The LendsBay system creates a new approach to loans between people, solving the problems such as: No formal loan records: disputes arise about repayment dates, terms and conditions; no reminders are sent; No contract: there is no mechanism for judicial enforcement of debt repayment; No market-based mechanism for determining interest rates: the market is either larger or smaller than its potential; No tools for risk management: no credit rating, diversification, insurance. ⠀ ⠀ We offer the following step-by-step solution to the above-mentioned problems: Creating an app to manage loans between relatives, friends and acquaintances: the app is used to find a lender and then to record, document and administer (e.g. send out reminders) the loan; Creating social groups (so-called bays) to pool financial resources through mutual lending, e.g. there are social groups centred around work, universities and social clubs that already have a certain level of trust, common values and a high degree of social control, not to mention little tolerance for irresponsible behaviour; Creating a blockchain to store individuals' credit-rating information (LBR); Using the blockchain for any financial transactions between individuals (non-credit assessment) (LBU); Developing the elements of an ecosystem for financial relations: mutual insurance; purchasing, selling or leasing items; and decision-making systems. ⠀ LendsBay team have already developed a functional and ready-to-use alpha version of the application.
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 "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.
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.
|“||2016-2017: Createding a web prototype.
Builtding a financial model.
Developed the server and user part of the application.
JUNE 2018: Conducting a pre-ICO.
JULY 2018: Release of the beta version of the app for Android/iOS.
Developing the legal component (loan agreements, lawsuits, debt collectors).
Establishing ratings and pricing mechanisms.
SEPTEMBER 2018: Carrying out an ICO.
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.
MARCH 2019: Creating social groups: Co-workers/University.
Linking to a payment system.
Implementing the social ratings system (proximity rating).
Implementing the behavioural ratings system.
Creating an API.
Entering developing markets.
SEPTEMBER 2019: Implementing the blockchain ratings system (LBR): distributed accounting and storage of ratings data.
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.
FEBRUARY 2020: Creating a universal rating for economic relations (LBU).
Creating various ecosystem elements.
Building a consolidated ecosystem of transparent relationships.
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