How Centrifuge is contributing to a new data paradigm

Data is the new gold of the digital world, a vital resource which when it comes to us as individual consumers and participants on the web, is coveted, used and commodified by Google, Facebook and other giant corporations.

As a measurable unit of information, data is ubiquitous, including in the business world. In that realm, it is viewed as a vehicle for growth, by enabling not only collaboration and the realisation of shared goals between businesses, but internally gives enterprises a competitive edge or a way to differentiate themselves. The marketplace recognises the importance of data, evidenced by the creation of new industries and careers which traverse data collection, analysis, and processing.

In centralised business and financing models, data storage, distribution and usage presents a number of challenges, such as data duplication, human input errors, inaccessibility, and questions around authenticity, validity and accuracy.

The problem of data silos is particularly pernicious. Data silos refer to the segmentation or isolation of data in way that undermines transparency, accessibility and verifiability. This can be the result of organisational culture, technological barriers, scaling issues, or other factors. Data silos can give an incomplete view of the business, create a less collaborative work environment, lead to bad customer experience, slow the pace of an organisation, waste storage space, and promote a closed culture.

Centrifuge brings with it a novel proposition to unlock data in a way that is verifiable, preserves its integrity and protection, and which creates material value and exchange. Its approach resolves a specific set of significant problems with data management.

Document data

Problem: Under existing financing frameworks, each business party stores and validates data independently, according to their own rules. This can create inconsistency and poor decision making around how data is used.

Solution: Creating on the blockchain a global, single and inalterable source of truth that ensures consensus on data documents.

Data state

Problem: Data is often stored in disparate, disconnected and siloed systems or networks with inconsistent ways of assigning status to that data. This creates inefficiency and undermines the trust in the system.

Solution:

A single, shared source of truth around the data through a codified governance model restores faith in the veracity of the data.

Data sovereignty

Problem: Data is often locked in single purpose, or private deployments. Although users might own their data, they are unable to use it or share it with other interests or third party applications in way that could benefit the business.

Solution: Data is stored and used in a decentralised way, allowing users the flexibility to share their data at a granular level while keeping all other data private. This system allows parties to share what data they choose with the party of their choice and for specific, agreed upon purposes. This removes the power of a single actor to censor the possibility of this exchange.

New generation of applications

Problem: Under a closed, segmented data management model, the ability of build, deploy and leverage applications that can advance the interests of the business is stifled. Launching new applications might require the re-building of the business network or creation of new marketplaces, which is costly, time consuming and creates another bureaucratic layer.

Solution: Under the Centrifuge system, users can freely choose whom to grant access to their information. For example, third party applications can receive access to current transactions, and history and document relationships. This might engender customisable and innovative responses to issues that plague the business.

Relationships between business and their data

Problem: Under siloed arrangements, linking businesses relationships, reputation and supply chain connections freely is difficult if not impossible. This undermines improvements to financing protocols and other processes.

Solution: Mapping relationships becomes not only possible but a central feature, which enables better ways of delivering payments, creating finance options and improving supply chain outcomes.

By connecting to a shared operating system, individual actors with their own unique values and interests can interact productively without giving up control of their data. The data can instead go to work to benefit themselves and their business partners, and the data itself can express a value that was previously not fully appreciated.

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I guess I hadn’t even considered the ability to chose which data a company shares as part of Centrifuge design. Great write up.

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Sounds like you guys have really given some deep thought to data sovereignty, I like

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Reading this only one comes to mind, Centrifuge can actually create an efficient market where the asset is perfectly priced acording to the knowledge revolving around said asset.

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Hi @Elias ,

that’s a good write-up and I think also where the general direction of decentralized (crypto) systems are headed. However, giving up “control of data” selectively can be quite the tricky issue.
For example, when we enter the realm of sensitive data, you’d not want to share it in a trustless manner. For investors that might be KYC data, for borrowers that might be sensitive company data (cash flow, assets owned, etc.).
Regarding Centrifuge/Tinlake, I’m wondering how data sharing can work for single assets & risk assessment.

Happy to discuss further :slight_smile:

Hi @metamod

Why wouldn’t You want to share the data in a trustless manner?
I am asking because i thought that trustless systems don’t need trust between system participants for system to be working, which means that all the data is accurate, valid and authentic. Nowadays people can alter informations pertinent to your risk assesment and the flow of information is slow, laggy.
With centrifuge, you aren’t relinquishing control on who can access what data because You will manage who can get which information.
I read your linked post and whilist I agree with you on the 2008 financial crisis, two factors are now different. Firstly we know now why 2008 happened and back then banks gave intrest only loans to subprime borrowers and then repacked those loans into derivatives, which were then sold to everbody and inflated the bubble (sentiment: American citizens will never not repay his/her loan).
Again what I think with centrifuge is that those situations with pools(derivatives) filled with bad assets would be recognized sooner as you have the option to see underlying assets of the pools.

Best regards

Hi @Ivor ,

good thoughts - let me share my view on your questions:
My point regarding data sharing is that some data falls under privacy concerns.
For example a borrower would not want his or her risk assessment raw data to be public, since it usually contains also sensitive data. Example: List of assets owned by the legal entity, cash flow, etc., public knowledge of which may pose a competitive disadvantage to the entity.

I was not discussing this specifically, but you mention that in a trustless system data is accurate, valid and authentic. While technically it is true that data on the blockchain is immutable, the accuracy, validity and authenticity really depend on the oracle. If for example fraudulent data is being put onto a blockchain it doesn’t help at all that it cannot be modified.

So the bottom line question is: How are the two positions resolved that on the one hand you want as much data as possible to generate a good risk assessment and on the other hand you want to expose publicly a risk assessment which is trustworthy, while (parts of) the raw data must not be shared. How can you then trust the risk assessment if it cannot be verified?

Kind regards