PRE-ICO WHITE PAPER

Contents:

1. INTRODUCTION 3

2. PREREQUISITES FOR THE PROJECT 4

3. MARKET ANALYSIS 6

4. PROJECT DESCRIPTION 10

5. PRODUCT: BETA VERSION 13

6. TECHNOLOGIES 14

7. RISKS (USER RATINGS SYSTEM) 15

8. TOKEN DESCRIPTION 17

9. LEGAL REGULATIONS 20

10. ROADMAP 22

11. LENDSBAY TEAM 23

12. PROTECTION FOR BUYERS OF TOKENS 25

13. CONCLUSION - DISCLAMER 26

1. Introduction

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.

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 (banks/multilateral lenders).

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:

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 credit history, which can have an impact on a borrower’s ability to obtain subsequent loans

No integration with the formal lending segment: behaviour in one segment does not affect financing conditions in the other

No market-based mechanism for determining interest rates; the market is smaller than its potential

No mechanisms for reducing risk: credit ratings, diversification, insurance

Why did the Lendsbay system appear now?

For the Lendsbay platform to be created, numerous conditions had to be in place, the most important of which is the emergence of an alternative to global financial markets. We are referring to the rapid pace of technological progress, thanks to which everyone now has a device that enables them to carry out any financial operations they want whenever they want; the appearance of blockchain technology, cryptocurrencies and smart contracts, which significantly increased the security of interactions without intermediaries.

The successful experience of various P2P trading platforms for smartphones prepared the groundwork for financial applications. The majority of them, however, were aimed only at formal markets (the banking segment), while the informal market—lending between individuals—remained "in the shadows".

What is the purpose of the Lendsbay system?

The Lendsbay application was designed for interaction between users. One of the main purposes of the application is to streamline and secure the informal financial market, as well as to simplify the procedure for finding partners and completing transactions. This is what its main functionality was designed for, which includes:

Simple and easy-to-understand debt management

The conclusion of a contract based on agreed loan terms

Notification of current and upcoming events (payments)

User-friendly search function for borrowers/lenders

A tool for assessing the borrower's level of risk

The creation of social groups (bays)

Loans in bays (co-workers, friends, classmates)

A blockchain-based credit history

Preparation of court documents in the event that a borrower refuses to repay their loan

The work of bailiffs for court-ordered debt collection

Resale of distressed debt to third parties or collectors

The platform is not limited to its main basic functions. From the beginning, the application has also included broader, global solutions that allow users to interact with third-party markets, making it possible to record a credit history in other financial companies in different countries. Prospects for project

development: the establishment, maintenance and assessment of not only financial but also other socio-economic relations between individuals.

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—is 50%.

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:

The Golden Billion

Russia, CIS,

Eastern Europe

Africa, South

America, Asian

countries

China India,

Pakistan, Bangladesh

Total

Population, millions 1,136 412 2,848 1,388 1,713 7,497

Average family size, # 2.5 2.6 3.5 2.0 4.8 3.0

Number of households, millions 455 158 814 694 357 2,477

Debt-free households, % 10% 15% 20% 15% 25% 17%

Number of indebted households, millions 409 135 651 590 268 2,052

Only formal banking, % 90% 55% 25% 30% 15% 40%

Informal banking, % 10% 45% 75% 70% 85% 60%

Number of borrowers in informal banking, millions 41 61 488 413 228 1,230

Number of loans per year 1 2 2 2 2 2.0

Average term, months 3.0 2.1 1.5 2.5 1.3 1.9

Average household income, USD 1,500 650 250 488 210 384

PTI ratio, % 50% 50% 50% 50% 50% 50%

Average household income, USD 3 2.1 1.5 2.5 1.3 1.9

Average amount of debt, USD 2,250 682.50 187.50 610 136.50 382

Outstanding balance, USD millions 23,011 14,468 22,886 104,942 6,729 172,037

Disbursed per year, USD millions 92,045 82,674 183,092 503,723 62,114 923,649

Sources: • National Research University Higher School of Economics: "Informal loans in Russia credit rationing or

borrower's choice?" • http: //www.nationmaster.com/country-info/stats/Cost-of-living/Average-monthly-disposable-

salary/After-tax • "Household Size and Composition Around the World 2017":

www.un.org/en/development/desa/population/publications/pdf/ageing/household_size_and_composition_around_the_world_2017_data_booklet.pdf

• Working paper, National Research University Higher School of Economics: "Informal loans in Russia: credit rationing or borrower's choice?", publications.hse.ru/en/view/93695695

Marketing research

Lendsbay conducted several marketing surveys on the need and demand for such an application among respondents in Russia, the United States and Great Britain, and the following trends were identified:

1. More than 81% of respondents assessed the application as promising and said they would like to

use it

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:

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 children. For example, where parents lend their children money to pay for cars, flats or their education and, at the same time, they need to help their other children or to continue saving after retirement, they would like to have a contractual basis for the transaction or an unequivocal record of the loan.

