Examples of Effective Financial Data Visualization (& What Charts You Should Be Using)
Effective communication is important as a financial advisor, especially if you work with clients coming from non-financial backgrounds.
In order to help clients make data-driven decisions, you need to be able to interpret complex data and explain financial processes to your clients without confusing or overwhelming them with financial jargon.
This is where data visualization comes in. You can help your clients make informed financial decisions by using visual aids to explain your points intuitively, especially if you’re consulting corporate clients.
Enterprises with a more complicated decision-making process would benefit from visual representations to make inferring the data easier. Normally, internal finance teams might prepare these types of charts so major decision-makers, such as stakeholders, the CFO, and the CEO, can use them to come to a conclusion.
Not only that, but visualization can also help you in your data analytics by uncovering patterns you wouldn’t see otherwise.
In this article, we will explore the different types of financial data visualization charts, provide examples, and discuss best practices.
Types of financial data visualization charts
How your data is represented varies according to various factors — including what data you have and what actionable insights you’re trying to find through the visualization.
Here are a few types of data visualization charts commonly used by financial advisors.
Comparison charts
Comparison charts are used to compare two or more variables. These charts allow you to highlight differences, trends, and relative performance by presenting your data set side by side.
These charts are especially useful when comparing investments, such as the performance of two different stocks. Here are some commonly-used types of comparison charts:
Bar charts employ horizontal bars to represent different data points, allowing for quick visual comparison. This type of chart is ideal to showcase the performance of different investments or the revenue generated by different business units.
Similar to bar charts, column charts use vertical columns to represent data. They are particularly useful when comparing data across different categories or time periods, making trends and variations easily identifiable.
Stacked bar charts offer a unique twist to comparison charts. In these charts, the bars are divided into segments, each representing a different component or category. Stacked bar charts are excellent for illustrating the composition of a whole and comparing the contributions of different elements within that whole.
Trend charts
Trend charts are used to show how a financial variable changes over time.
Whether you want to showcase historical performance, market trends, or forecast future outcomes, these charts allow you to present data in a visually appealing and easy-to-understand manner.
Line graphs, area charts, and combo charts are popular choices to display trends effectively, allowing clients to grasp market movements and identify potential opportunities. These charts are also useful for clients who want to see how their investments have performed over a specific period of time.
Line charts are commonly used to illustrate trends. By connecting data points with lines, line charts display the progression and fluctuations of a variable over a given time period. They are particularly useful for showcasing historical stock prices, portfolio performance, or economic indicators, allowing clients to identify long-term trends and potential turning points.
Area charts are another powerful option for visualizing trends. Similar to line charts, they display the progression of a variable over time. However, area charts fill the area between the line and the x-axis, emphasizing the magnitude of the variable's value. This makes them effective for showcasing cumulative data or comparing multiple variables' contributions to a whole.
Combo charts allow you to combine the representation of multiple variables (more than two) using line and bar charts within one graph. For example, when you want to compare your clients’ yearly income, revenue, and profit.
Distribution charts
Distribution charts are used to show the distribution of a financial variable. These charts allow users to visualize the distribution of data points within a dataset.
Histograms, box plots, and violin plots are commonly employed to represent data distribution, making them useful tools when demonstrating risk-related distributions such as portfolio diversification, risk assessment, or asset allocation. These charts are helpful in effectively conveying distribution patterns to assist clients in making informed financial decisions.
Histograms are widely used to display the distribution of continuous data. The data are divided into a range of intervals along the x-axis and the frequency or count of data points within each range are represented by vertical bars. Histograms help visualize the shape, central tendency, and dispersion of the data. It helps clients see patterns in the data, for example, to identify outliers or frequent values.
Box plots, also known as box-and-whisker plots, offer a concise summary of the distribution. They display the median, quartiles, and outliers of a dataset. The box represents the interquartile range, while the whiskers extend to the minimum and maximum values within a certain range.
Box plots are useful for comparing distributions and identifying skewness, variability, and potential anomalies.
Violin plots combine aspects of box plots and kernel density plots. They showcase the shape of the distribution, providing a density curve that conveys the probability density at different values. Violin plots offer a visual representation of the data's spread and multimodality. It helps clients assess distribution characteristics and make comparisons between groups.
Correlation charts
Correlation charts are used to show the relationship between two or more variables. With financial data, these charts are especially useful when you’re trying to explain how one investment may be affected by another.
By using these types of charts, such as scatter plots and bubble charts, advisors can demonstrate the correlation between different investments, asset classes, or economic indicators. These visualizations allow clients to grasp the interdependency of the financial data and help them construct well-balanced portfolios or evaluate risk factors.
Scatter plots are commonly used to represent the correlation between two numerical variables. Each data point is plotted as a dot, with one variable represented on the x-axis and the other on the y-axis.
The pattern formed by the dots reveals the nature and strength of the relationship between the variables. Scatter plots allow clients to identify trends, clusters, or outliers, aiding in the assessment of investment performance or the impact of economic factors on financial outcomes.
Bubble charts enhance the concept of scatter plots by adding an additional dimension. In addition to the x and y-axis variables, bubble charts incorporate a third variable, usually represented by the size or color of the bubbles.
The size of each bubble indicates a specific metric, such as market capitalization or revenue, providing further insights into the relationships between variables. Bubble charts help clients visualize complex correlations and identify patterns or clusters within the data.
Hierarchical charts
Hierarchical charts allow you to showcase the structure and hierarchy between financial processes. These charts can provide a comprehensive overview of various hierarchies, including organizational structures, investment frameworks, or portfolio compositions.
