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I chose the finance industry because it’s where I see myself building a career. Finance has always combined analysis, strategy, and human decision-making, but now artificial intelligence is changing everything about how the industry operates. AI is behind faster transactions, smarter investments, and better fraud prevention. The use of machine learning, predictive analytics, and natural language processing is reshaping how financial data is understood and used.

I’m especially interested in how AI can reduce human error and uncover patterns that analysts might miss. As someone planning to work in finance, I think understanding how to use these tools responsibly is essential. AI isn’t just about automation; it’s about creating more accurate, efficient, and transparent financial systems.

In this Padlet wall, I’ll explore three examples of how AI is used in finance today: PayPal’s fraud detection systems, Betterment’s AI investment tools, and JPMorgan Chase’s customer service chatbots. I’ll also look at future trends like algorithmic trading and ethical challenges around data bias and privacy. I want to understand how AI will shape my work in finance and what skills I’ll need to succeed in an industry that’s becoming more data-driven every year.

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PayPal uses machine learning to analyze millions of transactions per second, spotting suspicious patterns and stopping fraud in real time. The system constantly learns from new data, improving its ability to detect risks while reducing false alarms. This kind of automation protects customers and builds trust, something that’s critical in finance. As someone entering this industry, I find this exciting because it shows how data and AI can make financial systems more secure while cutting costs and human error.

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Betterment – AI in Investment Management

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Betterment – AI in Investment Management

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Betterment uses AI-powered robo-advisors that apply machine learning to help clients manage investments automatically. The platform creates personalized portfolios, rebalances them, and adjusts strategies based on goals and risk tolerance. This shows how AI can make wealth management accessible to people who don’t have financial advisors. As someone interested in finance, I like how this technology opens opportunities for younger investors and helps build smarter, data-driven portfolios.

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Robo Advisors Explained | What Are They? Are They Right For You?

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JPMorgan Chase uses AI chatbots powered by natural language processing (NLP) to handle millions of customer requests every day. These chatbots can understand questions, find account information, and solve problems quickly, freeing up human employees for more complex work. For me, this highlights a key shift in finance: AI isn’t replacing people, it’s changing the kind of work people do. The focus is moving toward strategy, creativity, and human judgment.

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Building Trust in AI: Chatbots, LLMs, Decentralized Finance, and JPMorgan Chase

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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AI will continue to shape the future of finance, especially in areas like algorithmic trading, risk management, and personalized financial advising. Banks and investment firms are already using predictive models to forecast market movements, and AI will only get more advanced. I’m interested in how this technology can help identify opportunities faster while reducing volatility.

However, the growth of AI raises important ethical questions. Algorithms can reflect the biases in the data they’re trained on, which could unfairly impact credit scores or loan approvals. There are also privacy concerns, since financial systems rely on personal data. As someone planning to enter this field, I believe it’s my responsibility to understand these ethical issues. The industry needs professionals who can balance innovation with transparency and fairness. AI has the potential to make finance more efficient and inclusive, but only if it’s developed and used responsibly.

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AI in finance has already made banking and investing more accessible. People can open accounts, apply for loans, or invest, all from their phones. This level of convenience is something I want to be part of improving. But I’m also aware of the trade-offs. Automation is replacing some traditional roles in banking, and that changes how people build careers in finance.

AI also raises concerns about data privacy and bias. If not managed carefully, algorithms can discriminate or invade people’s financial privacy. On the other hand, AI can make the system more transparent by removing human prejudice from certain decisions. I think the future of finance will depend on how well we balance innovation with ethical responsibility. Personally, I want to be part of a generation of finance professionals who understand both the technology and the human impact behind it.

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Researching AI in finance helped me understand how fast the industry is evolving. I used to think AI was just about automation, but now I see how it supports better decisions, risk management, and customer relationships. My biggest challenge was sorting through technical sources to find reliable, real-world examples. This process taught me that working in finance will require both analytical and ethical thinking. AI is powerful, but its real value depends on how we use it. I’m more motivated now to build a career that combines finance expertise with technological awareness.

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PayPal. (2023). AI and machine learning in fraud detection. PayPal.com.
Rationale: Used to explain how PayPal applies AI to detect and prevent fraudulent transactions in real time.

Betterment. (2023). How Betterment’s robo-advisors use AI for smarter investing. Betterment.com.
Rationale: Chosen to illustrate how AI-driven robo-advisors personalize investment management and financial planning.

JPMorgan Chase. (2023). AI in customer service. JPMorganChase.com.
Rationale: Used to show how major banks leverage AI chatbots and natural language processing to enhance customer support.

Marr, B. (2022). How artificial intelligence is transforming the financial industry. Forbes. https://www.forbes.com
Rationale: Provides a broad, credible overview of AI’s impact across different areas of the financial sector.

Arner, D. W., Barberis, J., & Buckley, R. P. (2017). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business, 37(3), 371–414.
Rationale: Included to discuss the ethical and regulatory implications of AI’s growing role in global finance.