According to a report by Allied Market Research, the global blockchain technology market was valued at $3 billion in 2020 and is expected to grow to $39.7 billion by 2025. Similarly, the AI market is projected to grow to $190 billion by 2025, according to a report by MarketsandMarkets.
With the increasing demand for both blockchain and AI, combining these technologies can revolutionise many industries and transform the way we do business.
What Is Blockchain?
Blockchain technology is a decentralised, distributed ledger that allows for secure and transparent transactions without intermediaries. It was first introduced in 2008 by an unknown individual or group of individuals under the pseudonym Satoshi Nakamoto to facilitate Bitcoin transactions.
The technology works by recording transactions in blocks linked together to form a chain, hence the name ‘blockchain’. Each block contains a cryptographic hash of the previous block, ensuring the chain’s integrity.
The benefits of blockchain technology include increased security, transparency, and efficiency. By eliminating the need for intermediaries, such as banks, transactions can be completed faster and at a lower cost. The technology’s decentralised nature also makes it more resistant to fraud and hacking. Blockchain is used in various industries, including finance, healthcare, and supply chain management.
What Is AI?
AI, or artificial intelligence, refers to the ability of machines to perform tasks that would typically require human intelligence, such as learning, reasoning, and problem-solving. The history of AI traces back to the 1950s when researchers first began developing algorithms for machine learning. Since then, AI has evolved to include many technologies, including neural networks, natural language processing, and computer vision.
AI has rapidly transformed the finance industry by providing faster, more accurate decision-making capabilities and improving operational efficiency. Some examples of how AI is being used in finance include:
- Fraud detection: AI-powered fraud detection systems use machine learning algorithms to identify unusual behaviour patterns and detect fraudulent activities.
- Trading and investment: AI-powered trading algorithms use natural language processing (NLP) to analyse news articles, social media, and other data sources to identify patterns and predict market movements.
- Customer service: Financial institutions use chatbots and virtual assistants to provide customer service and support.
Financial firms worldwide are increasingly turning to artificial intelligence (AI) technologies to improve their efficiency, automate their processes, and provide better customer service. Three examples of financial firms that have successfully adopted AI are Capital One, Citigroup, and Ping An.
Capital One, a US-based financial institution, has implemented natural language processing (NLP) to enhance customer service. Its virtual assistant, Eno, can understand and respond to customer inquiries in natural language, available via the company’s mobile app, website, and text messages. The system has helped Capital One reduce wait times and enhance customer satisfaction. The company has also used machine learning to detect and prevent fraudulent activity.
Citigroup, a multinational investment bank, has been utilising computer vision to analyse financial data. Its research team has developed an AI-powered platform to analyse financial statements and other data to identify patterns and trends.
The platform can also provide predictive insights, assisting investors in making well-informed decisions. The system has improved Citigroup’s research capabilities and enabled the company to provide superior investment advice to its clients.
Ping An, a Chinese insurance and financial services company, has been using machine learning to improve its risk management. Its risk management platform, OneConnect, can analyse large amounts of data to identify potential risks and provide real-time insights.
The system can also offer tailored risk assessments for different types of businesses. OneConnect has assisted Ping An in reducing its risk and enhancing its operational efficiency.
Financial firms are increasingly adopting AI technologies to remain competitive and enhance customer service. By leveraging NLP, computer vision, and machine learning, financial institutions can streamline operations, improve customer service, and make informed decisions. Firms that fail to embrace these technologies may risk falling behind their competitors.
Why AI and Blockchain Must Work Together
AI and blockchain are two of the financial services industry’s most innovative and disruptive technologies. While they are often seen as separate technologies, AI and blockchain are becoming increasingly interdependent for several reasons.
One of the most significant advantages of blockchain is its ability to provide secure, transparent, and tamper-proof transactions. However, blockchain cannot detect fraud, which is where AI comes in.
By integrating AI and blockchain, financial firms can build more secure and transparent systems that leverage AI’s fraud detection capabilities to enhance the trustworthiness of blockchain. This combination can offer improved security and transparency in transactions, which is crucial in financial services.
Another advantage of integrating AI and blockchain is the improved accuracy and efficiency of financial services. Smart contracts built on blockchain can automate financial transactions and self-execute when predefined conditions are met. By integrating AI, smart contracts can also be made more intelligent and capable of automatically adjusting to changing conditions. This integration can lead to the creation of more efficient and accurate financial systems.
Integrating AI into the blockchain can also help financial firms to detect and mitigate risks more quickly and effectively. AI can analyse vast amounts of data in real-time, making it an ideal tool for risk management. For example, AI can identify anomalies in financial transactions and flag them for review or rejection, making detecting fraud and other risks easier. This benefit can lead to better risk management, an essential component of financial services.
The integration of AI and blockchain can also help financial firms to comply with regulations more effectively. Financial rules are complex and ever evolving, making compliance a significant challenge for financial firms. By combining AI and blockchain, financial firms can improve their ability to comply with regulations and reduce the costs and risks associated with non-compliance. For example, blockchain can provide an immutable record of transactions, while AI can be used to analyse the data and ensure that it complies with regulations.
AI Creates New Business Models
Finally, integrating AI and blockchain opens up new business models and opportunities for financial firms. Decentralised finance (DeFi) applications are leveraging AI and blockchain to create new financial products and services that are more efficient, accessible, and affordable than traditional financial services. The combination of AI and blockchain technology creates new opportunities for financial firms, leading to the development of new financial products and services that were not possible before.
In practice, many examples of financial firms are already successfully leveraging AI and blockchain to enhance their services. For instance, Ripple, a blockchain-based payments solution, has integrated AI to improve its fraud detection and risk management capabilities. JPMorgan Chase is using blockchain to develop a decentralised platform for tokenising gold, and AI is being used to analyse the data generated by the platform. Visa also leverages blockchain and AI to enhance its fraud detection and prevention capabilities.
AI and blockchain can transform financial services, enhancing security, transparency, accuracy, efficiency, risk management, compliance, and new business models. By working together, AI and blockchain can create synergies that make them greater than the sum of their parts. Financial firms embracing AI and blockchain are likely better positioned to succeed in an increasingly competitive and complex financial services landscape.
The future of AI-enabled blockchain in financial services is promising, with significant advancements expected in the next decade. Here are some potential developments:
- Financial firms will continue integrating AI and blockchain to improve their operations, increase efficiency, and reduce costs.
- By combining AI’s ability to analyse data with blockchain’s secure and transparent ledger, financial firms can develop systems that provide more secure and private transactions.
- Decentralised finance (DeFi) applications are already leveraging AI and blockchain to create new financial products and services.
- As AI and blockchain become more integrated into financial services, regulatory oversight will increase.
- Integrating AI and blockchain will likely create new business models and revenue streams for financial firms.
Overall, the future of AI-enabled blockchain in financial services looks bright, with continued growth and development expected in the next decade. As financial firms increasingly adopt and integrate these technologies, we can expect to see significant advancements in efficiency and security as new business opportunities emerge.
Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.
The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltec.io.
The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltec.io.
The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.