When it comes to investing and trading, the decisions made are spontaneous and dependent on the analysis of the market, and Crypto charts which can be hard sometimes.
This is why using blockchain technology for financial purposes, including investments and trading, has become quite common in today’s time. Also, learn about How Blockchain is Transforming Different Industries in this guide.
The Integration of Financial Technology with Blockchain has become more prevalent with the ever-evolving technological (AI) advancements.
AI helps streamline investment and trading processes with its advanced algorithms and data analytics procedures to increase efficiency and avoid unnecessary human errors.
But how is this possible? The answer is simple. It is possible due to several features that are out there allowing us to leverage for our financial benefits.
Are you keen on learning how AI helps streamline investment and trading? Then this article is the perfect guide for learning Blockchain and the benefits of AI from a financial perspective.
So let’s get started!
Understanding Blockchain: Financial Perspective
“Fundamentally, [it is] an improvement over the way that, traditionally, databases have been designed and used in the past” (2016).
Morgan Stanley (American multinational investment bank and financial services company)
Countless industrialists involved in the development of blockchain technology have described it as a new approach to database architecture.
What makes this technology extremely valuable is its ability to organize and store large amounts of data for rapid search and retrieval.
It provides its users with data security and independence since the platforms are centralized, i.e., there is no higher authority having control over your activity on the platform. This makes the process of transactions smoother than ever.
Did You Know? To transfer an asset from Person A to Person B, the rightful owner of it is determined. Once that is done, the transaction can be made by using the cryptographic hash* that is associated with the given block.
*NOTE: The cryptographic hash is a string of characters associated with a given block that is difficult to calculate but easy to verify. This makes it easy to verify a block, but hard to engineer and put into the chain a block that records transactions that are not legitimate.
Historical Evolution Of AI And Trading
Artificial Intelligence, better known as AI, has gone through different stages of development and complexity over the following years. This evolution has added a layer to the traditional algorithmic trading at each step of the process.
Interestingly, the 1st generation algorithms were composed of buy or sell orders with simple parameters, followed by algorithms allowing for dynamic pricing.
While, the 2nd algorithm deployed strategies to break up large orders and reduce potential market impact, which helped in obtaining better prices or ‘execution algos’.
As technology evolved, AI algorithms have developed into automated, computer-programmed algorithms that learn from the data input used and rely less on human intervention.
In the future as well, AI techniques are expected to expand their capabilities which would help in devising strategies and executing them. This is why AI-driven algorithmic trading should be anticipated.
How AI Has Been Affecting The Financial Market
AI has always been a promising candidate when it comes to providing competitive pricing, managing liquidity, and streamlining execution.
They help enhance liquidity management and execute large orders without really being affected by the market. This can be done by optimizing size, duration, and order size dynamically based on the market conditions.
AI-driven models have been implemented even in financial institutions due to their creditworthiness, which makes them function at the core of finance.
It has also reformed the system of digital risk management (such as digital footprints, media data, and transaction data) with its availability of big data and advanced AI-based analytics models.
AI In The Financial Market: Positive Impacts
With the introduction of AI into the financial sector, the potential has increased for the efficiency and accuracy of operational workflows, enhanced performance, strengthened risk management, and improved customer experience.
Now with the help of AI-based tools like Natural Language Generation and Machine Learning have helped in humanizing and simplifying the data.
In this manner, it helps with the costs of investment managers, replaces manually intensive reconciliations with automated ones, and potentially reduces costs and increases speed.
Listed below are some major benefits of utilizing AI in the investment and trading procedure:
Enhanced Data Management
Optimized Energy Consumption
Enhanced Transaction Efficiency
Innovative Data Management
Augmented Security Measures
Improved Scalability
Unintended Consequences And Possible Risks
Using similar models could have unintended consequences for competition, which could contribute to the amplification of stress in the markets.
Using similar AI-generated technology could pose a potential threat to becoming a victim of cyber-attacks. It is because it gets easier for these attackers to access the data by influencing the autonomous agents of the data in a distinct behavior.
The collusive outcomes of the sustained algorithms can be dangerous since they are likely to be noticed in the market. Related to that is the risk that AI-driven systems may exacerbate illegal practices aiming to manipulate the markets, such as ‘spoofing’.
So it is better to beware before it is too late!
Always Remember!
Spoofing is an illegal market manipulation practice that involves placing bids to buy or offers to sell securities or commodities with the intent of canceling the bids or offers before the deal’s execution.
It is designed to create a false sense of investor demand in the market, thereby manipulating the behavior and actions of other market participants and allowing the spoofer to profit from these changes by reacting to the fluctuations.
Final Thoughts
Previously, it was quite risky to invest in an asset because there was no means to provide the user with live crypto charts. This is one of the reasons why one could not analyze the market trends to predict accordingly.
So as soon as Artificial Intelligence was incorporated into the financial segment, it led to the creation of the FinTech sector.
This has led to much more secure transactions and data security which could be retrieved at any desired moment. It also helps in driving insights on the performance measurements, as well as data analytics.
Although it may have its ifs and buts, countless positive outcomes outweigh the cons.