Bank

Friends

MFO

Neighbors

Relatives

Co-workes

0% 10% 20% 30% 40% 50% 60% 70% 80%

Borrowed from:

0% 20% 40% 60% 80% 100%

Friends

Neightbors

Relatives

Co-workers

Make a bank deposit

Given a loan to:

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.

Competitive environment

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:

LENDSBAY Karma Elix Salt Micromoney

Pre-ICO - June 2018

ICO - September

2018

Pre-ICO - August 2017

ICO - December 2017

Pre-ICO/ICO -

October 2017

Pre-ICO/ICO -

August 2017

Pre-ICO/ICO -

October 2017

Main idea An ecosystem for

informal lending

between individuals

based on a

blockchain rating

An ecosystem for lending

among small and medium-

sized businesses

A credit, payment

and crowdfunding

system

Loans

denominated in

a fiat currency

secured by a

cryptocurrency

Cross-border

multilateral

lenders

The existence of an alpha product

(at the pre-ICO stage)

Yes No No No Yes

Region of

operations Global Europe, Africa Global Global Africa, Asia

Use of fiat

currencies in lending

Yes No No Yes Yes

Availability of own scoring

Yes Yes No No Yes

Paid basic functionality

No, only advanced functionality

Yes, commission on

operations

No Yes No, loan interest

Lending in

cryptocurrencies Yes Yes Yes No Yes

Amount collected

in the pre-ICO/ICO (USD

million)

- 0.5/10 9 45 10.5

Market segment P2P Small business P2P

Multilateral lenders

Multilateral lenders

Basic token functionality Utility token, fuel for

the system Utility token

Utility token; two tokens: one for

loans, the other for rewards

Security (bill of

exchange) Currency

As can be seen from the table, Lendsbay's closest competitors do not operate in the informal market for lending between individuals and instead occupy other niches in the financial sector.

Key advantages

Lendsbay's advantages in relation to financial projects that have held an ICO:

The availability of an alpha version of the product prior to the pre-ICO

Unique scoring (rating) system using various parameters with the use of a proximity rating

Decentralised application geography: most projects are located within one region, one jurisdiction or a limited number of countries

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 geography

The Lendsbay credit rating system takes into account the existence and strength of social connections between potential borrowers and lenders

The Lendsbay ecosystem is scalable and can cover not only lending but also other socio-economic relations between people

The Lendsbay platform includes the development of a blockchain-based international credit bureau and is a catalyst for mutual improvement of the informal and formal consumer lending sectors

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 Benefits:

For lenders:

Recommendation of the borrower's loan rate

More effective use of free cash

Relationships are (legally) documented (loan agreements)

Reminders about repayment are sent

Analytics on the use of funds

Use of a mechanism for social control within groups

Preparation of a statement of claim in case of default

The possibility to sell debt and involve collectors

Potential to use insurance to reduce risks

For borrowers:

Very quick decision-making

Lower lending rates than in banks

No mandatory insurance

Remote loans through the app anywhere in the world

Reduction of the interest rate on the basis of a positive credit history

Flexible loan terms

Possibility of debt restructuring

Possibility of obtaining a loan without having a bank credit history

Transparent, blockchain-based international credit history

Social groups (bays):

Financial relations today are concentrated in spheres with a high cost of intermediation or with a low level of oversight:

In the formal sphere (banks, insurance, financial organisations), where there is a high price for mediation;

In the informal sphere (family, friends), where there is a high degree of tolerance, including in relation to unreliable behaviour.

To reduce the cost of mediation while maintaining a certain level of oversight, large communities are needed, like "bays" for ships. Without communities, financial relations are less controllable, less stable and less comfortable.

