Introducing GPT-4

The typical approach to generating insights in financial services involves analyst-focused dashboards and reports—and lots and lots of data entry and number crunching. GPT-4 is changing everything, helping advisors create more personal stories around their clients’ data, then augmenting it with easy to understand content. This allows advisers and investors to make more informed decisions based on real and relevant information—faster. Much much faster.

With GPT-4 still in its infancy, it’s already breaking new ground, and its meteoric growth is a testament to its effectiveness. The first version, ChatGDP-3, took just five days to reach one million active users. Within just four months, it reached 100 million monthly active users, making it the fastest-growing app in history.This massive user base is using GPT-4 over a billion times a month. Billion. With a B.

With the acquisition of one million users in five days, ChatGDT-3 is the fastest-growing app in history.

And it’s not just exploding in size; it’s also improving at a blistering pace. When the original ChatGPT attempted the bar exam, it scored in the 10th percentile. Not bad for a bot, but hold onto your hats. Four months later, the very next version, GPT-4 zoomed into the 90th percentile on one of the hardest exams on the planet.

While many uses of GPT-4 are still largely experimental, it’s quickly making waves everywhere. At ForwardLane, our consultants use it to quickly create slides and presentations. But that’s just the tip of the iceberg for us. How about development, business analysis, communication, and marketing content? The possibilities are endless.

Risks and limitations

ChatGPT has enormous potential to revolutionize the financial advisory industry, but  it's important to acknowledge the risks and limitations associated with the technology.

ChatGPT is like a knowledge worker that requires oversight. It's not a replacement for a financial advisor (which is why much of the hype about job loss to AI is unfounded). It’s an incredibly powerful partner, despite its limitations.

‍Inaccurate responses: The initial launch used ChatGPT-3, and much of the initial criticism of the technology, was due to the limitations of that earlier version. It had a tendency to very confidently give wrong answers that sounded completely plausible. While accuracy significantly improved with GPT-4, and will only get better, the repercussions of blindly trusting your AI responses could be career-ending.

‍Race and gender bias: Research has also found that the technology can exhibit biases related to race and gender, due to the bias included in the data it has been trained on. This presents a significant challenge that must be addressed to ensure the technology is used responsibly.

‍Lack of transparency: The black-box nature of ChatGPT also raises concerns. Machine learning this complex lacks transparency, with neural networks so deep that issues like bias can be difficult to address.

‍Security risks: As with any technology that is reliant on data input, there is always the potential for issues if the data is not thoroughly vetted or adequately secured.

So how do you safely use it within the financial industry?

How to get started with Chat-GPT

First and foremost, it's important to understand the rules and regulations around its use. Additionally, having a solid understanding of macro and micro economics, statistics, and effective communication skills is crucial to making the most out of this tool. Prompt engineering is also a rapidly growing field, as experts work to identify the inputs that yield the most accurate results.

ForwardLane is already using natural language AI to improve the efficiency of data-gathering and analysis. We capture information using advanced voice-to-text, straight into the advisors’ notes. Next, we connect the enterprise data—portfolio insights, risk analytics, etc.—to the conversations advisers have with their clients.

Data automation‍

In today's financial industry, data is everything. Without accurate, current data, financial advisors can't effectively manage their clients' portfolios, provide personalized investment advice, or ensure regulatory compliance. That's why data automation and personalization have become critical components of modern financial planning and management.

One of the main challenges in data automation is integrating complex data from various sources into a unified enterprise system. AI can take complex data, summarize it, and load it into a checkbox for easy access by financial advisors and their clients. This allows for 24/7 access to financial insights, giving clients a better experience and allowing them to interact with their own data—all before they even meet with their advisor.

Another application of AI and machine learning in asset management is automating data analysis to provide specific insights on portfolio drift or rollover, which can run automatically every day. This provides a more efficient and accurate way to manage risk, and can help financial advisors focus on more high-level activities and engage more deeply with their clients.

Data automation does come with risks, however, like overreliance on the system. It's easy to assume that the data entered into the system is always accurate, and financial advisors may become complacent and stop double-checking the information. This can lead to serious errors in portfolio management and regulatory compliance.

Another risk is data verifiability and compliance. With so much data being generated and processed, it's important to ensure that the data is accurate and compliant with regulatory requirements. Financial advisors need to take extra precautions to ensure that the data is verified and up-to-date, and that they're in compliance with all relevant regulations.

Personalized plans

Developing highly personalized plans is crucial in asset management because it provides a comprehensive picture of the client's financial outlook and goals. To engage and capture clients, it is important to establish reports that discuss their financial goals and needs, considering their background, risk inclination, and investments. The plan should also include benefits of diverse planning, portfolio estate, personal services, family wealth management, and generational planning. The financial advisor should also explain how they will build trust for a transparent long-term relationship, collaborate and communicate on an ongoing basis. This sounds like a lot of work–because it is.

To develop a personalized plan, the virtual system asks questions to gather all the information needed, such as financial goals and objectives, income, monthly expenses, investment experience, and specific financial concerns or challenges. The system can also provide open-ended questions to get a better understanding of the client's short and long-term goals. Once all the information is gathered, the system can create a plan and provide recommendations in just a few seconds.

These AI use cases in wealth management benefit financial advisors in easier onboarding, done automatically through desktop or mobile apps. The plan can be plugged into all the other aspects of a large organization, such as risk management, legacy planning, estate management, and investments. It simplifies complex processes, making life easier for the financial advisor and the client, improving the client experience, reducing friction, and making it more seamless.

How to work with technology as it changes‍

Rapidly evolving technology is a common theme in the financial services industry, and the development of AI-powered tools has only accelerated this trend. As we have seen with the discussion of AI and its potential uses in financial services, the technology has come a long way in just a few short months.

However, this rapid pace of innovation also raises concerns about the safety and accuracy of the data being used by these tools. This is why some have called for a moratorium on the development of AI tools until they can be fully certified and comply with all necessary regulations.

To mitigate skepticism from executive team members, pilots can be done in each area of interest with KPIs and measurements to see for themselves what can be measured. With the help of AI, financial advisors can focus on more high-level activities and engage with clients more effectively, making it easier to deliver sophisticated information in an easy format that stands out.

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Moving the AI world forward.

‍‍As AI continues to evolve, it is important for financial institutions to consider the areas where it can be safely implemented, such as marketing and client interaction, while also being mindful of the potential risks in areas where there are not yet established protocols and safeguards.

Overall, GPT-4 presents a significant opportunity for financial services companies to improve efficiency and enhance the customer experience, but it is essential to approach this technology with caution and careful consideration of its potential impacts.

ForwardLane’s AI-powered platform enables investment professionals to maximize their profits while managing risk more effectively than ever before. ForwardLane helps financial professionals deepen client relationships, grow revenue, and work more efficiently with the ability to unlock a 35% expansion in sales, 15% more sales capacity, and 650% faster time to insight.

It’s how financial professionals are leveling up performance. It’s how to use artificial intelligence–intelligently.