How to ensure ethical AI in financial services

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AI effectively manages key business processes. But it can also lead to biased decisions. What can financial companies do to mitigate the risks and reap the rewards?

By Gery ZollingerHead of Data Science and Analytics, Avaloq

Artificial intelligence is a combination of machine learning and real-world big data. But this data may contain biases – explicit or implicit – which can be learned by the AI ​​system. In some areas, including human resources, using historical data to train machines can reinforce common human biases.

Thus, when designing an AI system, it is important to identify high-risk areas of the business and define a clear plan to continuously monitor and train the AI ​​engine. By understanding the risks, companies can mitigate potentially unethical outcomes and maximize the benefits of AI in their business.

What are the implications for financial institutions?

The use of AI is becoming more prevalent in financial services, and the pressure to integrate AI into business processes to gain competitive advantage is immense. At the same time, regulations have significantly retarded innovation, so it can be difficult for financial institutions to find guidance on AI best practices.

The European Commission (EC) is one of the first regulators in the world to produce a draft proposal on the use of AI. It ranks AI activity by risk, from unacceptably high risk to minimal risk, with credit lending, for example, being classified as high risk due to the potential for harm.

Read Avaloq’s full report on ethical AI in finance here.

This proposal will likely serve as a model for similar regulations in jurisdictions such as Switzerland and Singapore, so financial institutions around the world should take note.

Could you share some use cases of AI in the financial sector?

The traditional use case for AI systems in finance is to automate and standardize routine tasks, allowing companies, such as wealth managers, to focus more on improving their value proposition and strengthening relationships with their customers. But today, AI is able to do much more.

For example, financial institutions can now leverage AI to instantly create personalized portfolio recommendations based on investors’ risk appetite and goals. Another innovative area is conversational banking, where AI systems use natural language processing (NLP) to interact with customers and understand their intentions. It goes beyond just improving efficiency – it improves the customer experience and drives engagement.

How can financial institutions make the most of AI?

To maximize the value of AI, companies need a partner who understands the technology behind the system, the regulatory landscape, and the financial industry as a whole. AI should be paired with a robust monitoring system to constantly improve performance as well as identify and correct any potential shortcomings, including unethical results.

And in line with EC recommendations, AI systems should only be used in low-risk areas – such as investment recommendations, customer churn predictions and chatbots – to minimize the severity of anything. unfair bias. By combining these factors, financial institutions can use the efficiency of AI to gain a competitive advantage while ensuring fair outcomes for their customers.


  • For more information on ethical AI in the financial sector, please see Avaloq’s latest news page.


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