How to Use Generative AI in Wealth Management

Generative AI can deliver enormous potential, and wealth management firms that make full use of the technology will reap the rewards.

Wealth managers have a lot keeping them up at night:

• higher costs
• lower profit margins
• slower business growth
• increased competition
• rising client expectations and demand for personalized service
• navigating regulatory landscapes
• time-consuming and inefficient practices

Under such pressure, they feel like they have to be everything to everyone, but with so much already on their plate, they have so little time and are not making enough progress.

And that's where Generative AI (Gen AI) comes in.

What is Generative AI?

So much is said about AI and Gen AI, but the differences between the two aren't always clearly stated.

While traditional AI focuses on analyzing existing data to make predictions or automate tasks, generative AI takes it a step further. It can create entirely new content –from text and images to code and even music – based on learned patterns and data.

The wealth management industry can certainly take advantage of this technology, as it has the potential to transform how wealth advisors interact with clients, analyze data, as well as streamline internal processes.

Below, we will share practical applications of generative AI, some of the potential pitfalls, and how to get started.

Use Cases of Generative AI in Wealth Management

Gen AI offers a wealth of opportunities across the front, middle, and back office. Let's explore some key applications:

1. Personalized Client Communications & Meeting Prep

• Draft tailored emails, investment performance summaries, and market updates that resonate with individual clients, saving advisors time and ensuring consistent, high-quality communication.

2. Onboarding

• Use Gen AI for reading, tagging, indexing, managing, and reviewing end-to-end aspects of the onboarding process, and use it to populate draft filing and regulatory aspects

3. Enhanced Client Portals

• Integrate AI-powered chatbots to provide instant answers to client questions, offering 24/7 support and freeing up advisors for complex inquiries.
  ‍
• Generate personalized financial education content based on client interests and knowledge levels.

4. Sales & Marketing Enablement

• Create compelling and company-branded marketing copy, social media posts, and thought leadership articles that attract new clients and position firms as forward-thinking innovators.

5. Automated Report Generation

• Automatically generate complex reports, including the production of visually pleasing performance summaries, compliance documents, and client presentations, all with company branding and colors

6. Research, Data Analysis, & Insights

• Analyze vast amounts of financial data to identify trends, patterns, and anomalies that can inform investment strategies and risk management.
  ‍
• Summarize research reports and market news to keep advisors informed and up-to-date.

7. Compliance Review & Documentation

• Utilize AI to review documents for regulatory compliance, flag potential issues, and even suggest revisions, reducing the risk of human error.
  ‍
• Automate the creation of compliance reports and documentation, saving time and resources.

8. Employee Training & Knowledge Base

• Develop interactive training modules and create a searchable knowledge base with Gen AI to help employees quickly access information and upskill.

Wealth Managers See the Value

Related to many of the above use cases, an Ernst & Young survey highlighted wealth and asset managers shared where they see Gen AI driving the most value:

- Data ingestion to drive alpha generating strategies
- Financial advice
- Investment operations (middle and back office)
- Client onboarding
- Marketing and client acquisitions

How to Get Started

It's one thing to know about all the great things generative AI in wealth management can do, but it's another to put it to use.

Here are a few helpful pointers:

1. Assess Needs

Identify specific pain points and areas where Gen AI could streamline workflows, improve client experiences, or enhance decision-making.

2. Choose the Right Tools

Evaluate different Gen AI platforms and models. Consider factors like ease of use, customization options, and integration capabilities with your existing systems. Don't hesitate to seek expert guidance.

3. Develop Effective Prompts

Ideally, work with skilled prompt engineers or data scientists to create clear, concise, and specific prompts that guide the AI's output and ensure accurate and relevant results.

4. Prioritize Data Security & Privacy

Implement robust security measures to protect sensitive client data and ensure compliance with regulations.

5. Start Small & Iterate

Begin with pilot projects to test the effectiveness of Gen AI in specific use cases. Gather feedback, learn, and refine your approach over time.

Gen AI Potential Pitfalls

There's no question generative AI offers tremendous potential, but it's important to be mindful of the headwinds:

1. Data Bias & Accuracy

‍AI models are trained on existing data, which may contain biases that can impact the quality and fairness of AI-generated outputs. Careful data selection and ongoing monitoring are essential.

2. Lack of Transparency

‍Some AI models are considered "black boxes," meaning their decision-making processes are not easily interpretable. This can raise concerns about accountability and trust, especially in regulated industries like finance.

3. Security & Privacy Risks

‍If not properly implemented, AI tools can create vulnerabilities in data security and privacy. Robust safeguards and ethical considerations are crucial.

4. Robotic Language & Inaccurate Depictions

While most material produced should look good, wealth managers should still take a "trust, but verify" approach with AI.

Be prepared to make a few revisals. There could be inaccuracies or mis-portrayals that don't align with how the wealth manager would present the information, and in turn, how the client should receive that information.

In such case, understanding the role of prompt engineers and Large Language Models (LLMs) can help firms produce more accurate and acceptable results.

And as people become used to seeing more AI-generated content, they are quick to notice it and dismiss the content if it doesn't feel "human enough." This isn't to say not use AI, but make changes as appropriate.

How Empaxis Supports Wealth Management in AI

At Empaxis, we recognize the transformative potential of technology in the ever-evolving wealth management industry.

We understand that staying competitive requires not only adapting to new technologies but also integrating them seamlessly into an operational framework. That's where our expertise comes in.

With our deep understanding of investment operations and technology, we offer end-to-end support for implementing generative AI solutions.

From building custom models to integrating them with wealth managers' existing systems, our team ensures a smooth and efficient transition.

We also provide guidance on data security and privacy, prompt engineering, and change management to maximize the value of your AI investment.

Embrace the Progress and Transformation

Generative AI is more than a buzzword or gimmick; it's a practical tool that allows wealth managers to get more things, more efficiently, accurate, and cost-effectively.

Additionally, it frees up time to focus on what matters most, serving clients and growing the business rather than getting bogged down by admin activity and non-revenue generating minutia.

Ready to learn more and get started with generative AI in wealth management? Contact Empaxis to discuss how we can help you harness this transformative technology.

‍