Approach Paper
Introduction
BetygFi is an Information Utility (emphasis supplied) that democratizes access to information within the blockchain ecosystem. This paper explores the challenges posed by bad actors in the blockchain space, the evolving regulatory landscape, and BetygFi's innovative approach to addressing these issues.
Real-Time Access to
Financial Data
Blockchain, as a technology, is unique; it makes information available real time. Notwithstanding public perception of blockchain as a technology, real time access to financial data without a gatekeeper is unprecedented. Despite real time availability of financial data, the process of accessing data is technically challenging and understanding on chain data is difficult. Bad actors have leveraged this information asymmetry, hence actors using blockchain have become synonymous with malicious conduct.[1]
Retail investors and the community have lost huge amounts of capital because of these bad actors.
Regulatory Landscape
The blockchain ecosystem has evolved into a dynamic and complex market segment, with a myriad of actors and constituents interwoven in intricate relationships. As regulatory oversight becomes paramount, it is imperative to employ advanced ML/AI solutions to assess and monitor systemic risk embedded within this ecosystem effectively.
Trust in the ecosystem has been the biggest casualty.
Regulators globally, having taken note of repeated malicious conduct by actors, have started closely scrutinizing activity on the blockchain.
IMF-FSB Synthesis Paper
The recent “IMF-FSB Synthesis Paper: Policies for Crypto Assets” is a consequence of the collaborative effort between the International Monetary Fund (IMF) and the Financial Stability Board (FSB), considering the serious concern by regulators globally in the backdrop of the growing prominence of crypto assets in the global economy.
Regulators globally have recognized that crypto as an asset class poses significant macroeconomic and financial stability risk.
It has the potential to undermine monetary policy and become a systemic threat to economies.
The IMF-FSB Synthesis Paper therefore emphasizes the need for a comprehensive regulatory response and seeks global co ordination to enable the same. It highlights concerns such as undermining monetary policy, fiscal risks, and the potential for systemic threats. The document emphasizes the need for a comprehensive regulatory response, advocating for strengthened monetary policy frameworks, clear tax treatments, and robust supervisory oversight.[2]
Notwithstanding the negative sentiment as recognized by the IMF-FSB paper, it is hard to ignore the unprecedented benefits of blockchain. Regulators globally whilst discouraging the traditional idea of cryptocurrency, have started exploring use cases premised on blockchain viz. CBDCs and are feverishly working towards developing mechanisms to better understand and regulate digital assets that utilize blockchain as an underlying infrastructure.
BetygFi's Foundational Thesis
BetygFi's foundational thesis is that sunlight is the best disinfectant, it provides actionable intelligence on the blockchain ecosystem. It leverages proprietary ML modelling and AI to provide actionable intelligence to stakeholders viz. regulators and the community globally.
BetygFi has built an approach that leverages its model to enable the foundational premise of the IMF-FSB paper which is the principle of “same activity, same risk, same regulation ”.
Simplifying On-Chain Data
Our approach endeavors to simplify on chain data, it enables stakeholders to better understand actors that inhabit the blockchain paradigm and take decision accordingly. We present a comprehensive analysis of the systemic risk within the blockchain paradigm, leveraging a proprietary Machine Learning (ML) model that operates on real-time on chain data (emphasis supplied).
The model provides relative health and growth scoring of actors and constituents within the ecosystem viz. it attributes real time dynamic score to Decentralized Financial Organizations (DeFis), Coins/Tokens and Wallets and further establishes relationship modeling to highlight real time systemic risk.[3]
Stack
At the core of BetygFi is a stack developed by Solvendo. The stack leverages lessons from the decentralized financial ecosystem and the traditional financial ecosystem and utilizes foundational models to solve the fundamental problem that plagues all financial ecosystems information asymmetry.
Community
Our machine learning model constantly revisits its output and score though a learning loop. It is our endeavour to build the most accurate, efficient and democratic model over time. As part of our endeavour to ensure that our model is democratic, it is designed to constantly learn from the community
We have devoted significant thought, time and effort to build a square where the community engages with each other and BetygFi, to enable us to learn from the community and reassess the machine learning model.
Our ability to learn from the community is underpinned by technology that enables BetygFi to distinguish between signal and noise.
We hope to create community space, where the community has access to real time credible data and actionable intelligence; and hope to incentivise the community to provide feedback, necessary to democratise finance, through gamification.
Highlights of BetygFi's Machine Learning model:
ML Model for Real-Time Analysis:
Our proprietary ML model processes real time on chain data to calculate risk scores for entities that leverage the blockchain ecosystem. These scores are derived from a comprehensive set of metrics both financial and non financial, including transaction volume, volatility, smart contract activity and network participation.
Relationship Graphs:
The model constructs relationship graphs to illustrate the interdependencies among various modules within the ecosystem. This processing aids in understanding the systemic implications of disruptions or anomalies in specific entities or sectors and their correlations.
Risk Score
The Risk score provides valuable insights into the stability and potential trajectory of individual actors and constituents. Entities with consistently high scores demonstrate robustness and positive growth potential, while those with declining scores may warrant further scrutiny
Systemic Risk Indicators
The model identifies key systemic risk indicators, including high concentration of influence, excessive dependence on specific entities, and anomalies in transaction patterns. These indicators serve as early warning signals for potential systemic vulnerabilities.
Open Access Data Platform (Data Studio)
The Data Studio is designed to democratize data access and reduce information symmetry on account of lack of data access. It allows proficient users to leverage BetygFi data repository to enable them to build applications, solutions and/or bespoke analysis. The Data Studio will in time make data, technological tools and machine learning capabilities available to users.
Community and Feedback based Learning
The community space enables the community to access real time credible data and actionable intelligence. We hope to incentivise the community to actively participate and provide feedback on our machine learning efforts, necessary to democratise finance.
Insights generated from the community are integrated into the model, enabling it to adapt and refine its risk assessment capabilities over time. This iterative process ensures that the model remains responsive to evolving market dynamics and is democratic.
We are working towards gamifying community participation to incentivise community to actively participate with BetygFi.
References
[1] It is our approach to identify the problem and solve for it agnostic of intent; for the consequences of actions notwithstanding intent are the same. It is debatable and the subject matter of judicial review as to whether actors that inhabit the crypto and blockchain space acted out of malice, negligence or both. It is however not a matter of debate that their actions had serious consequences on retail investors and the community.
“Never attribute to malice what can be sufficiently explained by ignorance”
[2] Please see the IMF-FSB Synthesis Paper: https://www.fsb.org/wp-content/uploads/R070923-1.pdf
[3] Coin typically refers to a unit of digital currency. It's like the money you use in your wallet, but it exists in electronic form on the blockchain.
A token is a digital asset that can represent a variety of assets or values. Tokens can be like certificates that represent ownership of something or the right to access certain services within a specific blockchain ecosystem.
A digital wallet in blockchain is like a digital pocket that helps you store and manage your online coin/token.