Based on a balance between transparency and the degree of social control, we plan to emphasise the following main social groups in the app:

FRIENDS: close acquaintances with a history of mutual relations and/or common interests. Given the high degree of trust within this group, the Lendsbay ecosystem adds a degree of responsibility (through loan documentation) and a convenient mechanism for accounting, management and oversight;

WORK: groups of employees within an organisation. This social group is characterised by an ample level of trust and social control, while Lendsbay's user rating and legal arrangements further reduce risks;

UNIVERSITY: a group of people associated with one institution. This group is characterised by a sense of belonging and responsibility. At the same time, people in this group tend to interact with one another less often than in the "Friends" and "Work" groups. In this group, the Lendsbay ecosystem further simplifies communication between people and adds up-to-date information about the financial situation and the rating of potential borrowers.

In addition to these groups, there are plans to create additional groups based on interests, e.g., sports, art, business, travel, which will have the advantages of the above groups.

Ratings system

The core of the system is the unique Lendsbay ratings system for users of the Lendsbay ecosystem, which combines all the latest developments in the banking sector, the use of credit bureaus, as well as a proximity rating, self-learning models (artificial intelligence), and the recording and storage of ratings in a blockchain. An important advantage of our rating for users is that it reflects a user's entire history of financial relationships in a format that the parties can easily understand, which is necessary to make the right decision when granting a loan.

Blockchain

Ratings are recorded and stored in encrypted form in a blockchain. Access to this data by third parties (lenders, financial companies, banks) can only be obtained with permission from the borrower by entering a one-time password.

Lendsbay's open blockchain will be available to every user for recording and reading credit histories. Thus, other financial companies will be able to record the history of user relations in the blockchain by using their personal digital signature. By gaining access to information on a user, banks and other companies will understand the degree of credibility and reliability of the data obtained on the basis of their trust in the company/platform that recorded it.

Tokens will be fuel for the blockchain, to serve as payment for third-party access to ratings. Thus, the value of tokens will be tied to growth in the cost of demand for credit histories. As a result of conversations

with several of the largest banks in Russia, we were able to confirm their interest in accessing information on the credit history of users in the informal market.

The advantages of using blockchain technology for Lendsbay:

The inability to modify transactions: neither the system nor the borrower can change the credit history stored in the blockchain

The distributed storage of information enables a high degree of data security

Improved fault tolerance through decentralisation

The ability to work with crypto-assets: BTC, ETH, tokenised assets (property)

Being linked to present and future blockchain registries: identification of people and companies, state registers

Outlook

As the Lendsbay project develops, and with an increase in the number of users, new elements of the ecosystem will emerge that extend beyond credit:

Financial services

Rating users and suppliers of goods and services

Mutual Insurance

Formalising relations related to leasing various items

Co-financing

Decision-making and voting systems

5. Product: beta version

In 2017, a web prototype of the application was developed that included: lending in the informal market on the basis of social groups, documenting debt relationships, renting items and documenting small loans. On the basis of this prototype, usability testing was conducted, and marketing surveys were carried out among the target audience, which identified the main areas for improving the prototype.

In 2018, on the basis of testing, the usability and the design of the application were completely overhauled. The beta version of the application is currently being finalised, which will be released for the iOS and Android platforms. The main functionality of the beta version is aimed at making it as easy as possible to document a debt relationship between friends and acquaintances.

A borrower will be able to find a lender, document the loan and sign the contract remotely in electronic form.

The app’s homepage will provide information in a user-friendly and easy-to-understand form on loans issued, indicating the amount and the date of the next payment.

A few days before the date of payment and also on the day of payment, the borrower will be notified of the need to make a payment. The application will allow both free-of-charge (without interest) and paid (with interest) loans.

After registering in the application and filling in their personal information, the user will be assigned a credit rating based on internal algorithms developed by Lendsbay, as well as external sources, including bank data (credit bureaus).

In the event that the lender does not receive a payment from the borrower and if a postponement has not been agreed upon, the lender is sent all the necessary documents and recommendations for taking appropriate legal action to protect their interests, and in the future it will be possible to file court claims directly through the app.

For professional lenders, the app will provide an advanced statistical system, as well as the ability to search for borrowers not only among their own contacts and in bays but also among other users of the application.

6. Technologies

Platform

The platform is a complex information system consisting of several components:

A mobile app

The back end

The program interface (API)

A blockchain/tokens

The mobile app will be written using React Native, a cross-platform framework for developing mobile applications from Facebook. This framework enables the use of the popular and reliable React library for the Android and iOS mobile platforms, which combines the development speed and flexibility of Javascript and the performance of native mobile device technologies.

