Session 6/7 Assignment: AI in Industry and Society by William Birney

Personalized Overview

williambirney — 2025-10-08 18:07:02 UTC

Artificial intelligence is shaking up the finance world in a big way. It’s not just banks using it for fraud checks anymore — AI is everywhere. From investment management to customer service, it’s changing how financial institutions operate and how people handle their money.

One of the biggest differences I’ve noticed is how fast decisions can be made. AI can look at thousands of data points in seconds and spot patterns that humans would probably miss. IBM recently showed how major banks use these systems to catch suspicious activity before it becomes a serious problem. It’s not perfect, but it’s way more accurate and efficient than older methods.

On the investing side, AI is doing the kind of work that used to take entire research teams. Companies like Bloomberg and Goldman Sachs rely on machine learning models to read market data and predict short-term trends. It’s wild how much faster things move now.

AI is also helping regular people. Robo-advisors, for example, give users customized financial plans with just a few questions. That used to require a full financial advisor. For someone like me studying finance, it’s interesting to see how accessible investing has become.

Overall, AI has made finance smarter, faster, and more open to everyone. It’s not replacing people—it’s just changing how the work gets done. The technology still needs to be used responsibly, but there’s no question it’s here to stay.

Finance – AI in Fraud Detection

williambirney — 2025-10-08 18:23:45 UTC

AI is playing a huge role in stopping fraud before it happens. Banks now use programs that learn how people normally spend and then flag anything that feels off. It’s kind of like a digital security guard that never sleeps. Machine learning is the main tech here — the system studies millions of transactions and starts recognizing red flags on its own. The cool part is how fast it works; it can catch weird activity in seconds. The biggest challenge is privacy, since all that data has to come from somewhere. I like this use of AI because it protects people’s money without slowing them down.

Finance – AI in Robo-Advisors

williambirney — 2025-10-08 18:24:31 UTC

Robo-advisors are one of the biggest ways AI has changed investing. Instead of paying a financial planner, people can now use an app that builds and manages a portfolio for them automatically. These platforms use machine learning to track goals, adjust risk levels, and rebalance investments over time. It’s basically like having a smart assistant that watches your money 24/7. The upside is that it makes investing way more accessible and affordable for everyone. The main issue is that it still lacks the human touch. I think it’s pretty cool that everyday people can now invest like professionals.

Finance – AI in Algorithmic Trading

williambirney — 2025-10-08 18:39:43 UTC

AI has become one of the driving forces behind modern trading. Instead of relying only on human judgment, firms now use algorithmic systems that can analyze market data, company reports, and even social media sentiment within seconds. These programs are powered by machine learning, which allows them to detect patterns and make split-second trades. The advantage is speed and accuracy — decisions that once took hours now happen in milliseconds. Still, that same speed creates risk when markets shift unexpectedly. I find this fascinating because it shows how finance has evolved into a space where technology doesn’t just assist traders — it competes with them.

Future Trends and Ethical Considerations

williambirney — 2025-10-08 18:54:09 UTC

AI in finance is developing fast, and honestly, it feels like the industry is still trying to catch up. One trend that stands out is predictive analytics. Banks and trading firms are using it to forecast risks and market movements with better accuracy. These systems pull data from everywhere—market prices, global news, even social media—and try to find patterns that humans would overlook. The idea isn’t to replace financial analysts, but to give them more reliable information, faster.

Another major focus is automation in risk and credit management. AI can constantly monitor accounts, detect changes in credit behavior, and flag problems before they escalate. Some companies are even testing generative AI to simplify financial reports and make them easier for clients to understand, which could help bridge the communication gap between professionals and the public. Over time, I think this type of technology will become standard in most financial institutions, not a bonus feature.

Of course, there’s a downside. The biggest issue is still transparency. Many AI systems work like sealed boxes—no one really knows why they make certain decisions. There’s also the risk of bias if the data behind them isn’t fair or diverse enough. In finance, that could mean unfair loan decisions or inaccurate credit scoring.