Common examples of hierarchical charts include treemaps and sunburst charts.
Treemaps display hierarchical data as a set of nested rectangles. Each rectangle represents a category or subcategory, and the size of the rectangle corresponds to a specific metric or value. Treemaps allow clients to understand the relative proportions of different components within a hierarchy, making them useful for visualizing portfolio allocations or asset class breakdowns.
Sunburst charts, also known as radial treemaps, offer a circular representation of hierarchical data. The chart is divided into sectors, with each sector representing a category or subcategory.
The size of the sector corresponds to a specific metric, and the inner layers represent nested levels of the hierarchy. Sunburst charts provide a visually appealing and intuitive way to showcase hierarchical structures and the distribution of values within them.
Geographic maps
Meanwhile, geographic maps offer a spatial perspective, which allows you to convey financial information based on geographical factors. Whether visualizing market trends, global investments, or regional economic indicators, maps provide valuable insights.
By using choropleth maps, bubble maps, or flow maps, you can showcase regional variations, identify global investment opportunities, and support clients in geographical diversification, especially in their investment portfolios.
Choropleth maps are commonly used to showcase regional variations in financial data. By coloring different regions or countries based on specific metrics or indicators, choropleth maps can provide a visual representation of how the data is distributed across certain geographical areas.
These maps can help identify areas of growth, market potential, or economic disparities, allowing you to guide clients in geographical diversification or targeted investment strategies.
Bubble maps add an additional dimension to geographic visualization. In these maps, bubbles are placed at specific locations, representing data points such as investment value, market size, or population.
The size and color of the bubbles convey additional information, such as the magnitude or category of the data. Bubble maps are effective in identifying investment opportunities, understanding regional market dynamics, or comparing different locations based on various factors.
Flow maps allow you to visualize movement or connections between geographic locations. These maps use arrows or lines to represent the flow of goods, capital, or information between different regions.
Flow maps are particularly useful for analyzing trade routes, migration patterns, or financial transactions. They provide insights into the movement of certain assets and can help identify emerging markets, supply chain inefficiencies, or potential risks associated with geographical dependencies.
Examples of financial data visualization
Below are a few use cases of how data visualization can streamline the financial process and provide the insights you and your clients need to succeed.
Example 1: Target-Maps(R) overview. Target-Maps(R) gives you a simple, one-page visual of your client’s financial picture relative to their major financial goals. It allows you to see where they are financially, identify funding gaps, and allow you to sort their goals by priority.
Target-Maps(R) can also double as a tool to promote meaningful conversations during client review meetings. It's simple yet informative interface can help your clients visualize how far along they are with their financial goals.
Target-Maps(R) can also help advisors visualize and compare different scenarios to help clients look at how feasible it is in the long run.
Example 2: Signals(™). Signals(™) provides a quick and visual overview of how well your clients are prepared to handle unexpected financial challenges that can disrupt their financial security. It helps you assess clients' readiness to withstand sustained financial loss and identify potential scenarios that may require attention.
Its engaging and easily-comprehensible visual cues facilitate more efficient discussions with your clients regarding which financial planning topics require immediate attention. This helps you provide relevant advice more quickly and efficiently.
Example 3&4: Target Map(R) Cash Flow details. While Target-Maps(R) overview page provides a quick look at whether your clients are on track for their goals, the cash flow details page provides more detailed information regarding your clients’ funding progress.
The stacked bar chart serves as an overview to help you and your clients see the impact of their annual cash flows — using both current and projected future values — on their goals.
This feature takes into account the clients’ cash flow sources and compares them to their planned future spending (COLA applied automatically). This way, you can show your clients what their financial future might look like and even point out a specific period in which they may run into debt based on their planned spending.
Best practices for financial data visualization
When creating financial data visualizations, it’s important to keep in mind best practices to ensure that the charts are effective and easy to understand. Some best practices include:
Choose the right type of visualization – Different types of charts are better suited for different types of data, so it is essential to choose the one that best conveys the message you want to deliver.
Use colors and labels effectively – Using colors and labels can make a chart more visually appealing and easier to understand. However, avoid overwhelming your clients with excessive colors and overly-detailed labels.
Provide context to your visualizations – This means including relevant information such as time frames, units of measurement, and any other key data points. Make sure that your raw data comes from all the data sources you need to include. If needed, create a central point to store and retrieve the information to avoid data silos.
Keep it simple and avoid clutter – Too many data points or unnecessary elements, such as gridlines, can confuse the viewer and detract from the intended message.
Additionally, it’s important to consider your client’s level of financial knowledge. Adapt the complexity and level of detail in the visualizations to match what they understand. Avoid using jargon or technical terms that may confuse or alienate them.
Upgrade your data visualization with Asset-Map
You might be well-acquainted with visual aids at this point.
Data visualization creates a more intuitive form of your data set. Not only for your clients but also to help you spot important patterns during your data analysis process.
And sure, you can do this in an Excel spreadsheet. However, your Sheets aren’t made to create diagrams more complex than a pie chart — like the ones used to visualize data for financial analysis.
The bottom line is that upgrading your data visualization tool to Asset-Map can help you create visualizations to convey complex subject matters with more ease than a spreadsheet.
Asset-Map is also equipped with features a financial professional needs to analyze their financial data visually. This includes real-time updates to make sure you’re always accessing the up-to-date data, discovery tools to make data gathering easier, and visual maps with interactivity.
As you can see in the data visualization examples above, you can see the data in different formats to suit your needs.
Schedule your demo today and see how you can take your visual mapping to the next level with Asset-Map.