The Challenger — Decentralized Credit Rating (DCR)
Systematic Failure and The “Credit Crunch”
Do we learn from the past? In 2007, the financial crisis has led to the deepest recession since 1930, leading to an extensive drop in private spending, high unemployment rates and major liquidity shocks across various banks, also known as the “credit crunch”. Lending conditions were tightened drastically, so that intermediaries were unable to mitigate the scope of liquidity shortages.
In four subsequent years, total investment expenditures were 20% lower, affecting especially small and young firms, who were strong depended on bank credit. This leads to the finding, that firm investment decisions are subject to the availability of bank credit. However, an analysis published last year suggests that banks do not “selectively reduced credit because of those firm characteristics” (Cingano, Manaresi & Sette, 2016, p.3).
Does it mean, that if centralized lending institutions do not fully control the consequences of market forces, that a decentralized lending structure might be able to mitigate market risk more efficiently, due to the nature of being an independent and globally accessible liquidity pool?
The Creation of Credit History and it’s Centralized Attitude
The credit history of a borrower is nothing that begins to exist with his or her birth, but it is rather a process of entering the financial market for the first time, as well as acting in it and sometimes building multiple credit histories simultaneously. How does that work?
A consumer’s credit record is aggregated in a credit report conducted by credit bureaus or other reporting agencies. Most of the data comes from creditors (e.g. banks), that include account information about the payment history, credit limits, balances and the number of new loan applications, which is evaluated on a regular basis.
Interestingly, credit history is created completely from scratch, when someone is moving to another country. That means, that when you plan to immigrate, credit history stays within your country. Pursuing this further, even the same applies for most networks of credit cards or credit bureaus, who do not share information between different countries.
For example, a person that lived in the U.S. for many years, which has accumulated a very good credit score, might move to Europe and experience difficulties in accessing loans due to the lack of a credit record. This person needs to establish a new credit history, until he or she will be able to obtain mortgages or even credit cards.
The Role of Credit Scores and Occurring Misuse
With the increase of popularity of credit and the difficulties in assessing individual credit risk, lending institutions started to introduce credit scoring. The benefit of scoring is the reduction in risk evaluation costs due to process automatization and thereby an increase in loan availability.
Credit scores, conducted by mathematical algorithms, show a numerical number that indicates the creditworthiness of a borrower (e.g. in the US between 300–850, with low number being negative rating and vice versa). The aim is to analyse the credit history rapidly, by comparing it to other debtors.
When borrowers accumulate an extensive number of defaults or late payments, the score will suffer and aggravate the access to credit. The calculation of the credit score varies between the models, but the general scoring system by FICO (based in U.S.) is the standard for other global areas also. Factors that are included are:
- Payment history (35%)
- Debt (30%)
- Credit File Age (15%)
- Account Diversity (10%)
- Search for New Credit (10%)
Credit reports are a big market and contained information are sold by credit agencies to firms and lending institutions. This creates much room for misuse, as shown by a new study, that found job seekers in the U.S. getting refused by employers, due to their personal credit score. In fact, 1 out of 4 unemployed are affected by those measurements.
Decentralized Credit Rating on the Blockchain?
All above described criteria for a functioning credit risk assessment system do suggest, that setting up a scoring model is far from rocket science since it can be broken down into a few examined factors, which occurrence and accessibility is greater and easier on a decentralized environment such as the Ethereum blockchain, as it is the case with the narrowed and bureaucratic lending market, where rating agencies do not even provide credit information to their subsidiary abroad.
To establish a real decentralized lending system on the Blockchain, that for now consists only of pseudo-anonymous users, we need to introduce a fully Decentralized Credit Rating (DCR) system, that obtains it’s data from the Blockchain directly. This way, the risk profile related to collateral free lending might become tangible, since addresses will have reputation, as we have it with centralized credit scores.
As we just learned, the credit history occurs at the moment when a new participant enters the systems, by getting involved into financial transactions. The Blockchain is a global, open and in real time available ledger of financial transactions, that can be analysed using automated algorithms and prediction markets. Just because credit scoring is not existent on the Blockchain, it does not mean that there won’t be any invented at some point.
DCR Allows for Interoperability between DAPPS
A Decentralized Credit Rating might help to mitigate risk in decentralized applications and increases use-cases from financial applications and merchants to any DAPP on the Ethereum Blockchain. That is the beauty of a globally connected transaction ledger.
DCR allows for increased security for the users as well as the developers of the DAPP. The blockchain gives access to a load of worthy information such as the number and source of transaction, the monetary balance, payment status, age of account and existing Blockchain assets (e.g. ENS domains, tokenized gold in the case of DigixDAO or tokenized real estate with REAL).
A DCR might create a system that finds those information sufficient for evaluating the creditworthiness of a borrower on a decentralized lending application such as ETHLend, a biometric payment application (e.g. Humaniq) or even a digital assets management platform like ICONOMI. The use cases and potential is huge as can be seen from the various examples. The remaining question is not „if“ there will be a system for Decentralized Credit Rating, but „when“ and „how“ it will be accomplished.
First research and real application testing is conducted by ETHLend itself, using a credit reputation system that rewards borrowers on each successful loan repayments with with non-transferrable credit tokens (CRE). CRE is only an attempt and does not solve the problem since due diligence by the lender is still required. However, the future will show what further inventions are needed for building a trustful DCR on the Blockchain.
Disclaimer: The author of this article, Sergej Stein, is the Financial Advisor at ETHLend, a decentralized lending application running on Ethereum Network.
Sources
Cingano, Federico, et al. “Does Credit Crunch Investment Down? New Evidence on the Real Effects of the Bank-Lending Channel .” OUP Academic, Oxford University Press, 7 June 2016, academic.oup.com/rfs/article-abstract/29/10/2737/2223378/Does-Credit-Crunch-Investment-Down-New-Evidence-on.
Author: unknown, “Credit History.” Wikipedia, Wikimedia Foundation, 11 Aug. 2017, en.wikipedia.org/wiki/Credit_history.
Stani Kulechov, “ETHLend.io White Paper — Democratizing Lending.” Github, 26 June 2017,
https://github.com/ETHLend/Documentation/blob/master/ETHLendWhitePaper.md.
About the author:
Sergej Stein from Germany/Frankfurt, Financial Advisor & Blog at ETHLend, Blockchain Enthusiast and Entrepreneur, leading various E-Commerce projects and being currently involved at the Frankfurt School Blockchain Center (Germany’ first Blockchain Research Center at German’s leading Business School). Many years leadership experience in international businesses, with almost ten years experience in economics. He is regularly producing articles on blockchain and finance, that can be found on platforms like Steemit, Medium or Patreon.
