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What is Lorenzo Protocol (BANK)
Learned by 89.5k usersPublished on 2024.04.01Last updated on 2026.06.02
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注意：项目简介来自于官方项目团队所发布或提供的信息资料，可能存在过时、错误或遗漏，相关内容仅供参考且不构成投资建议，HTX不会承担任何依赖这些信息而产生的直接或间接损失。
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I. Project Introduction
1. What Is the Lorenzo Protocol?
Lorenzo Protocol is a modular Bitcoin Layer 2 infrastructure built on Babylon, designed to unlock BTC liquidity and integrate it into the DeFi ecosystem. The protocol enables users to earn yield by staking Bitcoin in exchange for yield-bearing tokens such as stBTC and enzoBTC. These tokens can be traded or used to generate additional yield on DeFi platforms. Lorenzo enhances Bitcoin's scalability, enables smart contracts, and provides Layer 2-as-a-service infrastructure by integrating Babylon's staking and timestamping protocols along with Chainlink services. The protocol aims to offer BTC holders an efficient and secure framework for staking and yield management.
2. How Does Lorenzo Protocol Work?
The core components of the Lorenzo Protocol include:
stBTC: A liquid staking token that allows users to stake BTC and earn yield through Babylon's restaking mechanism.
enzoBTC: A decentralized BTC wrapping token that can be used for trading and yield generation on DeFi platforms.
Lorenzo OFT Vaults: Vaults created for trading strategies, supporting asset management, and yield distribution.
These components allow Lorenzo Protocol to unlock BTC liquidity and integrate it with DeFi, increasing Bitcoin's use in decentralized finance.
3. Who Founded Lorenzo Protocol?
The core team of Lorenzo Protocol includes:
Matt Ye: Co-founder and CEO, previously a Trading Engineer at Two Sigma.
Fan Sang: Co-founder and CTO, holds a Ph.D. in Computer Science from Georgia Institute of Technology and has held key roles in multiple technology projects.
Toby Yu: Co-founder and CFO, with extensive experience in finance and blockchain projects.
Tad Tobar: Chief Operating Officer, formerly Head of Operations at ZetaChain, possessing considerable experience in blockchain project management.
Publicly available data indicates that the Lorenzo Protocol has garnered support from entities such as NGC Ventures, MH Ventures, ABCDE Capital, YZI Labs, and 300DAO. The amount of funding secured from these supporters has not been publicly disclosed. Furthermore, Lorenzo Protocol held an IDO public offering on Binance Wallet, which ended on April 18, 2025, and generated approximately $200,000 in funds.
4. Lorenzo Protocol Tokenomics
The total supply of BANK tokens is 2.1 billion, distributed as follows:
Liquidity: 4%
Rewards: 25%
Investors: 25%
Ecosystem & Development: 13%
Team: 15%
Treasury: 5%
Advisors: 5%
Binance Wallet IDO: 2%
Marketing: 3%
Listing: 3%
As of now, the circulating supply is 425.25 million tokens, representing 20.3% of the total supply.
5. Timeline of Key Milestones
May 27 - June 10, 2024: IDO on Particle Launchpad.
April 18, 2025: IDO on Binance Wallet, raising $200,000 with a token price of $0.0048.
May 9, 2025: BANK token price reached an all-time high of $0.0705, approximately 14.7x the IDO price.
Lorenzo Protocol is currently actively expanding its ecosystem, with plans for further integration with more DeFi platforms and services to enhance BTC liquidity and applications.
II. Token Information
Token name: Lorenzo Protocol(BANK)
III. Related Links
Website:https://www.lorenzo-protocol.xyz/Explorers：https://bscscan.com/token/0x3AeE7602b612de36088F3ffEd8c8f10E86EbF2bF
Whitepaper:https://docs.lorenzo-protocol.xyz/
Social Media:https://twitter.com/LorenzoProtocol
Note: The project introduction comes from the materials published or provided by the official project team, which is for reference only and does not constitute investment advice. HTX does not take responsibility for any resulting direct or indirect losses.
