AI-Tools in Financial Advice: Increasing Efficiency without losing Customer Proximity

Artificial intelligence is revolutionizing the financial sector - according to a recent PwC study, 73% of German financial companies are already using AI tools. However, a study by the University of St.Gallen warns of hidden risks: AI can distort investment decisions and increase portfolio risks. How can AI be used responsibly in financial advice without jeopardizing the personal customer relationship?

The most important facts at a glance

• According to the PwC study, 91% of financial service providers are planning to expand their use of AI over the next five years. At the same time, 84 percent of companies will increase their efficiency through artificial intelligence, while 63 percent will reduce costs.
• The UniSG study reveals critical findings: AI systems can increase investment distortions.
• FINMA-regulated providers , on the other hand, guarantee professional control of AI outputs. A hybrid approach combines technological efficiency with human expertise.
• Financial advisors are also turning to AI : to increase efficiency, process data and create content. However, the results should be treated with caution and the human element in the advisory process should not be underestimated.

AI penetration in the German financial sector

Sector	Use of AI (PwC 2025)	Main application	Growth rate
Insurance companies	78%	Operations, claims processing	7% compared to previous year
Banks	71%	Risk management, compliance	4% compared to previous year
Financial service providers	73%	Portfolio analysis, research	Average

The transformation is accelerating rapidly. While only 17% of German companies planned to expand AI within a year in 2023, according to PwC, this figure had already risen to 48% by 2024. However, these figures do not reflect the quality of implementation.

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The bias trap: when AI leads you astray

Professor Christian Hildebrand from the University of St.Gallen and his team examined the investment recommendations of three widely used large language models. The result is sobering: in all tests, the AI systems recommended riskier portfolios than established benchmark funds.

The algorithms showed systematic biases. They favored US markets, recommended expensive actively managed funds and underestimated portfolio risks. Particularly problematic: the AI systems presented their biased recommendations in a convincingly competent tone.

Typical AI biases in investment advice

• US focus leads to overweighting of American equities in global portfolios.
• Home bias reinforces local investment preferences without rational justification.
• Fee blindness favors expensive, actively managed funds over low-cost ETFs.
• Risk misjudgment systematically underestimates portfolio risks.

Even explicit instructions such as “I don’t want to pay any management fees” only had a limited effect in the study. The machines remained true to their trained patterns.

Useful AI applications for financial advisors

Despite these findings, AI offers enormous potential - if it is used correctly. The key lies in professional control and clear demarcation of the areas of application.

AI shines when it comes to process automation. Document processing , compliance monitoring and automated report generation can be automated efficiently. Artificial intelligence also speeds up processes considerably in customer onboarding and risk profiling.

AI reveals its true strength in data analysis. Market trend recognition, sentiment analysis and the evaluation of alternative data sources for investment research have never been possible with such precision. Risk management and fraud detection benefit from the ability of algorithms to recognize patterns in large amounts of data.

We summarize it like this:AI is like a racing car - incredibly powerful, but dangerous without an experienced driver.

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Respecting boundaries: Where humans remain indispensable

Area	AI suitable	Human expertise required	Justification
Portfolio construction	Supportive	Decisive	Strategic considerations, bias control
Client meetings	Preparation	Implementation	Empathy, complex life situations
Regulatory responsibility	Not suitable	Indispensable	Liability, legal assessment
Data analysis	Optimal	Validation	Speed, pattern recognition

Strategic investment decisions require human judgment. AI can provide data and identify patterns, but the final decision on portfolio construction andinvestment strategy belongs in experienced hands. Complex customer discussions, ethical assessments and individual life circumstances cannot be solved using algorithms.

Practical recommendations for action

The scientific findings can be translated into concrete steps. Financial advisors should critically evaluate AI tools by checking the origin and training methods of the algorithms and comparing recommendations with established benchmarks.

Customer transparency creates trust. Explain openly where and how you use AI. At the same time, clarify the limits and risks of AI systems. Show why human expertise remains indispensable.

Compliance must not be neglected. Carefully document all AI-based decisions. Regularly validate algorithm outputs and develop contingency plans for AI system failures.

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Future prospects: Innovation with responsibility

The future of financial advice does not lie in the choice between man or machine, but in the intelligent combination of both strengths. Generative AI will open up new opportunities - but only under professional control.

Technological innovation must be combined with regulatory compliance. Human expertise remains the key differentiator. Transparency and trust are the cornerstones of successful AI integration. Continuous training and quality control ensure sustainable success.

The St.Gallen University study provides an important warning: AI is a powerful tool, but not a panacea. If you want to use AI tools successfully in financial advice, you need more than just technology - you need expertise, control and a sense of responsibility.

Financial advisors who follow this path can take advantage of the efficiency benefits of AI without losing personal customer proximity. This is the future of Swiss financial advice: intelligent, but not inhuman.