Outsmart The Future
Today in Everyday AI
6 minute read
🎙 Daily Podcast Episode: What impact will AI have on financial risk management? Will the robot overlords be making our financial decisions for us? How do those changes affect us as consumers? We dive in with an expert in the field. Give it a listen.
🕵️♂️ Fresh Finds: Creating your custom blog, FAQ & doc in 30 seconds, Meta AI Chief worried about an AI monopoly, and OpenAI is fine with ChatGPT falsely accusing people? Read on for Fresh Finds.
🗞 Byte Sized Daily AI News: US Government establishes AI executive order, ChatGPT gets new updates and OpenAI CEO warns AI is gaining superhuman persuasion. For that and more, read on for Byte Sized News.
🚀 AI In 5: Ever wished ChatGPT could mimic your unique writing style in any chat? We’re showing you how it’s possible using a ChatGPT plugin! See how here.
🧠 Learn & Leveraging AI: Could Generative AI help prevent a future bank collapse? And what risks come with handing off risk management to AI? Keep reading for that!
↩️ Don’t miss out: Did you miss our last newsletter? We talked about the future of careers with AI, UN forms AI Governance Advisory Body, and the best secret ChatGPT plugin. Check it here!
How AI Will Change Financial Risk Management 💸
Is it possible for AI to manage our money? Well we decided to find out.
What effect will AI have on financial risk management?
How will financial institutions change and what impact will it have on consumers?
Sandeep Maira, Founder & CTO of Raven Risk Intelligence, joins us to discuss the future of financial risk management with AI and how it'll affect us all.
Also on the pod today:
• Challenges of adding GenAI to financial risk 🤔
• The impact AI has on consumers 👥
• Implementing LLMs into risk management 🤖
It’ll be worth your 31 minutes:
Subscribe and listen on your favorite podcast platform
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Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – Notice AI lets you create your custom blog, FAQ & doc in 30 seconds, DeepTalk lets you chat with your data, and AI Code helps you craft web pages using AI code.
1. Biden's Historic Move on AI Governance 🤖
President Biden has announced the U.S. government's first-ever executive order on artificial intelligence. This significant move aims to bolster the nation's AI capabilities, emphasizing the importance of AI in the country's future. The order will address various AI-related issues, including research, development, and ethical considerations.
2. ChatGPT's Potential Cutoff Date Update 🔄
Speculations believe that ChatGPT might have received an update with more recent information up to 2023. While OpenAI hasn't officially confirmed these rumors, users and developers are keenly observing for any changes. The potential update could enhance the model's capabilities and knowledge base. Stay tuned for official announcements from OpenAI!
3. ChatGPT Plus Beta: More Tools, More Power 🛠️
OpenAI is introducing new beta features for ChatGPT Plus members. The update allows users to upload files and interact with them seamlessly. Additionally, the chatbot can now handle tasks like summarizing data, answering questions, and even generating data visualizations. From analyzing text files to creating Pixar-style images, ChatGPT's capabilities are expanding.
4. OpenAI CEO Warns AI is Learning Superhuman Persuasion ❌
OpenAI CEO, Sam Altman, is worried that AI is starting to lead to “strange outcomes.” Although we may be far from artificial general intelligence (AGI), the rapid advancement of AI’s capabilities is already leading to its persuasion on humans. Sam Altman believes AI will be capable of superhuman persuasion even before it reaches AGI.
5. Meta Advocates for a New Open Source Approach in AI 🌐
Meta's Fundamental AI Research (FAIR) center has released its large language model, Llama 2, with a unique approach to open-source licensing. While the model is available for free, its license doesn't meet all the Open Source Initiative (OSI) requirements. As the AI community grapples with defining open source in the context of AI, Meta's stance sparks a broader conversation about transparency, safety, and collaboration in AI development.
Make ChatGPT Write like you in ANY Chat! ✍️
Ever wished ChatGPT could mimic your unique writing style in any chat?
