The financial technology (fintech) sector is booming, transforming how people manage their money. 

From mobile payments to automated wealth management tools, fintech companies offer innovative solutions that are convenient, efficient, and accessible. But with this growth comes the challenge of measuring success. Unlike traditional financial institutions, fintech companies operate in a dynamic environment with unique customer behaviors and business models,  making it increasingly difficult to derive meaningful insights from complex financial data.

This is where data visualization comes in. 

With data visualization, you can:

• Identify trends – See patterns in your data that might be hidden in spreadsheets or raw numbers.
• Understand customers – Gain valuable insights into how customers interact with your products and services, enabling personalization and improving user experience.
• Make better decisions – Use clear data visualizations to support your choices and drive growth, giving you a competitive edge in the crowded fintech market.

Benefits of data visualization in fintech

Fintech thrives on data, but raw numbers can be overwhelming. 

Data visualization transforms this data into clear and actionable insights, empowering businesses to make better decisions. 

Here's how:

1. Enhanced decision-making: Visualizations make complex financial information easy to understand. Spotting trends, patterns, and outliers becomes effortless. For example, a fintech lender could use data visualization to quickly identify loan applications with higher risk profiles, enabling them to make more informed lending decisions.

2. Improved customer insights: Data visualization tools reveal customer behavior. Fintech companies can see how customers interact with their products and identify their needs and preferences. It empowers them to personalize services, improve user experience, and boost customer satisfaction. A mobile payment app could use visualizations to understand when and where customers are most likely to use their service, allowing them to tailor their offerings accordingly.

3. Risk management: Identifying and mitigating risk is crucial in fintech. Data visualization helps uncover hidden patterns in financial transactions. This allows for real-time fraud detection and proactive risk management, protecting the company and its customers. A wealth management firm could use visualizations to monitor unusual account activity, detecting potential fraudulent behavior before it causes significant losses.

4. Increased transparency: Clear and concise data visualizations enhance communication. Complex financial reports become easily digestible for investors, regulators, and everyday users. This fosters trust and transparency, strengthening relationships with all stakeholders. A fintech startup could use visualizations to clearly communicate their performance and growth metrics to potential investors, increasing their chances of securing funding.

Key KPIs and metrics in fintech: Measuring performance and driving growth

Fintech businesses rely on a specific set of metrics to gauge their success. 

These metrics, called Key Performance Indicators (KPIs), help identify areas for improvement and drive overall growth. Let's explore some crucial KPIs and how they translate to actionable insights:

1. Customer acquisition cost (CAC):

This metric tracks how much it costs to acquire a new customer.

Knowing your CAC allows you to evaluate the effectiveness of your marketing and sales efforts. If CAC is high, explore cost-effective marketing channels or refine your target audience. For fintech companies operating in a highly competitive market, keeping CAC low is essential for long-term profitability.

2. Customer lifetime value (CLTV):

This metric measures the total revenue a customer generates over their relationship with the company.

It's crucial for understanding long-term customer profitability. Strategies to increase CLTV include offering loyalty programs or upselling relevant products. In the fintech industry, where customer retention is key, maximizing CLTV can lead to significant revenue growth.

3. Conversion rate: 

This metric measures the percentage of users who complete a desired action, like signing up for a service or making a transaction.

A low conversion rate indicates friction in your user journey. Analyze user behavior and streamline the process to boost conversions. For fintech companies with digital-first business models, optimizing conversion rates can have a significant impact on customer acquisition and revenue.

4. Average transaction value: 

This metric reveals the average amount spent per transaction.

A low average transaction value might suggest a need for product bundling or offering premium features to increase spending per user. In the fintech space, where transaction fees are a common revenue stream, increasing average transaction value can directly boost profitability.

5. Net promoter score (NPS): 

This metric measures customer loyalty by asking them how likely they are to recommend your service to others. 

A high NPS indicates satisfied customers who can become brand advocates. Use NPS to identify areas for improvement in customer experience and implement changes to address concerns and boost loyalty. In fintech, positive word-of-mouth from loyal customers can be a powerful driver of growth.

Best practices for fintech data visualization

Data visualization is a powerful tool in fintech, but poorly designed visuals can confuse more than clarify. 

Here are some essential practices to ensure your fintech data visualizations are clear, compelling, and drive action:

1. Focus on clarity and conciseness: Your audience might not be data experts. Keep your visualizations simple and uncluttered. Highlight the most important message and avoid overloading viewers with information. For example, a cluttered dashboard with too many metrics and colors can overwhelm users and obscure key insights.

2. Choose the right chart type: Select the chart type that best communicates your data's story. Line charts show trends, bar charts compare categories, and pie charts showcase parts of a whole. Using the wrong chart type can lead to misinterpretation of data. For instance, using a pie chart to display time-series data would be ineffective.

3. Use color intentionally: Color can be a powerful tool to guide viewers' eyes and emphasize key points. Use color palettes strategically; avoid too many colors or confusing combinations. Consider accessibility and ensure colorblind users can understand the information. In the fintech industry, where data security is paramount, using color coding to highlight potential risks or fraudulent activities can be invaluable.