The mobile application will interact with the server through a high-performance, scalable REST API implemented using Python and the asynchronous AIOHTTP framework. First, the API for the mobile app will be completed. In the future, however, there are plans to create a similar solution that will allow third-party developers to work with the Lendsbay ecosystem. The API, which was designed from the start to work under high-load conditions, was prepared in advance for scaling and decentralisation.

The back end will handle the system's primary calculations. It will be implemented in the form of a number of different services connected to a database that will perform both the calculation and processing of data from mobile apps and the integration of information from external services, creating a combined data processing complex.

Fault tolerance will be ensured with the help of horizontal scaling, backup of stored data and decentralisation of the back end by splitting it into micro-services.

Pre-ICO/ICO tokens will be sold through smart contracts on the Ethereum platform and will fully comply with the ERC20 standard, which ensures the ease and convenience of working with any third-party software, thus providing a versatile and well-designed interface for operations.

Smart contracts will also be prepared for conducting the pre-ICO and ICO, which will work with tokens at all stages. All contracts will be implemented using Solidity, a language for the Ethereum Virtual Machine.

7. Risks (user ratings system)

Imagine that you are a bank or an investor who has a certain amount of free money to invest. If you want to lend someone money, i.e. issue a financial instrument with a predetermined payment schedule, you would like to be sure that the money will be paid back and, of course, that it will be paid back on time. There is a risk in any investment, however, and to make financial decisions, you have to be able to assess that risk.

The main tool used for this are statistical or scoring models that use a historical sample of issued loans that are marked as "good" (paid on time) and "bad" or that were defaulted.

This task has a number of serious obstacles and limitations, which, as we will show, reveal a certain injustice in the banking sphere.

The first limitation: all documented cases of non-payment by borrowers took place in the past. Mindlessly using information from the past would be like driving a car by looking in the rear-view mirror. That is to say, when measuring risk, you have to find a set of observations related to a situation that is similar to what is expected in your planning horizon and to be able to predict future changes that are not yet visible in the data from the past.

The second limitation: the information about the borrower that exists at the moment a decision is taken. Every default has a reason (or a series of reasons), e.g., a conscious decision not to pay from the very beginning, i.e., fraud; a client has a large amount of credit, and if they lose their job a year after a loan is issued, let's say, this leads to a default on all their loans; and, of course, unforeseen circumstances—anyone can be struck by lightning, after all. The problem with risk assessment is in trying to see signs of an increased probability of future non-payment when taking a decision and to assess the likelihood that such signs will manifest during the loan term. This is why banks make you complete a questionnaire with a large variety of questions—banks need comprehensive information for risk assessment. And yet, if there is not enough information about you in the system, assessing your risk would be like determining if a patient has a fever based on the average temperature of all the patients at a hospital. This is unfair since good borrowers with a low level of risk have to pay for the bad.

A third source of injustice is created by the types of scoring models used (logistic regression and other linear models) and the lack of data on non-payments, as a result of which averaging is used and the classification of the borrower is simplified according to a risk profile.

In banks of the past, scoring is used as an excuse for refusing a particular loan product. In financial companies of the future, scoring is used to select a product with a fair price to serve the interests of the borrower or to resolve the specific situation that the borrower is in. We are currently witnessing a transition period. The amount of information requested from clients is also being reduced, and in financial organisations of the future, the only things that a person will be asked to provide are their identity and their interests (if this is not determined automatically).

The ratings system developed by Lendsbay will combine a classic banking approach to scoring and innovative elements:

User registration and participation in Lendsbay's 'bays' as a tool for pre-filtering risks

Proximity rating: a rating based on an analysis of the user's circle of acquaintances, relatives and co-workers, their interconnections within bays, and recommendations of other users (taking into account the amount of potential loans) While banks evaluate a client mainly on historical data alone, Lendsbay conducts a risk assessment that combines bank scoring and social scoring, which makes it possible to identify risks with much greater accuracy and to select more precise conditions for payment. At the same time, the main purpose of scoring in the Lendsbay platform is not to intercept "risky" borrowers, but, by using the right pricing, to help any user find a lender

Using BigData (telecoms, social networks, the Internet, SMS aggregators, etc.)