I think the future of AI in this field will come down to trust. The tools will only work long term if people believe they’re being used responsibly. Without that trust, all the progress in speed and accuracy won’t really matter.

Societal Impact

williambirney — 2025-10-08 19:02:02 UTC

AI has changed how people interact with money in ways that most of us don’t even think about. It’s made things faster, easier, and more personal — but also a little less human. I think one of the biggest changes is accessibility. Anyone can download an app, answer a few questions, and have an investment plan in minutes. That used to require sitting down with a financial advisor or filling out piles of paperwork. Now, it’s something people do on their phones between classes or while waiting for coffee. It’s convenient, and it’s giving younger people a head start that older generations never had.

Another huge impact is security. Banks can catch unusual transactions almost instantly, which makes people more confident about online banking. For younger generations, that trust matters because everything we do is digital now. When the system feels secure, people are more likely to invest, save, and manage their money online.

But it’s not all perfect. AI also replaces certain jobs, and I’ve noticed more financial companies relying on chatbots or automated systems instead of people. There’s also the concern that algorithms make decisions based purely on data. It feels efficient, but sometimes it forgets that people aren’t numbers.

Overall, AI has pushed finance forward in a massive way, but it’s also forcing us to rethink how much control we want to give technology. The challenge isn’t just making AI smarter — it’s making sure it stays fair, personal, and trustworthy as it becomes part of everyday life.

Overview Video 1

williambirney — 2025-10-08 19:22:45 UTC

Part 1

Overview Video 2

williambirney — 2025-10-08 19:26:03 UTC

Part 2

Overview Part 3

williambirney — 2025-10-08 19:26:51 UTC

Part 3

Reflection

williambirney — 2025-10-08 19:30:45 UTC

Working on this project gave me a much clearer view of how powerful AI really is in the finance world. When I started, I honestly didn’t realize how deep it already runs through everyday tools like banking apps and fraud alerts. My biggest challenge was sorting through so many articles and figuring out which ones were actually credible. Once I narrowed that down, I started seeing real connections between technology and human decision-making. What I learned most is that AI can make finance more fair and efficient, but only if it’s used responsibly. This research definitely made me think more about trust, bias, and how important transparency will be for the industry moving forward.

References

williambirney — 2025-10-08 20:00:34 UTC

1. Aros, L. H., Ximena, L., Gutierrez-Portela, F., Johver, J., & Samuel, M. (2024). Financial fraud detection through the application of machine learning techniques: A literature review. Humanities and Social Sciences Communications. [Rationale: This article explains how machine learning improves fraud detection, supporting my section on AI’s technical role in finance.]

2. Doshi, K. (2025). AI applications in fraud detection in the banking industry. Forbes. [Rationale: This source provides real-world examples of how banks are using AI to prevent fraud.]

3. Fighting fraud in payments with AI. (2025). KPMG. [Rationale: I used this report to show how AI helps secure payment systems and reduce financial risk.]

4. Flinders, M., Smalley, I., & Schneider, J. (2025). AI fraud detection in banking. IBM. [Rationale: This article explains how banks use AI models to detect suspicious activity faster and more accurately.]

5. Steinhaeuser, I., & Reuters, T. (2024). How AI will disrupt fraud prevention and detection technologies. Thomson Reuters Institute. [Rationale: This article helped me understand how AI is transforming corporate fraud prevention and compliance.]

6. Kashyap, A. (2025). AI-driven financial advisory: The rise of robo-advisors. SSRN. [Rationale: This paper explains how AI-driven robo-advisors are reshaping investment management and accessibility.]

7. Vuković, D. B., Dekpo-Adza, S., & Matović, S. (2025). AI integration in financial services: A systematic review of trends and regulatory challenges. Humanities and Social Sciences Communications. [Rationale: I used this article to support my discussion on AI trends, automation, and regulation in finance.]