P2P credit. The role of reputation and solvency

The historical role of the Fractional Reserve Banking System

The Fractional Reserve Banking System has been a very useful financial instrument for the last centuries. It has provided trust. It has provided money abundance where it was most needed. And it has forced growth.

1. Banks provided a trusted registry service of all assets and money transfers. In the 18 hundreds banks were doing this bookkeeping in paper books of accounts and everybody trusted them. Modern banks were born having as competitive advantage the trust. Now this is done in worldwide interconnected and secured databases. Banks main asset is that we continue to trust them at doing the bookkeeping, and there seems not to be any reason not to do. I don’t know a single case worldwide of news about a breach of this trust.
2. Banks provided a service of giving loans, by creating money out of the nothing. The Fractional Reserve Banking System loan mechanism means that they are authorised to increase the total monetary mass (Money creation in the modern economy, by Michael McLeay, Amar Radia and Ryland Thomas of the Bank’s Monetary Analysis Directorate, Quarterly Bulletin 2014 Q1, BANK OF ENGLAND), and thus to generate a small inflation with each credit. The banks social added value is to analyse the solvency of the borrower. Banks give credit but also guarantee that the overall monetary mass goes back one day to the original level, so that money does not inflate forever.
3. Banks forced the economy to grow, and expand worldwide, because the obligation to pay back the capital plus an interest forced each business using loans to increase constantly the business, by selling more products in the market, or fail.

The end of the life cycle of the Fractional Reserve Banking System

The Fractional Reserve Banking System life cycle is at its end. The negative effects on the economy are now bigger than any beneficial effect. In fact, continuing with the Fractional Reserve Banking System may mean the death of the planet and with it the mankind.

1. As trusted registry, banks will become history. They have done this function with high quality. Unfortunately for banks, the blockchain can do the same, much better, more user friendly, faster, more effective and cheaper.
2. At giving credits, banks have been a fiasco when analysing the creditworthiness, the solvency, of the creditors. Instead, the bank speculators have been demonstrated as compulsive gamblers playing bingo and baccarat with real world. The profit of the financial market of derivatives of high risk credits given with no solvency was too tempting. We experienced the last world financial crisis in 2008. The next can be worst. The question is in the air is who will replace banks in this function. The essence of the discussion of monetary reform is the discussion about who analyses the creditworthiness of the creditor in any credit system, clearinghouse, or currency invention.
3. With regards growth, we do not want any more growth in products. Instead, we need to stop urgently any growth that consumes more natural resources. We need sustainable economies that grow only in wellbeing and equality. Credit with interest, if it was sometime justified, is now suicidal. Profit of risky investment is justified; interest on money created out of the nothing is not justified. 

The service of analysing the solvency is tricky. You may create automated reputation systems, but this will never replace a human analysis of all factors that may influence the solvency of a borrower. Analysis linked to solvency will stay human. We can provide indicators and some limits preventing major disasters, but that is all.

Radical democratisation of the solvency analysis

We propose to radically democratise the analysis of the solvency, and that is the main reason to propose an exclusive sovereignty of giving credit to the citizens, the P2P credit, as the only means to generate money out of the nothing when needed.  

Additionally, enterprises can generate self-credit in form of B2P type of currencies as a promise of goods. The solvency is analysed by their customers and the collateral is the enterprise goods.

The individual form of credit, the P2P credit, can be escalated to forms of crowd funding. It can be further escalated very carefully when individuals associate into DAOs to give credits. We can try out different degrees by which individuals delegate the analysis of a given credit to these DAOs, but the individuals will always keep the power of signing or not. By that, we hope to avoid the worst of the financial gambling we have experienced in the past.

Nevertheless, the question remains: How is the solvency analysed and how we prevent fraud and, worst, collective fraud?

We propose two mechanisms:

1. There is an index, reputation, which limits the amount of money a citizen is entitled to create as P2P credit. It’s the reputation of that citizen as honest moneylender. We have put already a penalising mechanism into the P2P credit smart contract. If the borrower does not pay back, you take all the available money from the moneylender. The limitation provided by the reputation limit is a previous safeguard.  
2. There is another index, the solvency, a public index of the borrower automatically generated by the system, which helps the moneylender to estimate the risk of the credit. In this case, it does not limit anything. Analysis linked to solvency has to stay human.

Elementary Reputations

Reputation as moneylender

There is no big deal at discussing the exact formula calculating the reputation, that is, the limit of credit each citizen is authorised to give at a certain moment in time. In the end, it will be a mathematical formula inside the P2P credit smart contract that each democratic association of citizens can change. It will take into account the historical success or failure of this citizen of giving credits that have been paid back. The formula below is proposed as a draft for the purposes of demonstration in the first implementations of P2P credit smart contracts.

1. The baseline reputation today measures the intensity of successful credits you have given in the past. It is calculated by the area of (amounts x time of the credits)/(time as citizen). In one word, if you gave a small credit long time ago, your reputation is low. If you accumulate a long experience of successful credits, your reputation is high.
2. At each period of time, the baseline reputation decreases with time.
3. At giving a credit, the amount of the loan is deducted from the baseline reputation. This deducted amount does not decrease, while the baseline reputation continues decreasing.
4. At payback, the deducted amount is deleted; the baseline reputation is increased by the amount of the successful loan.
5. Whatever quantity the moneylender had to put from his pocket is deducted from the baseline reputation.

Solvency as money borrower

There is more than sufficient literature about how banks should analyse solvency. Again, the formula below is proposed as a draft for the purposes of demonstration in the first implementations of P2P credit smart contracts.

1. The starting calculated factor is about the capacity of the borrower to pay back. We may calculate the proportion of regular savings to regular income the borrower has to put aside during the loan duration to pay the loan. To calculate the regular income we can look back at his history a period equal to the loan duration. This measures the effort the borrower has to do.
2. The second factor is to estimate the priority the borrower is going to assign to the payment of the loan, amongst other payment needs. To do so, we can use a similar formula as the baseline reputation, this time applied, not to the loans given, but the loans received.

A primitive solvency estimator, to be published at his profile, could well be the two factors multiplied. 

Complex reputations

Social Reputations

There are many posibilities to enrich these indicators with subjective social validations.

Taking into account the challenge

But the factors above can be improved by a more sophisticated calculation. For example, successfully lending money to a borrower that has a poor solvency record should be rewarded with a reputation reward higher than average. Failing to get the money back from a borrower with high solvency should be penalised more than average.

	high solvency borrower	low solvency borrower
sucessful loan	average reputation reward	high reputation reward
unsuccesfull loan	high reputation penalty	average reputation penaly

ethereum ĐEV plan https://www.ethereum.org/pdfs/Ethereum-Dev-Plan-preview.pdf Reputation system - In order for e-commerce to be successful, in many situations one must be able to know whom to trust. In some cases, you want to tell honest people apart from scammers. In other cases, you want to tell skilled people apart from the unskilled. Still other times, it matters not just what someone's current reputation is but also how highly they're leveraging it, so you can be sure that they cannot profit from scamming everyone all at once. Even in the modern world today, both online and offline, these problems are hard, but in the context of decentralized autonomous organizations they become even harder. Figuring out what can be done, and what should be done, in terms of effective reputation infrastructure will be a crucial concern even with regard to enabling different forms of trust between Đapps themselves. Trust through an escrow service

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TrustDavis on Youtube: Reputation on Ethereum
http://youtu.be/UXjIl0LZNOY
TrustDavis on Ethereum slides
http://www.slideshare.net/aatkin1971/...
TrustDavis: A Non-Exploitable Online Reputation System
http://www.cs.ucdavis.edu/~defigued/i...