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The use of cryptocurrencies is growing rapidly in acceptance. Perhaps it's because so many countries are trying to digitalize their economies. Julio M Herrera Velutini, Bancredito founder explains all the potential changes that might evolve the payment system in the banking sector with the emergence of cryptocurrency. Even if the cryptocurrency market is expanding quickly and becoming more well-known, traditional banking sectors are hesitant to accept the use of these digital assets, because they believe the dangers outweigh the potential gains. So, let’s explore the below article to know more about the impact of cryptocurrency emergence. Banks' opinions about digital money are being changed by regulatory organizations like the Office of the Comptroller of the money (OCC), which thinks that these assets might lead financial institutions into a new age of innovation and efficiency. Because traditional banks think that dealing with crypto assets has a higher risk and requires time-consuming and expensive due diligence, cryptocurrencies may have an impact on the banking industry. However, if financial institutions are prepared to make the change, digital currencies may provide various advantages to both them and their customers. Because they don't need a middleman and are independent of a centralized bank, government, or organization, crypto assets were created to replace traditional banking infrastructure. Utilizing cryptocurrencies makes it possible to conduct peer-to-peer transactions without the use of a regulated intermediary, allowing users to transmit money quickly and simply without having to pay transaction fees. Instead of being tied to a specific bank account via a financial institution, transactions are merely related to the transaction ID on the blockchain. The potential disruption of the current payment systems and intermediation processes is one of the key effects of cryptocurrencies on the banking industry. With the use of cryptocurrencies, consumers may send money between countries and legal systems without the aid of banks or other third-party service providers. This may lessen the need for remittance services, wire transfers, bank accounts, and payment cards, as well as the fees and charges related to them. Additionally, cryptocurrency can offer substitute forms of finance and loans for people and companies, eschewing conventional middlemen and credit checks. The regulatory and compliance ramifications of cryptocurrencies on the banking industry are another effect. For banks that wish to provide or accept cryptocurrencies, the various legal frameworks and laws that apply in various nations and areas create confusion and complexity. For instance, although other authorities have recognized cryptocurrencies as legal cash or assets, some have prohibited or restricted their usage. Furthermore, because they might support anonymous and illegal transactions, cryptocurrencies present substantial issues for now-your-customer (KYC) and anti-money laundering (AML) operations. To avoid money laundering, terrorist funding, tax evasion, and fraud, banks that work with cryptocurrencies must adhere to several regulations and standards. The potential for innovation and cooperation is the third way that cryptocurrencies are having an influence on the financial industry. For banks that are ready to adapt and use cryptocurrencies, they may also provide a wealth of advantages and chances. For instance, cryptocurrencies may assist banks in enhancing their product offerings, customer service, and operational effectiveness. Blockchain technology may be used by banks to improve their security, lower their expenses, and promote transparency. In Julio Herrera’s opinion, banks may utilize cryptocurrencies to draw in new clients, particularly underbanked and unbanked people who don't have access to conventional financial services. Aside from that, banks may work with cryptocurrency platforms and service providers to deliver integrated solutions and services that cater to the requirements and preferences of their clients.
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Blockchain: The Game-Changer in Revolutionizing Financial Services | Julio M Herrera Velutini3/1/2024 In recent years, there has been a ton of talk about blockchain technology. Many business owners like Julio Hererra Velutini, Bancredito founder and programmers are discovering how technology may be applied to enhance current procedures in a variety of industries, including the banking sector. Blockchain is already being investigated for its potential to decrease fraud and speed up and secure transactions. Blockchain will probably play a very important role in reducing risk and ensuring transparency as the global financial institutions grow increasingly integrated. This is so because blockchain was created primarily to prevent hacking and encourage trust asserts Julio Herrera Velutini. Anyone who works in the finance sector should be familiar with blockchain and the potential changes it might bring about. Are blockchains capable of improving financial services? Blockchain has the potential to greatly increase transparency in the financial services sector, making it less vulnerable to fraud since it generates an indelible record. Additionally, since this is feasible without significant investment in cybersecurity, consumers may eventually pay less for items. Transactions cannot be hidden since every activity taken on a blockchain is visible to everyone. This technology makes it much simpler to spot fraud, asserts Julio Herrera Velutini, Britannia Financial Group founder, giving financial institutions the ability to address these problems right away. Overall, there will be a significant reduction in the risk that financial institutions confront. The current digital world has far too many scammers, therefore blockchain is a terrific method to make financial service transactions more secure. In traditional banking, information passes via several different financial intermediaries, each of which carries the potential for interception. Blockchain offers information exchange security and does away with the need for such middlemen, which ultimately means that the customer is much more protected. There is never a single point of failure since the blockchain network is decentralized. Several other systems can still deliver the same information if one goes down. Additionally, if data in one system changes and the change is not consistent with the others, that system is changed. For hackers to successfully penetrate blockchain, they would need to simultaneously access several systems. As per Julio Herrera, Blockchain has certain advantages for fintech as well. Traditional financial services are losing popularity among consumers as they are replaced by technologically advanced ones. Blockchain addresses the security issue that finance businesses frequently encounter and makes it more practical to expedite procedures, which lowers prices for consumers. Fintech will be able to provide inexpensive financial services with the aid of blockchain as more people need them, added Julio M. Herrera Velutini. Soon, there could be a competition among financial businesses to see who can effectively incorporate blockchain the quickest, cutting operational expenses and offering a less expensive, more secure product. The businesses who implement this first will outperform many of their rivals. Read blog - How Cryptocurrency Emergence Evolved The Banking Sector with New Payment Regime? Developers are adopting AI-powered code generators — services like GitHub Copilot and Amazon CodeWhisperer, along with open access models such as Meta’s Code Llama — at an astonishing rate. But the tools are far from ideal. Many aren’t free. Others are, but only under licenses that preclude them from being used in common commercial contexts.
