AI Investing Advice Is Coming: Is Crypto Ready?

Long before OpenAI introduced the world to ChatGPT’s powerful artificial intelligence (AI) model, rudimentary automation was deeply ingrained in the financial world.

In 1978, for example, award-winning mathematician James Simons founded Renaissance Technologies, a quantitative hedge fund, by leveraging data to analyze the statistical probabilities of security price trends. The firm’s iconic medallion fund was established in 1988 and is said to have the best track record in investment history.

Soon after Simons introduced quantitative investing, expert systems became the standard in banking and finance to mitigate the risks of human error. Eventually, they were used to formulate financial plans for people with relatively high incomes.

More recently, machine learning, natural language processing (NLP), and interactive chatbots have been leveraged to help investment firms, banks, credit bureaus, and other financial institutions formulate predictive analytics, combating fraud, understanding customer needs, streamlining customer support, etc. .

Today, in the “golden age of AI,” powerful new AI models are paving the way for a range of disruptive tools and solutions that have the potential to redefine the financial services industry. However, while most industries are eagerly implementing AI solutions to streamline internal processes and provide better customer service, the once-innovative financial sector is lagging behind, according to Teddy Flo, general counsel at Zest AI.

But this is starting to change in part thanks to the adoption of AI in the crypto and blockchain sector.

We have already seen many AI-based crypto platforms and projects leveraging AI for various reasons. Platforms such as Fetch.ai, a machine learning platform designed to automate tasks such as data processing and trading, and Bittensor, a decentralized network enabling the dissemination of AI knowledge, showcase the ingenuity at the intersection of blockchain and AI.

Now, traditional finance could easily integrate the next generation of AI. To this point, cloud-native Software as a Service (SaaS) investment management platform FundGuard recently raised $100 million in a Series C round with its intuitive platform designed to help Asset managers and their service providers to manage mutual funds, exchange traded funds. (ETF), hedge funds, pensions and other financial products. The platform also supports digital transformation, process automation, AI-driven insights, and cloud migration, often serving as the core system for many financial institutions.

Likewise, thanks to the abundance of structured and unstructured data, affordable computing power, and vastly improved neural networks, complex algorithms now provide the basis for more accessible and efficient investment options.

As investors look for innovative ways to gain an edge in financial markets, the transformative capabilities of AI are now being harnessed to support investment strategies and decision-making, as noted by the legendary entrepreneur technology company Steve Cohen who launched an AI-oriented hedge fund offering algorithm-based strategies and decisions. .

Similar approaches have been implemented in the field of cryptography. Since engaging and making informed decisions about digital assets requires a high degree of technical understanding, the AI-powered cryptocurrency trading platform, GT Protocol, uses advanced algorithms to serve as a “ users’ personal Web3 investment and trading assistant.

Catering to all levels of investors, GT Protocol’s platform features a comprehensive conversational interface for providing analysis and developing investment strategies and trading recommendations – a much-needed helping hand for those have varied expertise and objectives.

Whether you are in traditional or decentralized finance, we can expect a growing demand for simplified investment solutions and reliable strategies. AI is enabling the industry to operate better while providing customers with simple, painless and intelligent investment solutions.

At this point, it doesn’t matter whether an institution is a DAO, a dApp, a major bank or an international investment firm, the use of AI is quickly becoming a prerequisite for remaining competitive.