on the blockchain.

2.Protecting Privacy Reasonably

Original personal information and non-desensitization data should not be stored at third- party institutions for a long term. Retaining personal data with the user is the most secure storage method. Such storage can be local, or can be encrypted and stored in the cloud, with convenient retrieval via local addressing.

Personal data can be transmitted to the recipient in an encrypted, point-to-point manner. Only the data recipient may process the data, and theoretically, after processing, the data recipient can choose not to retain the data. Alternatively, data can be provided to the data demander in the form of zero-knowledge proof, which allows for verifying the data authenticity and ownership without revealing the original text of the information, in order to fulfill the business requirement.

3.Eliminating Data Monopolies

Blockchain technology allows individuals to own and use their data, and eliminates the value premium caused by the centralized storage and verification of data from third parties. It also prevents data from being misused or leaked by third parties: traditionally, the authenticity of data held by individuals is verifiable and individuals have only ownership of data rather than the right to use data (which can only be gained via authorization to agencies as a means of providing proof).

4.Improving Data Validation Efficiency and Reducing Data Use Cost

Personal data can be automatically validated and used for multiple times according to data categories, significantly reducing the cost of institutions who use the data. The institutions are free from repeatedly obtaining authorization from users each time they use or access the data.

5.Creating “Data Marketplace”

Establishing a standardized data marketplace helps data certification bodies better promote the data standards they processed, construct the brands and high-value niches in terms of big data processing, and helps fix the price according to data use frequency and through feedbacking data to data platforms. Financial institutions can also see the number of available data modules within the data marketplace more conveniently, and thus drive their own IT systems to connect more valuable data.

6.AI Risk Control

Anti-fraud and modeling algorithms are provided on the blockchain through deep learning and AI risk control systems, in order to help financial institutions process personal data without storing data. This method helps financial institutions improve their risk control capabilities in accordance with compliance requirements.

Blockchain discloses risk strategies by providing an encrypted algorithm, and allows borrowers to apply for verification based on the algorithms published by algorithm providers and credit institutions and proactively screen lenders through the risk strategy service. Borrowers who can not access institutional borrowing can choose not to apply for loans from those institutions, thus preventing submissions of personal information by multiple institutions.

This would lead to drastic increase in transaction efficiency and further drop in transaction costs for credit institutions, eliminates the need to allocate computational resources and payment costs to borrowers who cannot receive lending services.

7.DisclosingLendingBehaviors

During the borrowing process, by creating a credit history report on the blockchain, data approved by both parties is accessible to other institutions that need to obtain the data, effectively preventing problems such as long-term borrowing and repeated test borrowing.

8.Positive Data Feedback

Beyond use by the lender, lending data can be used to help multiple institutions provide comprehensive analysis of the lender’s behavior and lending results, and help non- participants of single-time loans establish a more comprehensive personal credit rating system.

Partial data disclosed also allows more auditors and regulators to evaluate systemic risks more effectively.

Distributed Credit Chain applies the above solutions with Blockchain technology in real business scenarios, and develop a new super credit ecosystem that benefits the world.



DCC (DistributedCreditChain)是一项基于区块链技术的信贷信息服务它基于区块链本身去中心化、不可抵赖、不可篡改的特点来提供一套服务生态让信贷参与方共同加入去解决传统中心化交易模式下存在的问题。 DCC 是一条基于区块链技术的主链在这条主链上为各种不同的分布式金融业务建立业务标准、达成账本共识、部署业务合约、执行清结算等服务。

DCC DistributedCreditChain 中用来支付劳动力(PayforJobs)的凭证, DCC 中任何的劳动都需要支付 DCC 作为工作的报酬。 DCC 的余额管理由 DCC token合约进行维护, DCC 总量固定随着 DCC 中金融服务系统的增多分布式商业场景嵌入的越来越多使用越来越频繁流动性会大福增加。

 DCC 在系统中的使用

1. DCC 重构信用成本

DCC 系统中个人要从数据机构获取数据报告需要向数据机构支付 DCC ,通过 DCC 的支付改变了原本数据服务机构获取收入的方式从原来收集用户数据处理倒卖信息牟利转变为更好的服务客户获得收入。

2. DCC 重新分配生态利益

DCC 系统中个人申请借贷需要支付 DCC 给申请合约其中一部分比例(例如:50%)按照信贷机构使用数据验证服务的权重进行分配给数据机构作为验证费用一部分比例(例如:2.5%)作为信贷激励损耗进入当日信贷激励池一部分(例如:7.5%)会被燃烧回收以确保 DCC 总量的持续释放。一部分(例如:40%)作为信贷结果奖励进行分配如果审核放款成功借款人主动确认借贷合同该奖励返还给借款人如果在1天内未主动确认借款合同或者借款申请被拒绝则该笔奖励分配给借贷机构。

3. DCC 激励信用积累

DCC 系统中借贷申请过程中的一部分比例(例如:2.5%)转化进入当日信贷激励池和生态固定激励形成总激励池 DCC reward合约进行维护在T+1日对T日按时还款的借款人均分奖励池奖励。在 DCC 生态中未来不同的业务会形成不同的rewardpool,生态参与者可以在使用和贡献不同生态时获得不同pool种的奖励。

4.跨越国界的借贷凭证

由于 DCC 系统提供的是一个跨国、跨场景、跨法币数字资产的信贷服务, DCC 可以在各个国家对应不同服务于借贷的法币价值这给借贷服务机构的跨国业务提供了极大的便利。