Perceiving the demand for alternatives, AI startup Hugging Face several years ago teamed up with ServiceNow, the workflow automation platform, to create StarCoder, an open source code generator with a less restrictive license than some of the others out there. The original came online early last year, and work has been underway on a follow-up, StarCoder 2, ever since. StarCoder 2 isn’t a single code-generating model, but rather a family. Released today, it comes in three variants, the first two of which can run on most modern consumer GPUs: A 3-billion-parameter (3B) model trained by ServiceNow A 7-billion-parameter (7B) model trained by Hugging Face A 15-billion-parameter (15B) model trained by Nvidia, the newest supporter of the StarCoder project (Note that “parameters” are the parts of a model learned from training data and essentially define the skill of the model on a problem, in this case generating code.) Like most other code generators, StarCoder 2 can suggest ways to complete unfinished lines of code as well as summarize and retrieve snippets of code when asked in natural language. Trained with 4x more data than the original StarCoder (67.5 terabytes versus 6.4 terabytes), StarCoder 2 delivers what Hugging Face, ServiceNow and Nvidia characterize as “significantly” improved performance at lower costs to operate. StarCoder 2 can be fine-tuned “in a few hours” using a GPU like the Nvidia A100 on first- or third-party data to create apps such as chatbots and personal coding assistants. And, because it was trained on a larger and more diverse data set than the original StarCoder (~619 programming languages), StarCoder 2 can make more accurate, context-aware predictions — at least hypothetically. “StarCoder 2 was created especially for developers who need to build applications quickly,” Harm de Vries, head of ServiceNow’s StarCoder 2 development team, told TechCrunch in an interview. “With StarCoder2, developers can use its capabilities to make coding more efficient without sacrificing speed or quality.” Now, I’d venture to say that not every developer would agree with de Vries on the speed and quality points. Code generators promise to streamline certain coding tasks — but at a cost. A recent Stanford study found that engineers who use code-generating systems are more likely to introduce security vulnerabilities in the apps they develop. Elsewhere, a poll from Sonatype, the cybersecurity firm, shows that the majority of developers are concerned about the lack of insight into how code from code generators is produced and “code sprawl” from generators producing too much code to manage. StarCoder 2’s license might also prove to be a roadblock for some. StarCoder 2 is licensed under the BigCode Open RAIL-M 1.0, which aims to promote responsible use by imposing “light touch” restrictions on both model licensees and downstream users. While less constraining than many other licenses, RAIL-M isn’t truly “open” in the sense that it doesn’t permit developers to use StarCoder 2 for every conceivable application (medical advice-giving apps are strictly off limits, for example). Some commentators say RAIL-M’s requirements may be too vague to comply with in any case — and that RAIL-M could conflict with AI-related regulations like the EU AI Act. In response to the above criticism, a Hugging Face spokesperson had this to say via an emailed statement: “The license was carefully engineered to maximize compliance with current laws and regulations.” Setting all this aside for a moment, is StarCoder 2 really superior to the other code generators out there — free or paid? Depending on the benchmark, it appears to be more efficient than one of the versions of Code Llama, Code Llama 33B. Hugging Face says that StarCoder 2 15B matches Code Llama 33B on a subset of code completion tasks at twice the speed. It’s not clear which tasks; Hugging Face didn’t specify. StarCoder 2, as an open source collection of models, also has the advantage of being able to deploy locally and “learn” a developer’s source code or codebase — an attractive prospect to devs and companies wary of exposing code to a cloud-hosted AI. In a 2023 survey from Portal26 and CensusWide, 85% of businesses said that they were wary of adopting GenAI like code generators due to the privacy and security risks — like employees sharing sensitive information or vendors training on proprietary data. Hugging Face, ServiceNow and Nvidia also make the case that StarCoder 2 is more ethical — and less legally fraught — than its rivals. All GenAI models regurgitate — in other words, spit out a mirror copy of data they were trained on. It doesn’t take an active imagination to see why this might land a developer in trouble. With code generators trained on copyrighted code, it’s entirely possible that, even with filters and additional safeguards in place, the generators could unwittingly recommend copyrighted code and fail to label it as such. A few vendors, including GitHub, Microsoft (GitHub’s parent company) and Amazon, have pledged to provide legal coverage in situations where a code generator customer is accused of violating copyright. But coverage varies vendor-to-vendor and is generally limited to corporate clientele. As opposed to code generators trained using copyrighted code (GitHub Copilot, among others), StarCoder 2 was trained only on data under license from the Software Heritage, the nonprofit organization providing archival services for code. Ahead of StarCoder 2’s training, BigCode, the cross-organizational team behind much of StarCoder 2’s