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Bank AI: A Revolutionary Step in the Future of Banking Introduction In an era marked by rapid advancements in technology, Bank AI stands at the intersection of artificial intelligence (AI) and banking services. This innovative project seeks to redefine the financial landscape, enhancing operational efficiency, security measures, and customer experiences through the power of AI. As we embark on this exploration of Bank AI, we will delve into what the project entails, its operational dynamics, its historical context, and significant milestones. What is Bank AI? At its core, Bank AI represents a transformative initiative aimed at integrating artificial intelligence into various banking operations. This project harnesses the capabilities of AI to automate processes, improve risk management protocols, and enhance customer interaction through personalized services. The primary objectives of Bank AI include: Automation of Banking Functions: By leveraging AI technologies, Bank AI aims to automate routine tasks, reducing the burden on human resources and enhancing efficiency. Enhanced Risk Management: The project utilises AI algorithms to predict and identify risks, thereby fortifying security measures against fraud and other threats. Personalization of Banking Services: Bank AI focuses on offering tailored financial products and services by analysing customer data and behaviours. Improving Customer Experience: The implementation of AI-driven solutions, such as chatbots and virtual assistants, aims to provide users with more human-like interactions, revolutionising the way customers engage with banks. With these goals, Bank AI positions itself as a crucial player in rendering banking more efficient, secure, and user-centric. Who is the Creator of Bank AI? Details regarding the creator of Bank AI remain unknown. As such, no specific individual or organisation has been identified in the available information. The anonymity surrounding the project's inception raises questions but does not detract from its ambitious vision and objectives. Who are the Investors of Bank AI? Similar to the project's creator, specific information regarding the investors or supporting organisations of Bank AI has not been disclosed. Without this information, it is challenging to outline the financial backing and institutional support that might be propelling the project forward. Nevertheless, the importance of having a robust investment foundation is pivotal for sustaining development in such an innovative field. How Does Bank AI Work? Bank AI operates on several innovative fronts, focusing on unique factors that differentiate it from traditional banking frameworks. Below are key operational features: Automation: By applying machine learning algorithms, Bank AI automates various manual processes within banks. This results in reduced operational costs and allows human workers to redirect their efforts towards more strategic activities. Advanced Risk Management: The integration of AI into risk management practices equips banks with tools to accurately predict potential threats such as fraud, ensuring that customer information and assets remain secure. Tailored Financial Recommendations: Through continuous learning from customer interactions, the AI systems develop a nuanced understanding of user needs, enabling them to offer tailored advice on financial decisions. Enhanced Customer Interactions: Utilizing chatbots and virtual assistants powered by AI, Bank AI enables a more engaging customer experience, allowing users to have their queries resolved quickly, thus reducing wait times and improving satisfaction levels. Together, these operational features position Bank AI as a pioneer in the banking sector, establishing new benchmarks for service delivery and operational excellence. Timeline of Bank AI Understanding the trajectory of Bank AI requires a look at its historical context. Below is a timeline highlighting important milestones and developments: Early 2010s: The conceptualization of AI integration into banking services began to gain attention as banking institutions recognised the potential benefits. 2018: A marked increase in the implementation of AI technologies occurred when banks started using AI tools like chatbots for basic customer service and risk management systems for improved security handling. 2023: The sophistication of AI continued to advance, with generative AI being introduced for more complex tasks such as document processing and real-time investment analysis. This year marked a significant leap in the capabilities afforded to banks by AI technology. 2024-Current Status: As of this year, Bank AI is on an upward trajectory, with ongoing research and developments poised to further enhance capabilities in banking operations. Continued exploration of AI applications hints at exciting developments yet to come. Key Points About Bank AI Integration of AI in Banking: Bank AI focuses on adopting artificial intelligence to streamline banking processes and improve user experiences. Automation and Risk Management Focus: The project strongly emphasizes these areas, aiming to shift the burden of routine tasks while enhancing security frameworks through predictive analytics. Personalized Banking Solutions: By harnessing customer data, Bank AI enables tailored banking services that cater to individual user needs. Commitment to Development: Bank AI remains committed to ongoing research and development efforts, ensuring its adaptability and ongoing relevance as technology continues to evolve. Conclusion In summary, Bank AI exemplifies a crucial step forward in the banking industry, leveraging artificial intelligence to reshape operational paradigms, enhance security, and promote customer satisfaction. Despite gaps in information surrounding the creator and investors, the clear objectives and functional mechanisms of Bank AI provide a strong foundation for its ongoing evolution. As AI technology continues to advance and merge with the banking sector, Bank AI is well-positioned to significantly impact the future of financial services, enhancing the way we understand and interact with banking.
1.0k Total ViewsPublished 2024.04.05Updated 2024.12.03
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4.8k Total ViewsPublished 2025.05.09Updated 2026.06.02
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