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🤷♂️ What’s Going On and Why It Matters:
We get what you’re probably thinking — AI’s role in financial risk management has absolutely nothing to do with me.
Oh, what’s that? You don’t have a bank account, or a mortgage, or a 401K?
Of course you do. And that’s why understanding AI’s role in the future of risk management is actually super important for us all to grasp.
You wanna know what’s going on with your money, right?
That’s why we chatted with Sandeep Maira on today’s show, the Founder/CTO of Raven Risk Intelligence.
Sandeep has a deep background in banking AND AI, having held prominent roles at JP Morgan Chase and other large financial institutions.
So, we picked his brain for the most important takeaways when it comes to how financial institutions assess risk using AI, and what it means for us all.
Here’s the gist of what we dived into:
Limitations of current models in analyzing unstructured information
Using machine learning to correlate real-time events with economic impact
Human reinforcement learning and its significance
Regulators' concerns about using machine learning for decision-making
How AI can automate tedious tasks and improve productivity
Importance of interconnectivity in AI models for risk prediction
🦾How You Can Leverage:
The future of financial institutions?
Probably a powerful combo of traditional AI and large language models.
If you caught our episode with Sandeep Maira today, you have a better idea of how AI and financial risk play together.
Because here’s the reality — AI’s role in financial risk management affects us all.
Case in point: advancements in large language models, combined with traditional AI-powered financial risk management, could have helped prevent the Silicon Valley Bank collapse.
Got your attention now, right?
Sandeep talked about the long history of AI in the financial space, what it means to us all, and how the recent wave of Generative AI is going to shake the landscape.
Here’s 3 lessons, learning and predictions that can help us all understand where AI is headed in regards to financial risk management 👇
1 – The ‘AI winter’ is over 🥶
Sandeep shared a story about how he took an AI course at Cornell 30 years ago. Even then, the textbook talked about AI’s role in the financial industry and forecasted that artificial intelligence, in the future, would be able to emulate human decision-making.
Sandeep referenced that with recent advancements, the ‘AI winter’ may now be over. In short, AI in the financial industry has traditionally leveraged structured data in machine learning. In other words, models that dealt with finite data.
However, advancements in large language models now bring together an entirely new suite of tools to help assess financial risk. Financial institutions can now combine traditional structured AI data with LLMs to better help human decision-making around unstructured data.
Yeah, it’s a bit deep here. But, the rise of large language models and generative AI systems give the financial industry exciting new ways to better identify and deal with risk across the board.
2 – Gen AI + Traditional AI = future 🚀
Whether it’s improved fraud detection or the ability to more accurately give out loans to deserving applicants, Generative AI has been a much-needed toolset in the never-ending battle of financial risk management.
As an example, Sandeed mentioned the combination of traditional machine learning and newer GenAI can help institutions better expand access to credit for people without traditional credit history.
Generative AI can help paint a clearer picture of unstructured data that isn’t exactly 1s and 2s, and needs human-like reasoning to make a decision.
By leveraging unstructured data sets, AI algorithms can provide a more accurate outlook on a consumer's ability to pay back credit. This means that individuals from minority populations or those who have had a rough time can now have access to credit opportunities that were previously unavailable to them.
3 – Regulatory mindset needs to shift️ 🧠
New game, new rules. Right?
There’s actually two sides to this coin. Because traditional AI and machine learning has been used in the financial industry for decades, regulators already may have a hard stance on AI.
Sandeep mentioned that one of the challenges in implementing AI in financial risk management is gaining the trust and acceptance of regulators. While AI can bring TONS of improvements to decision making, regulators are cautious about potential inaccuracies and hallucinations in model outputs.
To put it into perspective, check out this article on Generative AI breakthroughs and how better regulation around AI could help prevent a future bank collapse.
Now This …
Are you excited or worried for AI to be implemented into financial risk management?