UX Patterns That Make AI Fintech Products Feel Safe

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In the AI era, trust is a valuable currency. AI-powered products should prioritize a reliable digital experience, as AI can often trigger uncertainty or even fear, especially in financial operations.

Trust is at the heart of fintech, where sensitive data protection and strong security are essential. Once broken, trust is difficult to restore. That’s why every user interaction on your website or app should convey transparency and security. 

Users need to feel confident that your product is reliable and delivers on its promises. 

Let’s explore how to design a trustworthy AI UX for a product that feels safe, transparent, and reliable.

Why users don’t trust AI in fintech products

According to a KPMG report, 67 % of people report low to moderate acceptance of AI. The main reasons for such distrust are:

• Cybersecurity concerns
• Its potential to affect and sabotage people and business decisions
• No regulation

AI can sometimes feel unpredictable, make obvious mistakes, or produce inaccurate results. That may be acceptable for low-impact, routine tasks, but it becomes far more concerning when AI decisions go wrong and impact your finances.

Here are the other reasons why people may not trust your AI fintech product.

Lack of transparency

AI still remains a black box for most people. Many don’t know when or how to use it to get the best results, while others expect it to work perfectly and end up disappointed.

• AI decisions often appear as a “black box,” offering little to no explanation or proof behind the outputs it generates

• Users can’t understand why a recommendation or action happened and whether they can trust it

• Without context, people assume AI might be biased

For example, AI is great at detecting any anomalies in financial operations and flagging transactions that may look suspicious. At the same time, it often struggles to explain why a particular decision was made.

Fear of errors and financial harm

If an AI model makes serious mistakes, it can lead to fines, loss of trust, and reputational damage. For example, if a financial transaction is mistakenly blocked, the business will be held responsible. 

That’s why many organizations don’t want to take responsibility for AI decisions gone wrong and resist relying on AI.

Perceived or real bias

When AI is trained on old or unstructured datasets without human oversight, it can reproduce biases. For example, a first name can unintentionally reveal or suggest a person’s gender or a surname can hint at a person’s ethnicity or background.

Even if an AI system is not supposed to consider gender or ethnicity, it may use names as indirect signals (proxies). As a result, credit scores or decisions may be influenced in biased ways. Such biases are unacceptable to regulators, as financial decisions must be objective and free from bias.

Data privacy concerns

AI often processes personal and sensitive data without user intent or explanation of exactly how this data will be used. That’s why it’s essential to provide a clear opt-in policy and give users full control over their personal data.

Best practices of UX design for fintech AI products

According to research, the word “AI” alone can trigger fear and reduce the likelihood of conversion. That’s why successful AI fintech products should not only solve the user problems but also address all the concerns when it comes to transparency, trust, safety, and data protection. 

Let’s take a look at the best UX practices for fintech AI products. 

Define the friction points in the user journey and whether AI can really help overcome them

Before designing any AI fintech product, you have to answer the following questions:

• What are the possible friction points in the user journey?
• How can we address any user journey points that could trigger concerns about data privacy and protection with AI? 
• Can AI really make a difference?
• Does AI improve the user journey or make it more complex?

Remember that AI is not the product’s main value proposition. Companies should always put the user first, not the technology, and explain exactly how AI will help achieve a specific goal and make the user’s life easier.

Give user a sense of control

While AI automates many routine tasks, users are hesitant to use products that leave them fully out of control. 

One of the main patterns in AI product design is to find a balance between humans and technology, and to let users control when and how they use AI. 

Use automation for tedious tasks users want to get rid of (those that take a lot of time and effort). In other cases, it’s better to use augmentation, when AI increases the efficiency of the tasks users want to be involved in but doesn’t fully take them over.

Decide on the degree of automation

Depending on the context and the complexity of the task to be automated, decide what level of automation is needed. 

For example, if it’s a low-risk task, such as monthly budget planning or financial management tips, you can choose full automation based on a predefined set of rules.

If your product involves complex financial operations that require human oversight, it’s better to go with partial automation (where the user controls and changes the AI output) or choose an option where the AI provides suggestions and tips, with the decision remaining up to the user.

Use chain of thought pattern

CoT display is a UX pattern that shows a step-by-step process for how AI arrived at its conclusions. 

Since many AI outputs come from the dark, with CoT display, users understand the process behind the AI model’s answers. This is how you can use this pattern:

• Show the progress bar and output processing steps, so the user understands that AI is generating answers and how exactly the process looks like
• Show the confidence level of AI
• Provide clear and accessible explanations of how exactly AI-generated answers
• Provide the data sources where possible

Make sure that your product is inclusive, transparent, and free of biases

Ensure your AI product treats all people fairly and does not discriminate. This requires actively identifying and reducing bias in its training data, algorithms, and outputs, ensuring it does not disadvantage specific groups based on race, gender, or other characteristics.

• Use diverse, non-stereotypical imagery
• Ensure charts and colors are color-blind friendly
• Flag moments where users may feel powerless or judged
• Don’t auto-select AI recommendations for high-impact actions
• Avoid patterns that push users toward automated decisions

Examples of AI-driven fintech products that feel safe

We’ve cherry-picked a list of fintech products that smoothly integrate AI into their ecosystem, giving users a sense of security and trust.

Cora+ – a generative AI upgrade to the bank’s digital assistant

Cora is a digital banking assistant that helps customers answer bank queries through natural language processing and machine learning. It has already processed over 10.8 million banking queries for customers. Here’s how Cora+ balances human oversight and machine learning.

• When a customer service agent needs to step in, it provides a brief summary of the conversation, allowing the agent to quickly grasp the customer’s issue.
• Previously, queries about mortgages or loans would return generic links, forcing customers to navigate and filter information themselves. Cora+ now interprets the context of each question and provides more accurate answers, as well as the links to the sources

HiroFinance – a personal financial advisor

HiroFinance is a financial advisor that helps you plan and achieve your financial goals and build a financial plan in just a few minutes. 

When it comes to finance management and calculations, HiroFinance lets users inspect and verify all calculations

Their website has a dedicated section on data security and encryption. They explain how exactly they use anonymized data for internal analytics and business purposes and how the platform connects to financial institutions

Conclusion

As technology advances, more and more products will put AI at their core. However, earning user trust in AI-driven fintech requires designers to prioritize user needs over technology. 

In AI-first product design, the question shouldn’t be, “How can we add AI to our product?”. It should be “How can we design an AI-powered product that solves user problems and makes their life easier?”

At Teamvoy, we combine user-centric design and robust functionality for designing trustworthy AI interfaces. If you want to build a roadmap for your product design, don’t hesitate to contact us for AI consultation. We’ll explain how AI fits into your business and what data you need to design a product your users will trust.

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