Exploring Authenticity, Accuracy and Bias in Emotion Recognition Systems

Posted by Ian McKenna | Oct 16, 2025 | Smart Systems | 0 |

In reading this article you will understand:

How emotion recognition systems function and their limitations.
The ethical, regulatory and data protection implications of using such tools in client interactions.
How to apply due diligence when assessing technology providers.
Integrating emotion insights responsibly within a human-led advice process.

No analysis of artificial intelligence is comprehensive without considering areas like bias. Emotion-recognition Artificial Intelligence (AI) promises helpful insights during client conversations. But advice depends on trust, clarity, and fairness. This article builds on themes raised earlier in this series and adds deeper guidance on due diligence, training data, and how far advisers can rely on tools they already own. It now also includes references to independent research and regulatory guidance to validate the discussion.

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About The Author

Ian McKenna

Ian founded Financial Technology Research Centre in 1995 nearly two decades before “FinTech” became part of the industry lexicon. A boutique consultancy the firm focuses on how personal finance organisations can communicate more effectively with their customers and help them take better financial decisions. As part of this work the firm work with many of the U.K.’s leading long-term savings institutions, financial advisers and technology providers to identify emerging technologies that can transform customer relationships. More recently the firm has added its own InsureTech and RegTech ventures to help advisers ensure they help consumers find the life insurance and workplace pensions solutions that best meet the needs. In addition to developing a UK view Ian travels extensively to identify similar trends around the world and the lessons that can be learned from other countries.