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The finance industry has been important for the economic state of the world. It influences business, investments, and wealth management. AI is revolutionizing many sectors including finance and finance is no different. I have chosen finance as my focus for this project, as it is the area of specialization of my major, which makes me excited about how emerging technologies can enhance decision-making processes in a more informed manner and the efficiency of financial operations.

In this Padlet I will talk about the role AI has in finance. This Padlet wall will explore the role of AI in finance through key applications such as trading , automating tasks like customer service, and fraud detection. Machine learning and chatbots make it possible to improve financial security, protection, and overall efficiency of the finance industry.

AI in finance is significant because it increases access to financial services, reduces the role of human biases in decision-making, and increases anti-fraud measures to make banks and investments safer for the customer. On the other hand, it causes worries  in data security, ethical applications of AI, and job loss, which needs to be addressed to enable adoption of AI responsibly.

Since I am a finance student, I am excited and nervous about the role of AI in finance. AI is transforming financial decision-making, risk analysis, and trading, making them more effective. However, automation can reduce career opportunities in traditional finance careers.

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Artificial intelligence-driven fraud detection systems review large amounts of financial transactions in real-time to identify unusual activities. AI applications use “multiple machine learning models to detect anomalies in customer behaviors and connections as well as patterns of accounts.” (Levitt 2023) AI enhances security by recognizing concealed patterns of fraud that would be missed by humans. This would reduce fraud losses. But such systems are afflicted with problems such as false positives, which can lock up genuine transactions, and the need for continuous data refreshes to remain current. But graph neural networks (GNNs) are able to look at “billions of records” and it can identify  “previously unknown patterns of activity to make correlations about whether an account has in the past sent a transaction to a suspicious account.” (Levitt 2023) i think AI is the best decision for this because it looks for patterns in the system and a person can be inept at seeing things so a program would be able to detect it with more efficiency. I think I would be okay with sacrificing a false positive for fraud and get it figured out rather than someone defrauding me of my money.

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AI in Finance - Fraud Detection, Algorithmic Trading, and Risk Management

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Banks are adopting AI chatbots and virtual assistants to improve customer service. The chatbots utilize natural language processing to comprehend and reply to customer questions, and machine learning makes it possible for the chatbots to improve answers over time. Speech recognition technology enables voice assistants such as Alexa and Siri to aid in banking transactions. AI in personalized banking offers 24/7 customer service, lowers operational expenses, and gives personalized financial suggestions. The chatbots “automate mundane customer service tasks” this cuts the “costs associated with employing multiple representatives.” (Capacity 2024) Disadvantages include  their potential to provide inaccurate information and fail to recognize when a customer is asserting their legal rights. "Financial institutions run the risk that when chatbots ingest customer communications and provide responses, the information chatbots provide may not be accurate, the technology may fail to recognize that a consumer is invoking their federal rights, or it may fail to protect their privacy and data." (CFPB 2023) This can lead to legal compliance issues and customer frustration. Provide three specific examples of AI applications and related technology within your chosen industry. I personally think it is good to have an AI chatbot readily available at all times because your financial problems don't come during bank hours usually. The thing that used to frustrate me was waiting for a person to come talk to me 30 minutes later.

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One Million People Are Now Using Erica - BofA’s AI-Powered Chatbot

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The Banking & Payments Show: AI in Banking 2024 | Feb 6, 2024

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AI is transforming financial markets with algorithmic trading, where machine learning algorithms analyze historical trends and execute high-frequency trades automatically. Deep learning improves the precision of market predictions, and natural language processing analyzes financial news and social media sentiment to predict market movements. "AI algorithmic trading’s impact on stocks is likely to continue to grow. Software developers will develop more powerful and faster algorithms to analyze even larger datasets. The programs will continue recognizing complex patterns, adapting faster to changing market conditions and adjusting trading strategies in nanoseconds."(Bansal 2024)  AI enables fast, data-driven decision-making, reducing human prejudices and optimizing investment strategies. But these models are at risk of being subjected to unexpected market events, and market manipulation and regulation concerns still persist. Despite this, AI has revolutionized trading, making it more profitable and efficient for financial institutions and individual traders. I do not think I would personally trust tAI to invest for me because a malfunction means you go broke.

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AI Turned $10k into Profits in 24hrs (No Coding!)

