Best practices for chatbots in consumer finance

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The influx of artificial intelligence (AI) and machine learning has sparked the widespread adoption of chatbots as an economic solution for customer support, particularly in financial services.

Although these tools offer potential efficiencies, the Consumer Financial Protection Bureau (CFPB) has outlined key concerns, including the issue of dark patterns - these are defined as manipulative design practices that have grown in scale and sophistication, creating more challenges for consumers.

Here, we explore how chatbots are used today along with their challenges, and how to mitigate associated risks and dark patterns in consumer finance.


Driven by AI algorithms, chatbots are fast becoming an integral part of consumer finance. Their use is now widespread across the industry.

1 in 3 of the U.S. population interact with a bank chatbot - this is only expected to increase.

However at a time where technology is rapidly evolving, institutions must think critically about how to implement these tools ethically and appropriately. The CFPB presented multiple challenges associated with using chatbots which includes, handling complex issues and disputes, obstructing human support, presenting security risks, potential non-compliance with laws, diminishing customer service, and the emergence of dark patterns.


Chatbots are a great solution to providing an accessible and efficient customer service platform across all industries, especially in financial services.

Unlike other industries, financial institutions have to create an additional layer of trust, security and transparency with their customers - a critical factor when considering any new customer service tool.

Chatbots, which simulate human-like responses using computer programming, were introduced in large part to reduce the costs of human customer service agents.

Consumer Financial Protection Bureau, Jun 23

The overarching benefit from using chatbots is cost-effectiveness. Their ability to process a high volume of requests by dealing with simple inquiries like balance checks, fund transfers, or basic financial queries, allows human customer service agents to focus on the more complicated tasks.

At a time where all businesses need to make sustainable economic decisions, these tools can seem increasingly appealing.


Complexities and disputes

Chatbots often struggle with complex issues, particularly disputes. Ultimately, their ability to understand nuanced contexts and specific circumstances surrounding a dispute needs enhancement, before they can safely handle more than basic requests.

Barrier to human support

We’ve all been there. An overreliance on chatbots can result in a frustrating customer experience, creating obstacles to accessing real support when you need it. This can lead to “doom loops,” a term that you’ll recognise if you’ve been repeatedly routed through ineffective bot responses, causing anxiety, frustration, and wasting valuable time.

Security risks

They can also present considerable security risks. Impersonation scams, system reliability issues, and the necessity to secure customer data all present substantial challenges to maintaining the integrity and safety of financial systems and personal information.

Dark patterns

Dark patterns are deceptive interfaces designed to trick users into actions they might not intend. Think of when you’ve signed up to a new contract and there’s a surprise charge debited one day - you think it must be a mistake, but it was in your contract the entire time, hidden behind complex designs or misleading UI.

The same experiences are unfortunately seen across chatbots through complicated responses and URLs. These dark patterns can mislead consumers, resulting in unintended consequences, like sharing sensitive data or consenting to unwanted services.

Compliance and service quality risks

Using deficient chatbots or employing dark patterns can quickly lead to non-compliance with laws, a decrease in customer service quality, and, ultimately, harm to the consumer. Businesses must ensure their chatbot systems are robust, reliable, and transparent to avoid legal consequences and customer dissatisfaction.

How to effectively manage the risks

Balance automation with human support

Striking a balance between automation and human support is essential. Easy access to human agents for complex issue resolution, which chatbots cannot effectively handle, must be guaranteed.

Improve capabilities

Advancements in AI will enhance chatbot capabilities and address their current limitations. This includes their ability to handle complex queries, understand context and language nuances, resolve disputes, and avoid the use of dark patterns.

Strengthen security

Robust security measures and investment in advanced fraud detection systems are vital for:

  • Preventing scams
  • Ensuring system reliability
  • Safeguarding customer data

Ensure compliance, service quality, and transparency

To maintain high service quality, regulatory compliance, and transparency, financial institutions should rigorously test chatbot systems before launch and continually monitor their performance. This also means ensuring chatbots do not employ dark patterns.

Google ratings as a risk mitigation and customer satisfaction indicator

High Google ratings can be used as a risk mitigation tool for institutions using chatbots. These ratings point to positive customer experiences, demonstrate effective management of chatbot-human interactions, proper dispute handling, and quality customer service.

Strong ratings also suggest avoidance of deceptive “dark patterns,” a sign of transparent and ethical practices that consumers trust. It also enhances perceived trustworthiness for institutions or debt collection agencies, creating more comfortable customer interactions.

An institutional culture that strives for positive Google ratings will promote constant monitoring and improvement of chatbot systems, security measures, and service strategies. However, these ratings should be viewed in parallel with other performance metrics to assess effectiveness and holistically identify improvement areas. This balanced approach ensures that institutions continuously provide reliable, high-quality customer services.

Final thoughts

While chatbots present cost-efficiency and time-saving benefits, their limitations, the risk of dark patterns, and potential failures underscore the critical role of human customer support, especially for complex financial issues.

As their utilization extends into specialized areas like debt collection, the potential for consumer confusion or harm may increase. Consequently, significant oversight is essential to ensure they function optimally and ethically within our industry.

Debt collection agencies can leverage chatbot benefits to effectively manage simple inquiries, freeing up human agents to handle more complicated tasks. However, it’s crucial to establish a seamless transition from automated to human support upon customer request to address any misunderstandings that arise in these critical conversations. This ensures that customers feel heard, respected, and focused on finding resolution. Ultimately this enhances the customer experience, and improves overall collections.

Risk management measures have to be rigorous. This includes continuously enhancing chatbot capabilities, implementing robust security and fraud detection systems, maintaining transparency, and ensuring full compliance with the laws and regulations of debt collection practices. Critically, agencies must proactively mitigate the risk of dark patterns, so that chatbots do not employ manipulative techniques that could deceive or harm consumers.

A combination of human and automated services with robust oversight and risk management can lead to a more efficient, ethical, and successful debt collection process. While chatbots are undoubtedly becoming a significant part of consumer finance, their implementation must be done thoughtfully, responsibly, and clearly committed to protecting consumers and enhancing their financial journeys.

By Tim Collins, General Counsel

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