4. Emphasize storytelling: Data visualizations shouldn't exist in a vacuum. Use clear titles, labels, and annotations to guide viewers through your data's story. Context is crucial; briefly explaining the data and its significance. For example, a visualization showing a spike in loan defaults should be accompanied by an explanation of the potential causes and the actions taken to mitigate the issue.

Fintech visualization examples

Allocation vs earnings by department:

Capital allocation divides the company's money to fund its various activities.

This chart shows how much money is allocated to marketing, production, customer service, and IT and how much each department earns. This information can help a fintech business decide how to spend its money. For example, if the marketing department is bringing in a lot of money, the company may allocate more capital to marketing in the future.

Conversely, if the customer service department is not earning a lot of money, the company may decide to allocate less capital to it in the future. This type of visualization can be customized to track specific fintech business units, such as lending, investment management, or digital payments.

Here are some of the benefits of capital allocation for a fintech business:

• It helps the business track its spending across different departments or initiatives.
• It helps the business make informed decisions about how to allocate resources for maximum return on investment.
• It helps the business identify areas where it can optimize costs and improve profitability.

Capital allocation is a helpful tool for fintech businesses to manage their finances and make sound financial decisions.

Performing vs non-performing loan value:

This line graph shows the total value of performing loans compared to non-performing loans over time.

Performing loans are those where borrowers are making their scheduled payments. Non-performing loans are those where borrowers are behind on their payments or in default. This graph helps a fintech business track the health of its loan portfolio. A loan portfolio is all the loans a lender has issued.

By monitoring the ratio of performing loans to non-performing loans, a fintech business can assess its risk of loss. If the percentage of non-performing loans starts to increase, it could be a sign that the business is issuing too many loans to risky borrowers or that economic conditions are deteriorating, requiring adjustments to lending practices.

Here are some ways that monitoring performing vs. non-performing loans can help a fintech business:

• Identify trends in loan performance and take proactive measures to mitigate risk.
• Assess the risk of loss from loan defaults and adjust lending criteria accordingly.
• Make better decisions about future lending practices, such as adjusting interest rates or tightening credit requirements.

By understanding the health of its loan portfolio, a fintech business can make more informed decisions about its lending practices. This can help you avoid losses, improve your profitability, and maintain a sustainable lending model.

Loan amount by risk category:

This pie chart illustrates the total loan amount division among four risk categories: low, medium, high, and very high.

A pie chart like this helps a fintech business understand how much risk it takes with its loans. Lenders consider loans to borrowers in the "low" risk category as the safest, while they consider loans to borrowers in the "very high" risk category as the most risky. A fintech business can see how much of its portfolio comprises risky loans by looking at the pie chart.

This information is essential for a fintech business because it helps them to manage their risk. Risk management involves identifying, evaluating, and reducing potential losses. In the context of lending, risk management means avoiding issuing loans to borrowers who are unlikely to repay them.

By understanding the risk profile of its loan portfolio, a fintech business can take steps to mitigate its risk. Here are some ways a fintech business might do this:

• Charge higher interest rates on loans to borrowers in higher-risk categories to offset potential losses.
• Borrowers in higher-risk categories are required to make larger down payments to reduce the lender's exposure.
• Limit the amount of money lenders can loan to borrowers in higher-risk categories in order to diversify their portfolio.

A fintech business can protect itself from financial losses by managing its risk. This helps the business to be more profitable and sustainable in the long term, while also ensuring compliance with industry regulations and maintaining a responsible lending model.

Building interactive dashboards with DataBrain: Power up fintech with AI

Data visualization is critical to success in fintech, but building custom dashboards can be complex and time-consuming. 

This is where DataBrain steps in. DataBrain is an AI-powered Business Intelligence (BI) tool enabling fintech businesses to create and embed interactive dashboards easily.

DataBrain simplifies data visualization for fintech by:

• Drag-and-drop interface: DataBrain's intuitive interface allows anyone to drag and drop data elements to build informative dashboards regardless of technical expertise.

• Secure and scalable platform: DataBrain provides a robust and scalable platform that keeps your sensitive financial data safe while accommodating your growth.

• Self-service analytics: Empower your team. DataBrain fosters a culture of data-driven decision-making by allowing everyone to explore data and gain insights independently.

• Drill down for deeper insights: Don't settle for surface-level information. DataBrain's interactive dashboards allow you to drill down into specific data points to uncover deeper insights and pinpoint areas for improvement.

• Real-time monitoring: Stay on top of your performance with real-time data monitoring. DataBrain's dashboards update automatically, giving you the most current information to make informed decisions.

With DataBrain, fintech businesses can create clear and insightful AI-Powered dashboards that:

• Track key metrics like CAC, CLTV, and NPS in real time.
• Identify trends and patterns in customer behavior.
• Monitor risk and detect fraud attempts proactively.
• Gain a deeper understanding of customer needs and preferences.

Unleash the power of data in fintech

By leveraging AI-powered data analytics tools like DataBrain, you gain a deeper understanding of your business, identify areas for improvement, and make data-driven decisions that drive growth. Don't let valuable data sit unused.

Start building your own interactive analytics dashboards with DataBrain's user-friendly platform. Explore the sample fintech dashboard we provided to see the power of data visualization in action.

Ready to take control of your fintech data and unlock its potential? Contact us today to learn more about how DataBrain can empower your business with secure, scalable, and insightful data visualization solutions.