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When Financial Advisors Might Use AI for Financial Analysis


Artificial intelligence is redefining the way advisors run their businesses. AI tools are making it easier to create social media content, automate back-end operations and allow advisors to digest large amounts of data. There are different ways to use AI for financial analysis, as well as to analyze your business operations and identify opportunities for increased efficiency.

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Understanding AI’s Potential as an Analytical Tool

While AI technology is continually being fine-tuned, its current capabilities are impressive. Advisors can use artificial intelligence to:

  • Glean actionable points from complex datasets
  • Analyze evolving market conditions and trends
  • Construct sample client portfolios based on a set of predetermined parameters
  • Forecast investment outcomes using hypothetical modeling
  • Generate personalized investment recommendations based on client preferences, needs and goals

The primary advantage AI has over human-driven analysis is speed. Tasks that might require hours of an advisor’s time can be completed in minutes or even seconds using AI tools.

How Can Advisors Use AI for Financial Analysis?

The most obvious use cases for AI in financial planning and wealth management center on making client recommendations and selecting investments. However, that’s just the tip of the iceberg regarding what you might be able to do with AI in your firm.

Here are some other possibilities you may consider for putting AI tools to work.

1. Analyzing Financial Statements

Updating your firm’s financial statements is important for measuring overall financial health at any given point in time. Some of the most important statements to maintain for your business include:

  • Cash flow statements
  • Income statements
  • Balance sheets

Compiling and analyzing these statements manually is time-consuming and leaves room for human error. AI technology can simplify this process and reduce the risk of error by analyzing your firm’s financial data and running the necessary calculations for you.

You can use AI tools to automate data collection and generate cash flow projections for the future, based on current trends. That can help you to optimize cash flow and gauge the best use of your firm’s assets.

2. SEO Analysis

AI can be an invaluable tool if you’re interested in gaining more traffic to your advisor website. You might use AI tools to analyze search engine optimization (SEO) data for your site and the sites of your top 10 or 20 competitors to better understand the following:

  • What search terms consumers are using to find your competitors’ websites
  • Which terms clients are using to find your website
  • Typical user behavior of those visiting your site
  • What’s helping or hurting your content qualify

You can also use AI to monitor search trends to see what people are talking about in the financial space at any given time. You can then create content for your social media platforms or email newsletter around those trending topics to drive traffic back to your website.

More traffic can mean more opportunities to convert and increase your bottom line.

3. Data Visualization

An advisor using AI for financial analysis to assist clients.

Visualizer tools can be helpful when discussing future outcomes with clients or plotting your next growth move. If you’re dealing with a substantial amount of complex data, AI can help you break it down in a more accessible format. Using targeted prompts, you can easily generate charts and other graphics with AI design tools.

For example, you might present your client with three different “what if” scenarios and use AI to create visual representations of the associated outcomes for each one. Using AI this way allows for dynamic analysis, and it can help capture a client’s attention more easily and keep them engaged.

4. KYC Compliance

Advisors are subject to a multitude of compliance rules, including Know Your Client (KYC) rules. These rules outline the steps advisors and other financial professionals must take to ensure that they know who they’re working with and are taking steps to actively mitigate the risk of financial fraud.

AI and machine learning can make this process easier by allowing advisors to:

  • Analyze large amounts of data to identify financial transactions that may be fraudulent or are otherwise suspicious
  • Automate data collection during the new client onboarding process
  • Compile the required data for due diligence
  • Analyze client risk
  • Continuously monitor client transaction data to spot patterns that might suggest fraudulent or criminal activity related to terrorism, money laundering or other illegal activities

Again, the primary advantage to advisors is that using AI saves time and reduces the likelihood of errors. You can also provide a better client experience by streamlining the onboarding process so that it’s as simple and minimally invasive as possible.

5. Cybersecurity

Cyberattacks present a real threat to financial advisors and the financial services industry as a whole. Having your clients’ personal and financial information compromised can be damaging to your brand reputation and it may also lead to fines and penalties if you violate SEC cybersecurity reporting rules.

AI can be an invaluable tool for defending your firm against cyberattacks. For example, you can use AI tools to analyze how client information is being accessed within your firm and identify events that may suggest a break from the usual pattern. AI can also be used to:

  • Predict possible cyberattacks based on the analysis of historical trend data
  • Analyze your existing security systems for vulnerabilities or flaws
  • Mitigate or contain cybersecurity threats when they’re discovered

As new types of cybersecurity threats evolve, AI evolves along with them through machine learning. This can help ensure that your business is not taken by surprise.

Frequently Asked Questions (FAQs)

What Is the Use of AI in Financial Analysis?

AI has numerous applications in financial analysis, especially for financial advisors who want to better serve their clients and run their businesses more efficiently. Some of the ways advisors can use AI include generating social media content, automating operational processes and ensuring compliance with regulatory rules.

What Are the Cons of AI in Finance?

AI is an imperfect technology, and there’s still a great deal of room for improvement. Some of the biggest drawbacks to be aware of when using AI for financial analysis or other analysis in your firm include concerns surrounding data security, the influence of bias forecasting and the lack of concrete ethical standards for AI’s application.

How Is AI Disrupting Finance?

AI is disrupting finance and wealth management in numerous ways as more advisors embrace its possibilities. Some examples of AI’s disruption include its use as a fraud detection and compliance tool, and its role in helping advisors construct client portfolios.

Bottom Line

Advisors using AI for financial analysis to run their firm more efficiently.

AI is still in its relative infancy, and it remains to be seen just how big of an impact it will have on the financial services industry. Considering the different ways in which you might use AI for financial analysis is a good first step in getting more comfortable with the technology, which doesn’t appear to be going away any time soon.

Tips for Growing Your Advisory Business

  • If you’re struggling with creating content for social media or email marketing campaigns, AI is one tool you might consider using. You could also look into partnering with an advisor marketing platform to increase your firm’s visibility. SmartAsset AMP offers an intuitive and comprehensive approach to lead generation. You can get access to leads along with the tools you need to nurture those relationships automatically. Schedule a free demo to learn how you can leverage it for business growth.
  • In 2023, the SEC proposed new rules that would require broker-dealers and investment advisors to address conflicts of interest associated with the use of predictive data analytics and similar AI technologies in their interactions with investors. While no final rule has been issued as of May 2024, it’s important to keep an eye on the regulatory landscape and where AI may eventually fit into it.

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