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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AI will revolutionize finance with algorithmic trading, fraud detection, and risk management. Banks are investing a lot of money in AI, with spending rising from "$35 billion in 2023 to $97 billion in 2027," an "annual growth rate of 29%." Companies like JPMorgan Chase have projected that "generative AI applications in the bank could produce up to $2 billion of value," and Citizens Bank anticipates "up to 20% efficiency savings through gen AI as it replaces tasks like coding, customer support, and anti-fraud procedures." On the other hand, financial AI poses significant ethical concerns. Algorithmic bias in lending can lead to discrimination if AI models are trained with biased data. AI-based trading can also increase market volatility, with banks trying to make "more complex and quicker algorithms.” (Parker 2024) I believe that while AI is revolutionizing finance for the better, it needs to be embraced sensibly and responsibly.Making sure there is transparency and equity in AI-based decisions will be critical in shaping its position in the financial industry.

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AI is transforming finance, increasing efficiency but also with concerns over jobs, equality, and stability. "AI algorithms can automate mundane tasks," saving costs but at the cost of jobs. The World Economic Forum estimates "as many as 30% of financial sector jobs could be automated by 2030."AI promotes financial inclusion. "AI-powered solutions have the potential to close the financial gap," extending banking services to the poor. Just like said before the algorithm could be biased since "AI algorithms learn from historical data, which can perpetuate current bias and discrimination." (Krimmelbein) Ethical shielding and transparency will be needed if fairness and stability are to be maintained as finance is increasingly driven by AI.

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Capacity. (2023, November 10). AI chatbots in banking: The future of financial customer service. Capacity. Retrieved from https://capacity.com/learn/ai-chatbots/banking-ai-chatbot/
Rationale: This article talks about AI chatbots in customer service for banking and i chose that as one of the roles AI has in finance.

Consumer Financial Protection Bureau. (2023, July 5). Chatbots in consumer finance. CFPB. Retrieved from https://www.consumerfinance.gov/data-research/research-reports/chatbots-in-consumer-finance/chatbots-in-consumer-finance/
Rationale: This report provides regulatory insights into the use of AI chatbots in financial services. This was also used in the chatbot section and it was an in depth analysis of AI in finance so it gave me more ideas for the other slides.

IBM. (2023, December 8). Artificial intelligence in finance: Opportunities and challenges. IBM. Retrieved from https://www.ibm.com/think/topics/artificial-intelligence-finance
Rationale: This was one of the first articles I read while doing the project. I did not use any quotes but it gave me some ideas to brainstorm with.

Nvidia. (2023, September 14). AI fraud detection: How RAPIDS, Triton, TensorRT, and NeMo protect financial services. NVIDIA Blog. Retrieved from https://blogs.nvidia.com/blog/ai-fraud-detection-rapids-triton-tensorrt-nemo/
Rationale: This article focuses on AI’s role in fraud detection, so i used it in one of the roles AI plays in finance.

Parker, D. (2024, October 3). The future of AI in financial services. Forbes. Retrieved from https://www.forbes.com/sites/davidparker/2024/10/03/the-future-of-ai-in-financial-services/
Rationale: This article examines upcoming AI trends in financial services, so i used it in the future trends section.

Sogeti Labs. (2023, October 20). The societal implications of AI in finance. Sogeti Labs. Retrieved from https://labs.sogeti.com/the-societal-implications-of-ai-in-finance/
Rationale: This source analyzes the broader social and ethical concerns of AI in finance, so i used quotes from it in the social impact of AI in finance.

Wayfair. (2023, August 12). Preventing policy abuse with graph neural networks. About Wayfair. Retrieved from https://www.aboutwayfair.com/careers/tech-blog/preventing-policy-abuse-with-graph-neural-networks
Rationale: this article talks about GNNs that help with fraud protection nd that was a role for AI in finance.

Forbes Technology Council. (2024, March 1). AI in financial services: Transforming stock trading. Forbes. Retrieved fromhttps://www.forbes.com/councils/forbestechcouncil/2024/03/01/ai-in-financial-services-transforming-stock-trading/
Rationale: This article highlights AI’s impact on stock trading.

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This project was interesting to me and also challenging. I think the most difficult task was actually the Padlet . It was not easy to use or customize. I wanted to make the text boxes different shapes but it makes it hard to do so. The research was easy for me because since AI is a new thing in finance there is a lot of recent information on it. This made me more aware of AI in finance and also it has made me think that instead of focusing so much on excel i should maybe think about programming since that's where it seems the industry is going.