Author: Jamie Houston
Artificial Intelligence (AI) is no longer a concept confined to science fiction or high-tech laboratories. This past year, AI has reached consumers in ways previously unimagined. The rise of Large Language Models (LLMs), such as ChatGPT, has given people an entirely new way of approaching problems. Engineers are using LLMs to help them write code, writers to help improve their flow, academics to summarize research papers, and the list goes on. The number of industries touched by this technology is quite remarkable. This raises the question: How will the rise of LLMs affect wealth managers?
At Bristol Gate, we have been incorporating AI into our process from the beginning. We are committed to staying at the forefront of technology through a process of continuous improvement and analysis of new technologies. Our history of combining man and machine has taught us how to implement technology to its full capabilities while not blindly putting faith into a black box algorithm. Our data science team has a long, successful track record of accurately predicting a company’s future dividend growth. These predictions inform our investment process and allow our portfolio managers to make unbiased, data-driven decisions that result in long-term wealth creation for our clients. We have always been strong believers in the synergies between AI and human intelligence and believe that many businesses can benefit from the integration of technology into their practices.
What LLMs Are Not
When talking about the potential of LLMs, it is important to first recognize what they are not. Large Language Models are not the golden solution that can be set off with no forethought and be expected to produce good results. In their current state, LLMs are most effectively used when combined with human insight. A good analogy for this relationship is a pilot and autopilot. Consider the human as the pilot and the AI as the autopilot; the pilot must determine the course of the flight and engage the autopilot appropriately, ensuring the flight stays on track and meets its objectives. Just as the pilot doesn’t rely solely on the autopilot for all decisions, effective use of LLMs requires human oversight to guide and utilize their capabilities for meaningful outcomes.
There are many known limitations that these models have and one of the major considerations that users should be aware of is when a model “hallucinates”. A hallucination is when a generative model produces incorrect information and presents it as true. For example, if you were to ask ChatGPT about specific compliance rules for investment advisors, the output may include false information that could harm your practice should you blindly trust the response. For this reason, the best use cases of these models are when they complement human expertise rather than replace it. They should not be used and trusted as the sole source of information for critical decision-making processes and the answers should always be cross-referenced with trusted sources to ensure accuracy.
Another concern with LLMs is the issue of bias in training data. These models are trained on very large datasets, which inevitably include biased or skewed perspectives. This can lead to outputs that unintentionally perpetuate these biases, whether related to political stances, opinions on the economy, or other factors. While LLMs can process and synthesize information at a remarkable scale, they do so based on the data they have been trained on, which may not always be neutral or comprehensive. This once again highlights the need for a balanced approach where human oversight is used to identify and mitigate these biases.
Knowing that we cannot expect ChatGPT to autonomously run a firm’s marketing, or take over the role of the CFO, there are many different areas which we can focus on that ChatGPT can help with.
Brainstorming. ChatGPT does a fantastic job of helping humans organize their thoughts and providing useful suggestions for further development. A simple query such as, ‘Please give me blog post ideas on taxes and investors’, can offer advisors a range of content ideas. For blog posts, it might not be smart to have ChatGPT write the whole thing, but continuing the conversation and asking ChatGPT to develop the structure of the blog can also be very helpful.
Learning and exploring. For simple topics, ChatGPT can be an excellent tutor. Generative AI models are great at simplifying information and presenting it in a style that works for you. Asking the model to explain something like a typical risk management process can be a great learning tool, especially when follow up questions are asked by the user to help with understanding. Follow-up questions are particularly important as they give users the ability to ask a near unlimited number of questions to refine their understanding. For example, after asking ChatGPT about a typical risk management process, a good follow-up question could be, ‘Can you explain how stress testing fits into this process?’. This back-and-forth conversation is very helpful when breaking down larger or more complex topics.
Text analysis. ChatGPT does an excellent job at traditional Natural Language Processing tasks such as summarization, extracting entities, or judging sentiment. By passing long or complex texts to ChatGPT with a specific task of summarizing in a specific tone, or extracting all company names, or even judging sentiment on a scale of 1 through 10, users can quickly absorb information that would have otherwise taken a larger amount of time.
Social Media. While the cases of brainstorming and idea generation have already been touched on, there are other, unique ways to utilize this technology. If you have previously written content, either on your company website, your pitch deck, or even blog posts, you can pass these documents to ChatGPT and ask to generate social media posts based off those topics. This is a handy way of repurposing content that you have already created.
Creative writing. Another valuable use case for wealth managers is leveraging ChatGPT’s creative writing ability. ChatGPT has the great ability to make complex topics seem simple and can help with your firm’s communications to clients. For example, if you have a highly technical report and would like to quickly communicate the insights to non-technical clients, ChatGPT can help you transform your report into one that is digestible by a wider audience.
The rise of LLMs offers promising avenues for various aspects of practice management for wealth managers. While not a perfect solution to all of our problems, these AI tools can significantly aid in areas such as brainstorming, learning, analysis, and marketing. As long as we are aware of the shortcomings of these models and exercise caution and good judgement, LLMs can provide users with incredible use cases that can save time and increase output. If you are ever short on ideas of how LLMs can help your practice, it can help to ask yourself the question, what would I do if I had the power of 5,000 10th graders on my team?
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