The cryptocurrency market and trust:a new approach to project evaluation

Context

Let's say you need to open a bank account. Most likely, you will make a list of banks in advance and then choose the appropriate one. This list will probably not be random: it will include those banks that have important licenses from the responsible regulator or those that were recommended to you personally. There may be many selection criteria, but all of them will determine the degree of your trust in banks. This will help you decide if you can trust this bank. Each of us has our own set of products and services that we trust. Why is trust so critical? When and what should you pay attention to?

Sociologists and economists conclude that trust reduces transaction costs: simplifies interaction between market participants, allowing you to quickly achieve the desired goal [1, 2]. The costs in question arise in conditions of increased uncertainty: in the process of searching and processing information, when selecting reliable partnerships, and so on. Indeed, if we want to perform any economic action (purchase, investment, or loan), we need to solve several non-obvious problems. Furthermore, this only applies to the micro level (that of a particular user). Macroeconomically speaking, what is the relationship between trust and economic expansion? Empirical studies of this issue indicate both the presence of a positive correlation (under certain conditions) and the fact that trust is a predictor of economic growth [3, 4, 5]. 

Sociology and economics describe society as a system of institutions. The concept of institutions, in a broad sense, means any established pattern of behavior in society. Institutions can be formal (for example, schools, governments, or commercial companies) or informal (for example, subcultures and families).

In this sense, the crypto community is an informal institution with its own unspoken rules, values, and guidelines, and trust becomes a key condition for decision-making. The sphere of regulation is frequently referred to as the institution of formal rules, in contrast to the institution of trust, due to its foundation on inviolable statutes, regulations, and laws. 

At the same time, regulation is not the best alternative to trust due to the additional costs that arise with enforcement proceedings, sanction restrictions, and regulatory control in general. Lobbying and corruption are just two examples of the factors that undermine the legitimacy of regulations. Not only does this influence reduce the overall productivity of the market participants’ economic actions, but it also decreases trust in the institutions and rules developed in society.

Crypto market development: crisis of confidence and new demand

Some researchers say that the drop in trust in the institutions of the traditional market is exactly what caused the cryptocurrency market to become so popular at first. [6, 7]. A completely new market has begun to materialize on the principle of decentralization. As it developed and expanded, new formats for interaction between users and businesses appeared: DAO (MakerDAO, etc.), LDAO (Aragon One, etc.), Community-based/oriented projects (Bitcoin, DeFi, etc.), parachain projects (PolkaDot, etc.), protocols, and other types of projects that did not exist before. The main features of these new forms of business organizations arise from the very idea of decentralization: transparency, verifiability of information, and the possibility of direct communication between market participants. In the new market, the role of trust increases, as does the value of trust itself. In other words, market participants submit a request for mutual trust [8, 9].

Existing approaches to measuring trust

What methods are available for verifying market projects? They can be divided into 3 groups: traditional audits/scoring, review services, and blockchain/Web3 on-chain scoring.

A large group of traditional analytical models of audits/scoring includes such business scoring as Startup Genome, Pitchbook, CB Insights. They are often systematic and detailed but focus on financial performance or legal information. Such scoring does not take into account key aspects like interaction with users, transparency of communication, and accessibility of information. The shortcomings described make these rating models incomplete and very indirect for reliably measuring audience trust.

Review platforms such as TrustPilot, SiteJabber do not always have data on the Web3/Blockchain market. The major drawback of these services lies in the data itself; it is not standardized and may contain unreliable ratings (for example, purchased reviews, etc.). All this makes it impossible to obtain a valid quantitative assessment of trust, not to mention a comparative analysis of such assessments.

Web3 scoring (such as Rocifi, Reputex, Credprotocol, SpectralFinance) that have appeared on the cryptocurrency market recently use on-chain data as the main source of information. This approach to project analysis is intriguing from the perspective of the tools utilized; however, the authors fail to reveal the correlation between audience trust and completed transactions, specifically the flow of funds.  The completion of transactions and the movement of funds can be associated with many reasons, not only the trust factor. Furthermore, the subjective evaluation of the project by individual users is disregarded.

Measurement quality: validity and reliability

None of the modern approaches allows us to validly and reliably assess the potential level of audience trust in projects. What role do validity and reliability requirements play?

Validity ensures that a tool meets its purpose. As an example, imagine a medical test to determine an infection. If this test is truly valid, it should correctly determine whether a person has an infection. If a person has an infection, the test should show a positive result (true positive). Whether the person does not have an infection, the test must show a negative result (true negative).

Reliability measures stability and comparability. Imagine a scale measuring your weight. If you step on this scale several times and get approximately the same result each time, then this scale is considered reliable. Reliable measurement produces consistent results every time you measure. If your scale showed a different result every time you weighed the same item, it wouldn't be reliable.
These requirements provide confidence in the measurements. This way, we can make informed judgments and conclusions based on the data. A trust index, known as the BDC Trust Index, was integrated into the framework of this methodology. To develop an effective methodology, we explored a number of questions. What factors should be considered? To what degree is the trust framework consistent and universally applicable to all participants in the market? The Crypto Trust Rating researches this phase.

