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The topic that will be discussed in this padlet is that of AI applications within Finance. This topic is specifically interesting to me due to my interest and experience in the financial field. AI has had a great impact on many aspects of finance. One way AI is helpful in finance is through virtual financial assistants, an example of this is Erica from Bank of America. Erica is an AI virtual assistant that can answer questions and give some financial advice that is tailored to the customer. This is increasingly appealing to the customer as it can give them answers in real time versus having to possibly wait on hold for the customer service number or the time it takes to go to a branch.  Another way AI is helpful in finance is with forecasting, this can be used in various aspects such as customer behavior or project spending. AI used in revenue prediction can be immensely valuable to investors that invest based on earnings announcements.  Lastly, a way that AI is helpful in finance is through planning. Planning helps connect where an individual or company is currently and where they aspire to be. This is especially helpful as it can give a clear plan that is to be completed as quickly as possible while still completing the task accurately. Investing is an appealing and complex topic. It will be interesting to see how AI has already affected finance, and what some of those changes may look like moving forward.

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AI is now used in customer service operations; it is helping to combat the increasing customer bases. You can find AI powered virtual assistant’s and chatbots on many types of company’s websites. These AI powered tools have the ability to answer common questions from a large sum of the customer base in real time. The use of natural language processing is what powers these tools. This not only positively impacts the customer but also the company. While these tools are equipped to answer a multitude of questions, they unfortunately do not have the answer or ability to answer every question yet. I find these tools extremely useful I personally have used Erica by Bank of America and was happy with what she was able to accomplish for me. https://youtu.be/wqjKtF-aSDM

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Financial forecasting is powered by machine learning AI and is quickly changing from not only static models but now to interactive and automated forecasting. Automated forecasting adapts the projections given if any new data comes to light. A benefit of this is the ability to adjust assumptions and get immediate forecast impacts.  AI enhances data-driven forecasting at an unheard-of rate. The company or organization that adapts to AI for forecasting will have given themselves an advantage over competitors that do not adapt. I found forecasting to be a very successful AI tool that can assist companies and organizations. The only concern would be to see what the outcome of this will be on staffing.

https://youtu.be/EnN3WlIZGtM?si=ygcIZsN-J27XRte5

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Financial planning connects the analysis of the current conditions and the forecasting of future predictions. An example of how AI achieves this is by the use of robo-advisories that can help with investments that lead to financial or retirement goals attained by the customer base. Additionally, businesses using this AI can highlight any budget impacts that may arise and how to manage them. This is conducive to the planning process being as short and effective as possible. AI in financial planning has increased the efficiency of repeatable tasks, therefore reducing time and money spent on those tasks. This AI tool is extremely useful and important to the world of finance, I worry it may stem to cuts of human workers if it becomes as useful as a human.

https://youtu.be/dWYFExknalY

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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The future of AI in finance is poised for transformative changes, driven by advancements in technology and the increasing demand for efficiency and accuracy. One significant trend is the expansion of AI in predictive analytics. AI algorithms are becoming more adept at analyzing vast datasets to forecast market trends, detect investment opportunities, and manage risks. This predictive power can lead to more informed financial decisions and optimized portfolio management. Another emerging trend is the use of AI in customer service through advanced chatbots and virtual assistants. These tools are improving the efficiency of customer interactions by providing personalized financial advice and resolving queries swiftly, thus enhancing user experience and accessibility. Robotic Process Automation (RPA) is also set to revolutionize financial operations by automating routine tasks such as transaction processing and compliance checks. This automation not only reduces human error but also frees up valuable human resources for more strategic roles. However, these advancements come with notable ethical considerations. Data privacy is a primary concern, as financial institutions collect and analyze extensive personal and financial information. Ensuring the security of this data and obtaining explicit consent from users is crucial to maintaining trust. Bias and fairness represent another challenge. AI systems, if not carefully monitored, can perpetuate existing biases present in historical financial data, potentially leading to discriminatory practices in credit scoring or investment decisions. It is essential to implement rigorous testing and validation to mitigate these biases and promote fairness. Finally, accountability for AI-driven decisions must be clearly defined. Financial institutions must establish transparent processes to address errors or negative outcomes, ensuring that AI applications enhance rather than undermine trust in financial systems. As AI continues to advance in finance, addressing these ethical concerns will be vital to harnessing its benefits while safeguarding fairness and integrity. The future of AI in finance as we can already tell is going to be transformative, watching how AI will change and grow will be quite interesting. Virtual assistants and chatbots have become important to customer bases and are very helpful to all. The main concern I have is chance of biases without careful monitoring.

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AI's integration into the finance sector is reshaping not only industry practices but also broader societal structures. One of the most immediate impacts is on employment. Automation through AI and robotics is streamlining routine tasks, which can lead to job displacement for roles focused on data entry, transaction processing, and even some analytical positions. However, this shift also creates new opportunities in AI management, cybersecurity, and advanced analytics, necessitating a workforce that is adaptable and skilled in emerging technologies. Privacy is another critical concern. Financial institutions utilize AI to analyze vast amounts of personal data for decision-making and risk assessment. This increases the potential for data breaches and misuse. Ensuring stringent data protection measures and transparent practices is essential to mitigate these risks and maintain public trust. Equity issues arise as well. AI systems can unintentionally perpetuate or exacerbate existing biases. For example, algorithms used in credit scoring or loan approvals may reflect historical biases in data, leading to unequal treatment of marginalized communities. To address these concerns, it's imperative to develop and implement AI systems with built-in fairness and bias detection mechanisms. Moreover, AI in finance can contribute to increased economic disparity. Automated trading and sophisticated financial tools may give large institutions a competitive edge over smaller entities and individual investors, potentially widening the gap between wealthy and less affluent sectors of society. In conclusion, while AI offers significant advancements in efficiency and decision-making in finance, it also presents challenges that must be addressed to ensure that its benefits are equitably distributed and its risks carefully managed. Balancing technological progress with ethical considerations will be key to fostering a more inclusive and secure financial landscape. Employment is and will be affected by the integration of AI into finance. Hopefully we can continue to work with AI to achieve goals rather than fully using it and disvaluing employees. A big concern is AI helping to widen the gap between wealthy and everyday people.

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I found this topic very interesting as it directly aligns with a passion of mine, finance. I was not aware of how much AI is integrated into the financial world. Chatbots and virtual assistants are now almost ingrained into our everyday life. It was intriguing to see how they truly impact not only the business but also the customer base as well. This research has opened my eyes to how revolutionizing the integration of AI in finance is but also how easily it can become negative if not properly used and monitored.

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References

Cheishvili, Archil. Top Five Ways AI Is Revolutionizing The Financial Planning Industry. 30 09 2021. https://www.forbes.com/sites/forbestechcouncil/2021/09/30/top-five-ways-ai-is-revolutionizing-the-financial-planning-industry/. 31 07 2024.

Hughes, Chase. Harnessing AI's Potential To Revolutionize Financial Forecasting. 20 11 2023. https://www.forbes.com/sites/forbesbusinesscouncil/2023/11/20/harnessing-ais-potential-to-revolutionize-financial-forecasting/. 31 07 2024.

Peranzo, Pete. AI for Better Finance: Real-World Use Cases and Examples. 30 08 2023. https://imaginovation.net/blog/ai-in-finance/. 31 07 2024.