Combating fraud by using external data sources and simplifying identification through the use of social networks/social circles

Calculating user ratings with a minimum number of fields in the questionnaire

Using machine learning to further improve the scoring model

According to our expectations, the system will create a stream of loans at annual interest rates from 7% to 30% and expected risks of 2% to 15%.

Flowchart showing Lendsbay's scoring and pricing system:

In addition, the scoring system will be improved on the basis of information about user debts recorded in the application and the actions taken with respect to those debts.

To protect investors' interests, we will develop risk diversification tools, such as insurance and the Lendsbay insurance fund, which will yield attractive returns and hedge potential defaults.

8. Token description

About tokens and their role in the application

The LBT token for the pre-ICO and ICO will be released on the Ethereum platform and will fully comply with the ERC20 standard. This standard guarantees the compatibility of the token with third-party services and applications running on the Ethereum platform, such as wallets, exchanges any other smart contracts.

In addition, LBT tokens are not limited to use only on the ecosystem platform. After the platform is launched, LBT tokens will be available for purchase/sale on cryptocurrency exchanges.

Terms and conditions for the sale of tokens: a total of LBT 100 million will be available, where 1 LBT = mLBt 1 million.

Of the total number of tokens:

5% will be for sale during the pre-ICO 70% will be available for sale during the ICO 15% will go to the system’s insurance fund 5% will go to the founders 3% will go to the bounty programme 2% will be distributed among team members

Funds received through the pre-ICO will be distributed as follows:

30% for development of the app 50% for ICO preparations 20% on salaries and the bounty programme

If the soft cap is exceeded during the pre-ICO, the remaining part will be distributed as follows: up to USD 300,000 will be spent on hiring the main consulting partner for the ICO (tentatively Deloitte) and a legal advisor; the marketing budget will be increased from USD 100,000 to USD 700,000; up to USD 150,000 for hiring additional employees (for one year) to reduce the time needed for development and to improve reliability: IT specialists, risk analysts, office managers in other countries; up to USD 100,000 on user involvement and positioning: marketing and PR; and up to USD 100,000 for unforeseen expenses. In total, the hard cap is set at USD 1.5 million.

Funds received through the ICO will be distributed as follows:

70% for project development 20% for the insurance fund 10% for the team, the founders and participants in the bounty programme

Token functions

Utility token, which will be used as follows

As a reward for the successful repayment of a loan through the app

As a risk insurance tool for investors: in case of default, part of the amount is repaid in tokens that can be sold on the exchange

As a tool for lending to other users

As payment for a PRO subscription, which includes advanced features in the app

As payment for services: guarantees on the part of borrowers, legal support, debt collection services

Tokens for the functioning of the blockchain-based global credit rating (fuel)—access to a credit history by third parties (financial companies, banks, mutilateral lenders, etc.) with the consent of the borrower.

The holders of LBT tokens gain access to a unique circle of trustworthy investors and borrowers, whose rating has been confirmed by numerous successful transactions, information about which is recorded in a blockchain in the form of a rating.

The price of a token will depend on the stage of the ICO:

Stage Tokens available, %

Tokens, LBT Maximum amount, USD

Maximum amount, ETH*

1 LBT in ETH*

1 LBT, USD

Discount

Pre-ICO

Presale 0.86% 860,000 214,286 428.57 0.0005 0.25 50%

Week 1 0.78% 780,000 214,286 428.57 0.00055 0.27 45%

Week 2 0.74% 740,000 214,286 428.57 0.00058 0.29 42%

Week 3 0.70% 700,000 214,286 428.57 0.00061 0.31 39%

Week 4 0.67% 670,000 214,286 428.57 0.00064 0.32 36%

Week 5 0.64% 640,000 214,286 428.57 0.00067 0.33 33%

Week 6 0.61% 610,000 214,286 428.57 0.00070 0.35 30%

ICO

Period 1 27% 27,000,000 10,000,000 20,000 0.0007 0.37 26%

Period 2 23% 23,000,000 10,000,000 20,000 0.0009 0.43 14%

Period 3 20% 20,000,000 10,000,000 20,000 0.0010 0.50

*The Ethereum rate is fixed at the level of USD 500.

Depending on the stage of the ICO, the price for one LBT token will vary from 0.0005 to 0.0010 Ethereum (the only currency with which you can buy LBT tokens). All unsold tokens will be destroyed.