Crypto Trust Rating

The CTR study examines and explains how regular users trust various market players in the cryptocurrency space. The final model consists of four key factors:

• previous experience with the project;
• transparency of communication between the audience and the project team;
• competence of the project and team;
• predictability and stability of project development.

As part of the study, a series of interviews and a quantitative survey were conducted with 2,000 cryptocurrency market participants (global sample).

1. Classification of crypto market participants

Data analysis showed the absence of a single configuration of trust for all market participants [10]. Different methods are employed to establish trust in market participants.

For example:

The determining factors for cryptocurrency exchanges are user prior experience, the project's and team's expertise, and the openness of the project's communication with the target audience. For many users, cryptocurrency exchanges are one of the very first channels of interaction with the cryptocurrency market, so exchanges are interested in investing in trust in both cryptocurrencies and their brands. As an example, we will reinforce the image of the exchange as a “crypto guide” through education platforms (KucoinLearn,  Binance Academy, etc.).

The primary determinants of trust in cryptocurrency media are the consistency of content and the transparency of communication between the project team and the audience (for instance, an analytical agency's content consists of analyses of events rather than news articles and reports). This is consistent with the fact that the audience prefers to select information sources based on consistency with their views [11, 12, 13].

Which channels are most effective for disseminating project information and establishing confidence in the endeavor? What are the specifics of user interaction with each of the information channels? These questions served as the starting point for subsequent research and development of the BDC Trust Index methodology.

BDC Trust Index: research

The user builds trust by looking into the project. Thus, the key step in building trust in the project is studying information about it, and the main criteria are the availability of any information about the project and its content.

The focus of this study is the mechanism for studying and evaluating projects by users. We were interested in how any piece of information about the project is read, including materials directly from the project (like the website, documentation, etc.) and other materials about the project (like news stories that talk about it or different groups' opinions on it).

To do this, we selected six crypto projects within one area (tooling projects - tools and software that simplify and improve interaction with blockchain technology and decentralized applications) and prepared examples of project representations in the form of interactive images. Thus, each respondent was asked to rate each information element of the project.

2. The mechanism for assessing the information element by the respondent; information element: social networks of the project’s C-lvl 

If we assume that trust is formed through the user's analysis of information, there is a risk that large projects may be systematically perceived more positively than lesser-known projects because their information trail is more visible. To account for this effect in our measurements, we incorporated a measure of awareness into the questionnaires themselves and selected three high-tier and three low-tier projects from Web3 market open data on fundraising. Each respondent received a project to evaluate in random order; the final sample included about 70 respondents for each project assessed (619 participants in total).

We randomly changed the sequence of information blocks to prevent the possible influence of the question order.

As a result of the data analysis, we determined the importance of the following information blocks for the audience of cryptocurrency users:

• opinions about the project (users, opinion leaders, acquaintances);
• information about the project team and management
• presentation of the project’s information (content on the website and in search results, etc.).

Proper development of only these components for tooling projects can provide 71% confidence in the project.

The most important blocks turned out to be associated with active external communication (reputation, team, image). This confirms the social nature of trust in such an innovative and technological sphere as the cryptocurrency market.

To determine the content of information blocks, we conducted a series of interviews with end users of tooling projects and with niche experts for each information block. As a result, we were able to establish meaningful quality criteria for each block (for example, the presence of described Use cases on the project’s website, reviews by opinion leaders, Tier-1 media mentions, etc.). Thus, we received the necessary information to develop a project evaluation methodology.

BDC Trust Index: project evaluation methodology

Standardized assessment is based on observable metrics. Therefore, we operationalized each criterion so that it was ultimately defined based on external observable data.

End users noted in interviews that the fact of investment/use of the project by friends is an important indicator of trust. Thus, the connectedness metric of project users may be a relevant criterion. How can this be recorded?

We proceed from the following hypotheses [14, 15, 16, 17]:

1. Acquaintance between two users is equivalent to mutual subscription on social networks;
2. Community subscribers (for example, on Twitter, Discord, Telegram) are equivalent to users;
3. Subscribing to any project’s network is a signal of continued trust in the project; otherwise, the user unsubscribes;
4. We can assume that a user's acquaintances hold a favorable opinion of the project if they are both subscribed users and members of the project's subscriber network.

As a result, we need to record the metric of connectivity between project users without taking into account the unifying factor, subscription to the project. This corresponds to the density metric of a social network/subscriber graph (SNA, density [18]). The density metric must be assessed in context, which is why a project's community density metric is compared with the median for projects in the same category. If the density of connections is above the median for this category of projects, “friends’ opinion on the project” can be assessed as positive. 

