Businesses that effectively embrace the digital transition will prosper as the world changes. The world as we know it is about to change because of two developing technologies: blockchain and artificial intelligence (AI).
However, it’s not always clear whether these two technologies complement or compete. Are they compatible or antagonistic with one another?
How can you ensure that your company embraces blockchain and AI seamlessly?
A blockchain is a continuously growing digital ledger that records every transaction that has ever taken place. The continuous ledger that is made up of a “chain” of “blocks” of data are connected across a network of computers and is referred to as a “blockchain.”
The network of computers that manages the blockchain disperses data across the network, unlike a conventional database, which is controlled by a single entity. As a result, a highly secure, transparent, and immutable distributed network system is produced.
This is so that any changes or additions to the ledger don’t require simultaneous changes to all of the computers on the blockchain network, which each maintains an identical copy of the ledger. As a result, the blockchain system creates a very safe and impenetrable record of transactions.
Artificial intelligence is the term used to describe computers that, through intricate algorithms built into the software, may display understanding resembling humans. AI enables organizations to develop and flourish by automating repetitive operations, improving decision-making, and streamlining procedures.
AI is computer code created to imitate and reproduce human intellect. It is a machine with human-like learning, comprehension, and response capabilities.
Machine learning (ML), a subset of AI, can fuel AI. A computer program that can “learn” and enhance its performance over time is referred to as ML.
For instance, if an AI system can be taught to recognize pictures, it may utilize the information to figure out what a particular image is. Everything from facial recognition to comprehending customer purchase behavior may be done using machine learning.
Blockchain and AI can combine to address sharing economy or supply chain management issues. AI-generated data and insights may be utilized to enhance the precision and accuracy of blockchain technology and establish new levels of system trust.
While computer systems and apps utilize AI algorithms to automate processes and activities, blockchain technology serves three core purposes when dealing with these systems and applications:
By incorporating data from sensors and cameras, which can gather more exact data, such as the date and location of an item’s creation, AI may help blockchain become more accurate and precise. The accuracy of the blockchain record can increase thanks to the data from these sensors. In addition, demonstrating an item’s provenance and assisting in eradicating fraud can enhance user confidence in the system.
Substantial potential for industry-specific integration of AI and blockchain has emerged due to the expanding use of these two technologies. While some of the opportunities are now fully tapped into, others are more likely to do so in the future. The following sectors demonstrate the greatest need for or the possibility of applying blockchain-based AI solutions.
Some DeFi apps already make use of artificial intelligence by:
• Maximizing proposals for exchange trades
• Automatically putting up the best portfolios of cryptocurrency assets from several platforms
• Predicting asset rate changes to assist in the decision-making of crypto investors
Most DeFi platforms now rely primarily on individuals to make the majority of trading and investing decisions, while they offer some limited automation capability for these processes. Essentially, they provide the user with a trading interface, letting them weigh their alternatives and decide what to do.
A few Defi systems have already made technological advances in AI. For instance, the yield farming app YAI.Finance on the Oraichain platform employs AI algorithms to assist users in evaluating the risks and rewards of various investment situations and provides suggestions for the best course of action.
The following are some use cases for blockchain and AI in the banking sector:
Banks use AI algorithms to detect and identify questionable transactions as part of their anti-money laundering efforts. Blockchain technologies may be used to exchange and access the necessary information because many anti-money laundering duties involve collaboration between various banks, financial institutions, and governmental organizations.
For the onboarding of new clients, banks often implement stringent KYC (“Know Your Customer”) checks. In this procedure, AI features like picture recognition are routinely applied. Additionally, it is frequently required for banks and governmental organizations to share data, especially in suspicious circumstances. Blockchain technology may enable multiple banks and government agencies to cross-verify the relevant identification data in this situation.
One of the most popular uses of AI in banking is evaluating new clients’ credit risk. Sharing the findings of these evaluations between banks and credit score reporting bureaus can be facilitated by blockchain-based systems. In addition, to improve credit risk assessments of consumers, they can also be utilized to obtain extra information from multiple banks and reporting agencies.
Another significant consumer of both blockchain and AI technology is the insurance sector.
Fraud detection in claims processing. To streamline their claims processing operations—the main activity of any insurance business—many insurance companies are turning to blockchain-based solutions. Blockchain networks link various reinsurers, brokers, healthcare organizations, auto repair shops, and other stakeholders.
To identify fraudulent claims, these claims processing networks usually utilize AI algorithms. For instance, critical data is provided to blockchain-based claims systems through external oracles to verify claims. The sensors and cameras deployed on roads and AI capabilities to assess traffic and road incidents are typical examples of these oracles.
Optimal insurance plan and rate development. Insurance carriers utilize AI algorithms to predict customers’ future claims events and behaviors, much as banks use AI to evaluate customers’ credit risk. The best insurance prices and policies are created based on these projections.
The accuracy of these AI forecast algorithms may significantly increase by using blockchain technology to inject external data into them from other insurers, governments, credit reporting agencies, and healthcare providers.
Government use cases for blockchain-based AI are numerous, given how often governments employ AI to fight crime, estimate economic models, develop urban settings, and offer various services to the populace.
Inter-departmental networks powered by blockchain for identity management and delivering a range of public services. These platforms heavily rely on AI technology, such as face recognition software, to identify identity theft and provide the general public with simplified services.
Intergovernmental blockchain-based networks employ artificial intelligence (AI) to look for and find financial crimes, unauthorized human movement, and tax evasion.
AI-based blockchain land registry records are used to identify fraud in land claims. However, due to challenges in obtaining and measuring land and other country-specific factors, land register records in many nations include inaccurate and occasionally false information.
Such a register might be managed by a blockchain and AI-based system, reducing fraud. The Swedish government is now testing a solution like this for its land register database.
Supply networks for big players in the retail sector are getting more intricate. Hence, the blockchain emerges as an appealing option to hold data for transparency and optimization as these supply networks get more complicated.
Supply chains for supermarkets frequently employ AI to predict the ideal amounts of inventory and orders for the next delivery period. All the network participants involved, including farmers, distributors, resellers, and transportation firms, may plan and optimize their activity levels and operations as these projections are communicated across a blockchain-based supply chain system.
Knowing the supermarket’s anticipated order level for the upcoming buying season will be advantageous to each of these network partners for the supermarket.
Supermarkets already utilize AI imaging technology to spot rotten produce on their shelves. Retailers might reduce expenses associated with purchasing subpar food by integrating AI technology to detect inferior product quality at the source of purchase and transmitting this information over the blockchain.
The openness and accountability of original produce makers and distributors concerning delivering quality food will improve by storing this information on a blockchain-based supply chain system.
Blockchain-based AI solutions open up a wide range of new prospects. The Defi, finance, insurance, retail, and government sectors are where AI will succeed most.
Blockchain and AI are frequently combined through sharing AI algorithm outputs on blockchain systems, using AI-enabled oracles to supply blockchain with data, and using asset optimization and prediction algorithms based on AI on various Defi platforms.
As the combined usage of blockchain and AI expands, the Defi sector should likewise experience rapid growth in intelligent automation. Platforms that offer AI-enabled automated trading and investment advice will win users away from Defi platforms that do not, as these services become the industry standard.
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.deltecbank.com.
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.deltecbank.com.
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.
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