The LBT token code specifies that if the soft cap is not met (the minimum at the pre-ICO stage and later at the ICO stage), then at the end of the sales period, the Ethereum tokens will be automatically returned to the digital wallets that they originally came from.

If an application is submitted at the pre-sale stage (before the pre-ICO), investors will get the maximum benefit from the token discount offered, which, at that stage, will be up to 50% off the price at which tokens will be traded at the final stage of the ICO.

Dividends will not be paid out on LBT tokens.

We recognise that to develop the ecosystem, we will have to allocate a sufficient supply of tokens for incentivisation (the bounty programme).

Pre-ICO bonus programme (% of the bounty pool):

Channels: % of the bounty pool

Equivalent in tokens Bonus in LBT

Facebook 10% 90,000 30

Telegram 10% 90,000 30

Bitcointalk Signatures 10% 90,000 30

Bitcointalk Support 20% 180,000 30

Media 15% 135,000 30

Instagram 5% 45,000 30

YouTube 10% 90,000 30

Medium 5% 45,000 30

In different countries 5% 45,000 30

Active members 10% 90,000 30-2,000

TOTAL: 900,000

After the ICO, we plan to place LBT tokens on the following major cryptocurrency exchanges in order to simplify, in the long term, the use of the tokens in the ecosystem and to convert them into other cryptocurrencies and fiat currencies/assets:

Bittrex: one of the main features of the Bittrex trading platform is the ability to work with a large number of virtual currencies. The list includes 200 trading instruments, including well-known cryptocurrencies, as well as little-known currencies that are not used by our competitors. This opens up a wide range of opportunities for trading LBT tokens

Openledger: the OpenLedger trading platform includes advertising technologies (HubDSP), OBITS tokens and the ICOO crowdfunding system, which make up the entire ecosystem. You can trade cryptocurrencies, smartcoins, assets, shares and fiat currencies, which directly enhances the ease of use of the tokens used in the Lendsbay ecosystem that we are developing.

Poloniex is one of the largest cryptocurrency exchanges in the world. It offers no fewer than 50 currency combinations. The exchange was launched relatively recently, in 2014, but it is already considered one of the best. Every day, hundreds of thousands of trades take place there, and millions of users visit the site on a regular basis. Nearly USD 1 billion is traded on a daily basis.

It is in demand among Russian-speaking users. Poloniex is among the top three most popular platforms, along with Bittrex. Some of the exchange's features make it easy for beginners—not to mention experienced traders—to use.

9. Legal regulations

At present, more and more technical solutions are becoming digitised. The laws in most developed countries recognise contracts concluded in electronic form as if they were concluded in written form.

According to the laws of Great Britain and Russia, documents signed by an electronic digital signature by both parties in the app will be accepted as evidence in court if one of the parties fails to fulfill its obligations to repay a loan.

Document flow between users of the platform will be carried out electronically and recorded in the blockchain. Countries in which courts do not accept electronic contracts will be connected to the platform without the functionality of documenting loans.

Examples of the electronic contracts that will be used in the system include:

Loan agreements and the prolongation/renewal thereof

Bank guarantees

Insurance

Securitisation and release from pledge

Claims and collective actions

Amicable settlements

Assignment of receivables as security

Contracts with a debt collector

In the future, as the judicial authorities develop in various countries, we will have the opportunity to file claims directly from the app.

Legal status of tokens:

Buyers of tokens are not investors, and tokens are not an investment

Lendsbay tokens are utility tokens for the app

Buying a token is buying a licence to access the software and data

The more tokens, the greater the access privileges

Tokens will be sold on the basis of an offer

The owners of tokens will not be restricted in terms of reselling their tokens to others

There will be restrictions on participation in a token sale for US and Chinese citizens

A token is not a security or an investment according to the Howey Test:

○ Tokens are purchased in exchange for money or an equivalent thereof

○ The organisers of a token sale are a group of persons united in one enterprise

○ Tokens do not satisfy the third point of the Howey Test (with a reasonable expectation of

profits derived solely or predominantly from the efforts of others), in so far as:

There are no plans to pay out dividends to the holders of tokens

Tokens are not bonds; the issuer will not pay token holders a regular percentage on

loans

To make profit from owning a token, it will be necessary to make an effort: using the

software and carrying out transactions on the platform

When tokens go on sale, the first version of the software product will be ready

User identification

In both automatic and manual modes, the system will enable the remote identification of users (using external databases), which will make it possible to verify their identity.