Each metric was subsequently described in a rule codifier format. Thus, each project that is assessed is checked against the rules of the codifier.

Evaluation procedure

The codifier is designed to conduct expert assessments of projects, regardless of the user-evaluator. Each rule has its own rating scale, appropriate to the context. This rating system runs from 0 to 1 point (for example, the presence or absence of a specific section on the site), from 0 to 5 points (a mention of a project of a given Tier in the media), and so on. Expert assessment is the ratio of actual scores to maximum scores; scores on different scales are balanced against each other and brought to a common form (%).

The assessment model is based on two components: the user importance of elements and an expert description of the content of the elements. The final score is the sum of the criteria scores, normalized by the importance of each criterion:
 

The final score is a numeric value ranging from 0 to 100, with a score of 100 indicating complete trust (end-user confidence). This assessment, in turn, places the project in one of four confidence categories (from low to absolute). The model provides/takes into account the measurement of the potential level of trust for different target audiences. Consequently, the importance coefficient will undergo modification, enabling a more focused examination of the project as perceived by the audience with the highest priority. 

Evaluation result

The assessment will provide the project with a detailed description of the potential perception of the current information field surrounding it, as well as recommendations for its improvement.  Such an assessment may be useful for various groups of market participants.

For developers and project team:

• Scoring will identify weaknesses and provide recommendations for improvement.
• The assessment encourages the team to follow best practices in project development and management.
• A high score can draw the attention of qualified developers and experts, allowing the team to grow and the project to progress.

For investment funds:

• Standardized scoring will enable faster and more accurate evaluation of potential crypto projects, increasing the efficiency of decision-making and reducing risks.
• By employing scoring, we will be able to incorporate a trust parameter into the evaluation of a project's investment appeal.

For launchpads:

• By utilizing a scoring methodology, it will be possible to ascertain which projects are the most appropriate and dependable to feature on the platform, thereby increasing the confidence of participants and attracting high-quality projects.
• Evaluating projects on the launchpad can reduce investment risks as investors will have more confidence in their project selection.

For exchanges:

• Exchanges will be able to more carefully select projects for listing on their platform thanks to scoring. This will ensure that the exchange's listing maintains a high level of quality and dependability.
• If projects with a high level of trust are uploaded on the platform, the exchange's reputation will increase, and it will attract more traders and investors.

For ecosystems and protocols:

• Scoring will enable platforms to ascertain which initiatives are reliable in the eyes of users. A robust and cohesive community of projects that enjoy a high level of audience trust can be an attractive factor when it comes to ecosystem integration.
• Hosting projects that have obtained a high trust score can facilitate the expansion and acceleration of a protocol or ecosystem's adoption due to the increased confidence that users will have in its dependability.

For regulators:

• The scoring methodology can become a starting point for regulation in the crypto space, since it takes into account many factors that determine the reliability of projects.
• Regulators can use scoring data to more effectively monitor and identify potentially problematic projects in their early stages.

For educational organizations, analytical and expert communities:

• The scoring methodology combines extensive databases of trust criteria and audience characteristics to conduct research and analysis in the cryptocurrency and blockchain fields.
• Industry experts can monitor the efficacy of their work and pinpoint additional areas of focus for themselves or their clients by using the scoring methodology.

For end users of cryptocurrencies and retail investors:

• Scoring can help the user more accurately assess project risks.
• The extensive range of parameters included in the scoring model makes it easier to study various projects

Prospects and project roadmap

The BDC team is interested in developing the project and improving the assessment methodology. We have identified several areas that we plan to work on over the next year:

• Verification of trust criteria and conducting additional audience surveys;
• Assessment of the relationship between trust and project performance on the market;
• Development of the assessment user interface;
• Implementation of productive AI solutions for parameter assessment;
• Direct evaluation of various projects;
• User audience research.

A truly effective valuation methodology must apply to projects in any phase of the market. To do this, we need to ensure the relevance of the selected criteria and their periodic verification. The user audience is also capable of changing as cryptocurrencies and blockchain-oriented projects become more widespread. To measure user trends and examine end-user market development potential, we need to conduct audience characteristics research regularly.

Conclusion

With the assessment database, we can study the correlation between market success and trust indicators over time, as well as the relationship between various trust characteristics and project market dynamics. This system will improve the reliability of the BDC Trust Index as well as assess the methodology's forecasting potential.

The BDC Trust Index is primarily a project assessment tool. In this regard, most of the work will be devoted to project assessment sessions for user trust. In this manner, we will be able to fine-tune the process using real-world cases, as well as build a database for future verifications. The more we learn about the market and our target demographic, the more tools we have to precisely characterize it and access data that was previously unavailable. If you are interested in getting involved in this or another project, we would love to chat with you.

Sincerely yours,

BDC Consulting