去中心化区块链对于信贷业务的价值

1.打破垄断和暴利

人人都可以选择放贷对象市场在去中心化的服务情况下百家竞争把定价权交给市场双方而不是交给中介机构市场参与主体通过在区块链上提供算法和算力获取回报重新分配数据的价值。

2.合理保护隐私

个人原始信息和非脱敏数据不应长期被第三方机构所缓存个人的数据保存在用户处是最为合理的方式存储的方式可以是个人本地存储可以是加密存放在云上通过本地寻址方便的取回。

个人传递数据通过加密通道点对点的传输给数据接收方只有数据接收方可以对数据进行处理处理完毕后数据接收方理论上可以不保留数据。或者数据以零知识的证明的方式提供给数据需求方通过不泄露信息本身原文的情况下证明数据的真实性和所有权完成业务需求。

3.打破数据垄断

让个人拥有数据的所有权和使用权传统的方式中由于无法验证个人持有数据的真实性个人拥有数据只有所有权没有使用权使用权需要个人授权机构提供证明才能获得区块链技术打破数据在第三方机构集中存放、证明带来的数据价值溢价也避免了数据被第三方机构滥用和泄露。

4.提高数据验证效率、降低使用数据的成本

个人的数据可以被自动验证正确、并且根据数据类型可以多次被使用能显著降低数据使用机构在使用数据过程中的成本。无需每个使用机构在每次使用用户数据过程中去重复获取用户的授权重复调用获取数据。

5.构建数据超市

建立标准数据超市帮助数据认证机构更好的营销自己处理过的数据标准建立大数据处理的品牌和价值高地通过数据被使用频率和反馈数据给数据平台进行定价。金融机构也可以更便捷的看到数据超市有多少数据模板可以被使用推动自身IT系统对接更有价值数据。

6.AI风控

通过深度学习和人工智能风控系统在链上提供反欺诈和模型算法帮助金融机构处理个人数据但又不存储个人数据合规的帮助金融机构提升风控能力。

通过提供加密算法将风险策略进行发布服务让借款人通过链上的风险策略服务基于算法供应商以及信贷机构发布的算法进行申请校验对于可以获得的借贷服务进行主动筛选而无法获得机构借款的客户则选择不与该机构发生借贷申请避免个人信息重复的多家提交。

这使得信贷机构的交易效率得到了大幅度的提升而交易成本进一步下降不再为了获取那些原本无法提供服务的借款人分配算力资源也不再支付成本。

7.借贷行为公开

借贷双方将双方认可的借贷发生过程数据开放给其他需要获得数据的机构通过在区块链上创建信贷历史报告帮助放贷机构有效避免多头借贷、重复试探借贷等问题。

8.数据正向反馈

借贷数据能够被除了借贷方使用可以帮助多机构全局的分析借贷人行为和借贷结果给单次借贷非参与方建立起对个人更全面的信用评价。

通过部分公开的数据可以让更多审计机构、监管机构更有效的评估系统风险。

DistributedCreditChain将以上解决方案落地到实际的业务场景中建立和进化为一个全新的、服务于全球的超级信贷生态。




ROAD MAP

09/2017

Established unified identity system based on the Ethereum test network

10/2017

DCC testnet launched

12/2017

DCC online credit declaration contracts deployed on DCC test net

03/2018

First personal loan product DApp launch on DCC, DCC Explorer launch

04/2018

Distributed Credit Chain open platform launch, second DApp launch

05/2018

Interface with more than five financial institutions with services ranging from loan, data and risk control

2018 Q3-Q4

Open self-creation API of Distributed Credit Chain

2018 Q3-Q4

Establish unified DCC MPC

2018 Q4

Enter Indonesia lending market

2019 Q1-Q2

Enter Vietnam & other SEA country lending markets

2019 Q3-Q4

Continue to develop and expand in the SEA lending markets

2020

DCC public chain migration

2020

Initiate development of Asset Manage and Settlement systems

TEAM

Stewie Zhu

Serial entrepreneur,Founder of TN Tech,Ph.D. candidate in Finance at LSE,M.S. in Financial Economics , Oxford University,M.S. in Statistics, Yale University

Vanessa Cao

Director at Keywise Capital, Partner at Bridge Capital, M.B.A, Tsinghua University, CFA

Stone Shi

TELECOM, Ingenieur, Former vice president at JP Morgan Chase, Nanjing University, Computer Science/Math, Nanjing University, Electronic Science and Engineering

Dr. Daniel Lu

Ph.D. in Mathematics, Yale University, Postdoctoral Research in Financial Engineering, focusing on the Representation Theory, University of Leipzig, Germany

ADVISERS & INVESTORS

Yu Chen

Partner of JX Capital, Famous angel investor, KOL in China with the net name as “Jiangnan Young Cynic (Jiangnan Fen Qing)”

Yuhang Guo

Chairman of Xinghe Capital, Co-founder and co-chairman of Dianrong, Former partner of a famous Shanghai law firm

Ming Yao

CTO of CCX Credit, the pioneer of China's domestic rating industry, Worked at Bell Labs, years of experience in big data technology

Zhiwu Chen

Former Professor at Yale University, Research Director at Hong Kong University, One of the most renowned and influential Chinese economist

Henry Cao

Renowned financial economist, Professor in CKGSB, finance, Former professor in UCB and UNC

Matthew Chang

Managing Director of KKR, Leading expert in the areas of private equity, fixed income, and capital markets, Former global senior partner at Roland Berger Strategy Consultants