By William White, Fetcherr Advisory Board Member
Technology has revolutionized the modern business environment, making it easier for companies to operate with “big data” and machine learning. These tools have become powerful and can help businesses make data-driven decisions and micro decisions. Artificial Intelligence (AI) can unlock strategic business opportunities in Big Data, providing beneficial business insights to support micro decision-making. However, large companies face several challenges in investing in and integrating new technology.
Some of the most common challenges include data security, digital transformation, cloud solutions, compliance, integrations, automation, application deployment, and lack of an effective digital transformation strategy. Sometimes newer technologies have challenges integrating with older systems or legacy applications like those found in the airline, banking and insurance sectors. Legacy systems act in isolation and are difficult or impossible to be integrated.
Companies need to identify challenges that systems/processes impacted by the change may experience, as they adjust and adopt the change. Embracing these changes is critical in the new business environment and in welcoming the opportunities AI offers.
Over my 30 years in financial markets I have witnessed the benefits of being a first mover in technology. The opportunities are numerous, including strong brand recognition, higher business margins, market share, and the ability to outpace competitors in the learning curve. However, many businesses struggle with limiting R&D budgets, poor IT management, legacy infrastructures, lack of appropriate technology resources, bureaucracy, and lack of support from the organization.
These challenges are present across every industry, but opportunities to access innovation have become more accessible today than in the past. This access has been common in AI transforming the stock market by automating research and data-driven decision making, which allows investors to spend less time researching and more time overseeing actual trades and advising their clients. High frequency traders use machine learning, sentiment analysis, and complex algorithmic predictions to analyze millions of data points and execute trades at the optimal price. AI trading also analyzes forecast markets with accuracy and efficiency to mitigate risks and provide higher returns.
Algorithmic trading has transformed the way trading is done, and stock traders are using algorithms to bring higher speed and efficiency to trading in securities. AI in trading was a game changer, and some have compared modern AI and machine learning to the original electronification of trading.
The financial markets have led with the utilization of AI, and businesses with these capabilities are looking to disrupt nontraditional trading companies. Fetcherr is an algo-based company that has engineered a unique agnostic AI-driven platform market engine that aim to disrupt traditional, rule based systems through deep learning methodologies which can be applied to different industries – beginning with the airline industry. For example, the similarities of the financial and airline industries at first look are limited, but pricing trades and pricing airline tickets is very similar.
The demand curve shows the relationship between the price of a good or service and the quantity demanded for a given period of time. It’s the law of demand, which states that the quantity demanded will decrease as the price increases for the majority of goods. Demand curves can be used to understand the price-quantity relationship for consumers in a particular market, such as trading, airlines or any retail demand product. Demand curves are based on the demand schedule, which shows exactly how many units of a good or service will be purchased at various price points. The simple strategy for High Frequency trading is being duplicated into the airline industry and beyond.
William White is a Fetcherr investor and advisory board member and an experienced managing director. William is currently CCO of IMX, the financial futures exchange for the healthcare industry. He is the former CEO of ClearList, the equities marketplace for private companies; and the former Managing Director and Global Head of Product Development and Platform for Markets at Barclays Investment Bank. He is a financial leader with an eye for innovation and extensive experience in capital markets and derivative trading.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
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