Ripple объявляет о крупном партнерстве с Franklin Templeton и DBS Bank Singapore

cryptonews.ruPublished on 2025-02-17Last updated on 2025-09-18

Ripple объявила о крупном партнерстве с Franklin Templeton, глобальным управляющим активами, который может похвастаться активами на сумму 1,5 млрд долларов, и DBS Bank, крупнейшим банковским учреждением, с целью развития рынков Репо на основе стейблкоинов и токенизированного обеспечения.

В рамках партнерства токен sgBENJI компании Franklin Templeton, представляющий собой акции токенизированного фонда краткосрочного денежного рынка, деноминированного в долларах США, будет размещен на сингапурской бирже. Его можно будет мгновенно обменять на стейблкоин RLUSD, который также будет размещен на торговой платформе. Вместо того чтобы держать волатильных токены без доходности, инвесторы получат возможность мгновенно перейти на более безопасный продукт, приносящий доход, в периоды волатильности.

Следующий этап партнерства будет включать использование токенов sgBENJI в качестве обеспечения и получение кредита от DBS или другого стороннего кредитора в наличных деньгах или стейблкоинах.

Это будет функционировать как типичный рынок РЕПО в традиционных финансах, когда финансовые учреждения используют казначейские облигации США в качестве обеспечения для получения краткосрочных кредитов и получения большей ликвидности.

Более широкое распространение XRPL и RLUSD

В частности, Franklin Templeton выпустит токен sgBENJI в сети XRP Ledger, а также в нескольких других блокчейнах. Ripple утверждает, что XRPL идеально подходит для токенов MMF с большим объёмом выпуска. Тем временем стейблкоин Ripple RLUSD , рыночная капитализация которого в настоящее время приближается к 730 миллионам долларов, станет базовой валютой для торговли sgBENJI. Найджел Хаку из Ripple утверждает, что возможность проведения сделок репо для токенизированного MMF с помощью стейблкоина станет «переломным моментом».

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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. Personalisation 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. 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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 conceptualisation 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. 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