The following verification methods will be used:

An SMS code to confirm their phone number

An e-mail code

In the event that the bay function is used, an e-mail code will be sent to their work e-mail account in order to confirm that they are employed by a particular organisation

Payment card details (its validity)

Information contained in an identification document, as well as a photo of the user with this document, including information on registration of their permanent address

GPS/GSM identification of the user's location, which will be correlated with the information entered by the user

Code word (for the purpose of data recovery if their mobile phone is lost)

Facial ID

Fingerprints

PIN

Personal data security

Partial access to the information in the app and in the blockchain will only be available to registered participants; this may be all the participants or only those who need a specific piece of information. Partial access to information means information in a generic form that is necessary for lending to a particular user. Complete access to information will be available only to authorised participants (organisations) who undergo a verification process on the platform and to whom the user provides access keys. Complete access is understood as arrays of statistical data that users can use to build their own ratings models. Restricting access to personal data ensures the right balance of confidentiality and transparency.

10. Roadmap

2016–2017

Creating a local prototype

Market research

Building a financial model

Using contractors to create a web prototype

Conducting surveys of the target audience

Usability testing based on the web prototype

Developing both the back end and front end of the app

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

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

Token conversion

Implementing the social ratings system (proximity rating)

Implementing the behavioural ratings system

Creating an API

Entering the markets of developing countries

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

11. Lendsbay Team

The team has extensive experience in banking in such areas as investment business, retail risks, corporate finance and derivatives. In particular, in the area of risk, team members have successfully managed retail risks at leading Russian banks and have an understanding of how to build effective scoring/ratings models for assessing the creditworthiness of borrowers and how they can be improved.

The IT division of the team is engaged in the development of complex high-load production software solutions on various scales, including using blockchain technologies for distributed storage of information.

ALEXANDER KOPTELOV

Founder, CEO

Graduated from the Department of Computational Mathematics and

Cybernetics at Lomonosov Moscow State University, Master's in Finance from the

New Economic School in Moscow. Banking experience includes seven-plus

years in market risk, three-plus years in IT and four-plus years in corporate finance at Zerich Bank, Alfa Bank and Raiffeisen

Bank. Associate Director of Sberbank CIB.

ANTON GAZIZOV

Founder, International Development/IR

Graduated from Cambridge University with a degree in Economics. Has extensive

experience in corporate finance at a number of major global banks and

investment companies, such as Goldman Sachs, Rothschild Investment Corporation, Deutsche Bank and VTB Capital. Managing

Director of Sberbank CIB.

ANDREY CHEREMKHIN

Founder, COO

Graduated from the Law Faculty at the Moscow State Pedagogical University with a degree in Civil Law. More than 10 years'

experience in the legal profession, including in the fields of intellectual

property and IT, extensive judicial practice in courts of various instances.

Entrepreneur.

LYUDMILA LUKASHOVA

Founder, CRO

Graduated from the Faculty of

Mathematical Methods in Economics at the Financial University under the

Government of the Russian Federation. More than 10 years' experience in retail

risk at top-three Russian banks, Chief Risk Manager

VLADIMIR GORBUNOV

Head of IT

Graduated from Russia's National

University of Science and Technology (MISiS). More than 10 years’ experience in IT/programming and designing online and offline systems and applications. Three-

plus years' experience in programming for iOS/Android. Extensive experience with

Big Data and blockchain technology. Technical Director of a

developer/integrator company.

DARIA BATAMIROVA

Marketing Strategy

Graduated from the British School of

Design with a degree in Graphic Design and from the State University of

Management with a degree in Sociology and Psychology. Over 13 years'

experience in marketing communications and branding for the agencies JWT, BBDO,

Y & R, LEO Burnet, DDB, DRAFTFCBADV and with international clients. Director of Marketing and Communications at Sova

Capital Limited.

MURAT YENIKEYEV

Risk Adviser

Graduated from the Department of

Mechanics and Mathematics at Lomonosov Moscow State University,

Master's in Finance from the New Economic School in Moscow. Spent two years working for a top-three telecoms

operator and has eight-plus years' experience in the field of retail risk. Head

of the Retail Risk Analysis in top-ten Russian Bank.

KRISTINA SHILOVA

SMM

Graduated from the St Petersburg State University of Film and Television with a degree in Audiovisual Engineering. Also

studied Marketing and PR. Five-plus years' experience in online marketing. A Google

AdWords and Yandex.Direct certified specialist. Extensive experience with SMM

and targeted advertising.

