|Price||1 LBt = 0.001 ETH|
|Price in PreICO||1 LBt = 0.0006 ETH|
|Bonus in ICO||● 1 week: -45,1% ● 2 week: -42,1% ● 3 week: -38,8% ● 4 week: -36% ● 5 week: -33% ● 6 week: -29,7|
We are constantly borrowing money from our friends or lending money to them. While some people might do this once every few years, others are doing it every month or even every week.
That said, while the essence of debt relations may be more or less clear, there are no commonly accepted social norms or rules of behaviour in informal credit markets between individuals, which can result in any number of problems and unpleasant situations. Nearly everyone knows someone who likes to say "I don't lend money to friends" or someone other people say you shouldn't lend money to; we sometimes help someone out with a loan only to find out later that they have already borrowed from most of their friends. And when it comes time for a loan to be paid back, we can also sometimes encounter problems that should never happen, e.g., when, on the day the money is due, the borrower simply disappears or ignores our calls. And, worst of all, no one has eliminated the risk of loss or fraud.
When we lack information about the borrower or have had unpleasant experiences in the past, this can increase the time needed to decide whether it is worth lending money at all, and it can also rid us of the desire to help even our friends.
At the same time, while there are already various applications in other spheres of our lives that simplify day-to-day activities and reduce the risks that might arise—from buying a used sofa to ordering a taxi— there is not a comprehensive solution to one very important aspect of our lives: financial relations between individuals.
That is why we came up with the idea of developing the Lendsbay application, which is a lending ecosystem where people can give each other loans, the history of which is stored in a blockchain, and the risk that they will not be repaid is assessed through social and bank scoring.
Our solution makes it possible to borrow money very quickly and easily—concluding an agreement in accordance with the laws of a particular country if necessary—to look for investors or borrowers from your own social circles or just to keep track of your debts, while also making it possible to have your accumulated positive credit history in Lendsbay taken into account when obtaining future loans: in case you move to another country or apply for a bank loan.
LendsBay search trends in Google
2. PREREQUISITES FOR THE PROJECT
3. MARKET ANALYSIS
4. PROJECT DESCRIPTION
5. PRODUCT: BETA VERSION
7. RISKS (USER RATINGS SYSTEM)
8. TOKEN DESCRIPTION
9. LEGAL REGULATIONS
11. LENDSBAY TEAM
12. PROTECTION FOR BUYERS OF TOKENS
13. CONCLUSION - DISCLAMER
We are constantly borrowing money from our friends or lending money to them. While some people
might do this once every few years, others are doing it every month or even every week.
That said, while the essence of debt relations may be more or less clear, there are no commonly accepted
social norms or rules of behaviour in informal credit markets between individuals, which can result in any
number of problems and unpleasant situations. Nearly everyone knows someone who likes to say 'I don't
lend money to friends' or someone other people say you shouldn't lend money to; we sometimes help
someone out with a loan only to find out later that they have already borrowed from most of their friends.
And when it comes time for a loan to be paid back, we can also sometimes encounter problems that
should never happen, e.g., when, on the day the money is due, the borrower simply disappears or ignores
our calls. And, worst of all, no one has eliminated the risk of loss or fraud.
When we lack informati...
2. Prerequisites for the project
There is currently a grey segment of the global lending market that lacks transparency, i.e., lending
between individuals (usually relatives, friends and acquaintances).
Although similar in size, this segment of the market differs significantly from the formal lending market
Normalising this lending market would reduce the risks for lenders and improve the terms for borrowers.
The main problems of the informal market are as follows:
formal loan records: disputes arise about repayment dates, terms and conditions; no
contract: there is no mechanism for judicial enforcement of debt repayment
credit history, which can have an impact on a borrower’s abi
lity to obtain subsequent
integration with the formal lending segment: behaviour in one segment does not
affect financing conditions in the other
3. Market Analysis
Analysis of the size of the market
An analysis of the size of the informal credit market on the basis of data from open sources and expert
estimates showed that the percentage of families not using any debt service is 10-25%; on average,
families take out one to two loans every year (any member of the family), the average loan term is one to
three months, and PTI
the ratio of the monthly loan payment to the family's monthly income
Taking into account the above calculations, the market size can be estimated at USD 1 trillion, which is
comparable to the size of the formal (banking) market for consumer lending:
2. 46% are willing to be borrowers
3. 63% are ready to be investors
4. 89% of respondents have at some point borrowed money, including:
5. 96% of survey participants have given a loan, including:
Given a loan to:
Make a bank deposit
The survey shows that a much larger number of people complete transactions in the informal
lending market (lending to people in their own circles: relatives, friends, co-workers, neighbours)
than in the formal market (e.g., making a bank deposit).
6. Surveys conducted in the United Kingdom and the United States showed considerable interest in
the platform, especially for documenting and formalising transactions between parents and
7. The reduced risk within social groups has been confirmed by a 2017 study by HeadHunter: of all
borrowers who take loans from their place of work, 97% of them pay back the amount in full. In
the case of the remaining 3%, the borrowers either forget or lose their jobs.
These results confirm the considerable degree of interest among the target audience, the need and the
usefulness of creating a tool for informal lending within the social groups identified above.
We are unaware of any project like Lendsbay anywhere in the world. Below, we take a look at our closest
competitors that have held an ICO:
Pre-ICO - June 2018
ICO - September
ICO - December
An ecosystem for
An open market that allows users themselves to decide who to lend to and at what interest rate
Use of fiat currencies and cryptocurrencies
The possibility of building an ecosystem for any socio-economic relations between people based
on groups and Lendsbay's blockchain rating: insurance products, the rental and sale of items,
decision-making and voting systems, other products
Differences from existing P2P platforms (e.g., Lending Club, Zopa)
The Lendsbay platform primarily supports lending between individuals who either know each
other, work together, studied at the same university or who have common interests
The operation of the Lendsbay platform does not depend on the presence of a critical mass of
users in a particular group or region (in general, P2P projects do not work if there is a small
number of users), which is a great advantage for the development of the platform in any
The Lendsbay credit rating system ta...
4. Project description
A new approach to loans between friends and acquaintances:
An approach to financing based on mutual assistance, trust and transparency
The ability to quickly and easily document a loan to a friend or acquaintance with confirmation
from the other party
Flexible loan terms at any time anywhere in the world
A rating that combines all the advantages of a bank rating based on data from credit bureaus and
supplemented by Big Data sources and a proximity rating
Borrowers create a transparent, blockchain-based international credit history
The ability to draw up documents, simplified recovery and natural motivation to comply with the
terms of the contract
Simple and convenient analytics
Artificial intelligence is used to improve the algorithms for social ratings
Prospects for the development of a socio-economic rating
Builtding a financial model.
Developed the server and user part of the application.
Developing the legal component (loan agreements, lawsuits, debt collectors).
Establishing ratings and pricing mechanisms.
Converting tokens, connecting to the app.
Adaptation for Telegram.
Connecting to a credit bureau.
Connecting to telecoms/online credit history providers.
Entry into the UK and US markets.
Linking to a payment system.
Implementing the social ratings system (proximity rating).
Implementing the behavioural ratings system.
Creating an API.
Entering developing markets.
Constructing a ratings model based on multiplicity of data.
Providing the suppliers of goods and services with secure access to the ratings system data to create their own ratings.
Granting financial organisations secure access to ratings data.
Creating various ecosystem elements.
Building a consolidated ecosystem of transparent relationships.