roadmap, gave code owners a chance to opt out of the training set if they wanted. As with the original StarCoder, StarCoder 2’s training data is available for developers to fork, reproduce or audit as they please. Leandro von Werra, a Hugging Face machine learning engineer and co-lead of BigCode, pointed out that while there’s been a proliferation of open code generators recently, few have been accompanied by information about the data that went into training them and, indeed, how they were trained. “From a scientific standpoint, an issue is that training is not reproducible, but also as a data producer (i.e. someone uploading their code to GitHub), you don’t know if and how your data was used,” von Werra said in an interview. “StarCoder 2 addresses this issue by being fully transparent across the whole training pipeline from scraping pretraining data to the training itself.” StarCoder 2 isn’t perfect, that said. Like other code generators, it’s susceptible to bias. De Vries notes that it can generate code with elements that reflect stereotypes about gender and race. And because StarCoder 2 was trained on predominantly English-language comments, Python and Java code, it performs weaker on languages other than English and “lower-resource” code like Fortran and Haskell. Still, von Werra asserts it’s a step in the right direction. “We strongly believe that building trust and accountability with AI models requires transparency and auditability of the full model pipeline including training data and training recipe,” he said. “StarCoder 2 [showcases] how fully open models can deliver competitive performance.” You might be wondering — as was this writer — what incentive Hugging Face, ServiceNow and Nvidia have to invest in a project like StarCoder 2. They’re businesses, after all — and training models isn’t cheap. So far as I can tell, it’s a tried-and-true strategy: foster goodwill and build paid services on top of the open source releases. ServiceNow has already used StarCoder to create Now LLM, a product for code generation fine-tuned for ServiceNow workflow patterns, use cases and processes. Hugging Face, which offers model implementation consulting plans, is providing hosted versions of the StarCoder 2 models on its platform. So is Nvidia, which is making StarCoder 2 available through an API and web front-end. For devs expressly interested in the no-cost offline experience, StarCoder 2 — the models, source code and more — can be downloaded from the project’s GitHub page. The majority of Julio M. Herrera Velutini's formative years were spent in New York. Later, he attended both The American School in Switzerland (TASIS) and The American School in England (TASIS England). Later, he returned to Venezuela to finish his undergraduate studies at Universidad Central de Venezuela. In 1991, Julio Herrera began working as a stockbroker at the Multinvest Casa de Bolsa, a brokerage house located at the Caracas Stock Exchange. He acquired stockholders, including George Soros' family ownership, eight years later, at the age of 28, when he was already a powerful worldwide figure, to become the company's majority shareholder. He was also a board member. He was named CEO of Inversiones Trans banca the same year, and Transban Investment Corporation, a family-owned business that was formed following the sale of Banco Caracas, made him one of its primary stockholders. As a result, he was able to advance to the position of senior director in several major corporations, including Kia Motors of Venezuela, BMW of Venezuela, BBO Financial Services, Transporte de Valores Bancarios de Venezuela (a firm that transports securities), Banco Activo, Banco Comercial, and Banco Real. At the age of 29, he was appointed Co-Chairman of the Bolivar Banco Universal Board of Directors. From early 2007 to February 2009, he presided as Banco Real's and Banreal Holding's board chairman. Bancredito International Bank in the United States in late 2009 by Julio M. Herrera Velutini. Bancredito foundation was another establishment along with the international Bank. In London and Switzerland at the start of 2012, he established Britannia Financial Group. He presently serves on the board of directors for numerous more businesses. He was named CEO of Inversiones Transbanca the same year, and Transban Investment Corporation, a family-owned business that was formed following the sale of Banco Caracas, made him one of its primary stockholders. As a result, he was able to advance to the position of senior director in several major corporations, including Kia Motors of Venezuela, BMW of Venezuela, BBO Financial Services, Transporte de Valores Bancarios de Venezuela (a firm that transports securities), Banco Activo, Banco Comercial, and Banco Real. At the age of 29, he was appointed Co-Chairman of the Bolivar Banco Universal Board of Directors. Bancredito, a bank focused on private banking, corporate banking, and institutional banking with a large customer from Latin America, was established in Puerto Rico by Julio Herrera Velutini in 2009. Bancredito has more than 100 workers and a capitalization of more than $60 million. He is the board chairman at the moment. All these achievements of Mr. Velutini are just a glimpse of their career where he excels with flying colors and added a new chapter in the House of Herrera. Julio’s achievements list can’t be harnessed in one blog, that’s why we are ending this blog here with a note to the audience to connect with us in the next part of Julio Herrera’s career. |
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