ANGELICA PHILLIPS

Partner in the UK

Prior to co-founding ANDN Consulting, was a partner at Norton Rose Fulbright

Corporate Finance Department, London, and spearheaded Norton Rose Fulbright’s CIS practice. Vast experience in advising on emerging markets transactions, CIS

and CEE.

ANDREY LUKASHEVICH Adviser

Graduated from the Department of

Computational Mathematics and Cybernetics at Lomonosov Moscow State

University, MBA at INSEAD Business School. Worked as a partner at Kei-Ei

Consulting, Ward Howell International and as an M&A consultant at PwC.

2015-2018 COO, CEO Delivery Club (the largest food delivery service, presented in 97 cities of Russia). Currently CEO of the

investment division Mail.ru Foodtech Ventures.

ALEXEY KHALIULLIN

Adviser

Graduated from the Cambridge University with a Master degree in Economics. Alexei

worked at Deutsche Bank and Morgan Stanley in London, in a PE fund Alfa

Capital Partners in Moscow. From 2005 to 2010 was the CFO of a premium fitness club chain "World Class". From 2010 to

2015 built a successful consumer business. Since 2015-consultant and

project leader at The Boston Consulting Group, specializing in operations

efficiency in a wide range of industries, as well as government innovation policy.

EVGENY KAPLIN

Adviser

CEO Modultrade. 17+ years in International Trade and Banking business

with Strategic consulting experience. Successfully launched and ran a global

trade finance platform in one of the top Europe bank. McKinsey, Sberbank, Cargill,

Gazprom.

The market research conducted regarding the need for such a product and team members' extensive experience in the banking sector have contributed to the successful implementation of the Lendsbay project.

12. Protection for buyers of tokens

The team and the Lendsbay project are doing everything possible to ensure that the project is as transparent and safe as possible for buyers of tokens right from the start of the project.

The open token code available on github shows that if the soft cap is not reached during the pre-ICO, all funds (without the possibility of intervention on the part of the Lendsbay team) will automatically be returned to the wallets from which the money was transferred. In order for this to be possible, tokens may only be purchased in Ethereum, since purchases made with other currencies do not allow for automatic refunds. Providing a refund eliminates the risk the portion of funds collected will be insufficient for the operation of the product (most projects do not provide for automatic refunds).

The availability of the tested alpha version of the product and the release of the beta version prior to the completion of the ICO shows the result of the project and provides an opportunity to test the product before the end of the ICO (at the time of the ICO, less than 7% had even a prototype of their app).

Members of the Lendsbay team are graduates of top Russian and international universities such as Cambridge, Lomonosov Moscow State University, the New Economic School, the Financial Academy under the Government of the Russian Federation and others. The Lendsbay team has considerable experience in the banking industry, largely in credit and retail products, at major Russian and international banks such as Goldman Sachs, Deutsche Bank, Raiffeisen Bank, Home Credit, Sberbank, VTB, Alfabank and others (many start-ups are being established by teams in industries that are new to them).

In order to secure the funds collected during the preliminary sale and sale of LBT tokens, all funds converted on the Ethereum platform are stored in a multisignature wallet. A multisignature wallet is a wallet that requires a large number of people to confirm the release or transfer of funds. The project will gain access to the funds in the wallet only after the completion of the pre-ICO.

13. Conclusion - Disclamer

The goal of the project is not to get more profit from interested parties but to build more transparent and easy-to-understand relations between individuals in the informal lending market.

We want to offer people a more convenient way of interacting in the informal sphere with convenient access to credit instruments as part of their basic rights guaranteed by the country in which they live and thereby improve their quality of life. Although the clients of multilateral lenders are not the main target audience of the project, many good people with small incomes will be able to borrow funds not at excessive rates of 1-2% daily, but at interest rates close to those of banks, i.e., 10-30% per year.

We offer a solution that will allow multilateral lenders, banks and insurance companies to access large amounts of data so as to better understand the market, which means it will enable customers to get cheaper, faster, better-quality and, above all, individual financing without compromising their confidentiality.

Nearly 2 billion adults all around the world currently use lending services in the informal market, and they can all enjoy the benefits of using the Lendsbay platform.

OUR MISSION is to develop a society based on pooled financial resources and mutual trust