Measuring Behavioural Change That Matters

Greg B Davies

Head of Behavioural Finance

Join Greg Davies and explore how behavioural interventions can be measured for real impact on decision-making. Learn how smart metrics, ethical AI, and regulatory rigour ensure progress that lasts.

Wealth Management

Join Greg Davies and explore how behavioural interventions can be measured for real impact on decision-making. Learn how smart metrics, ethical AI, and regulatory rigour ensure progress that lasts.

Subscribe to watch

Access this and all of the content on our platform by signing up for a 7-day free trial.

Measuring Behavioural Change That Matters

12 mins 48 secs

Key learning objectives:

Define what constitutes effective behavioural measurement
Identify key metrics that capture decision quality, not just activity
Compare different evaluation methods, from A/B testing to machine learning
Explain how ethical and regulatory standards shape behavioural measurement

Overview:

Measuring behavioural interventions is not about counting clicks or short-term activity; it’s about understanding whether interventions genuinely improve decisions and outcomes. That requires moving beyond surface metrics to track patterns, long-term resilience, and the absence of harmful behaviours such as panic selling. While A/B testing and RCTs offer rigour, they are limited in complex, personalised environments. Machine learning enables adaptive, real-time measurement that captures what works, for whom, and in which context. Done responsibly, with transparency, data minimisation, and privacy safeguards, behavioural measurement builds trust, demonstrates compliance, and ensures interventions support lasting progress, not just temporary activity.

Subscribe to watch

Access this and all of the content on our platform by signing up for a 7-day free trial.

Summary

Why is measuring behavioural interventions difficult?

Behavioural interventions often create surface changes, like more clicks or quicker responses, that may not reflect genuine improvement. Seasonal patterns, market shifts, or self-selection effects can all mask true impact.

The real challenge is distinguishing activity from progress: are clients genuinely more resilient, or just temporarily nudged?

What behavioural metrics matter most?

Meaningful indicators include drop-out rates, hesitation points, depth of interaction, use of behavioural tools, and redemption patterns during volatility. These metrics highlight not just what clients do, but how they engage and whether their behaviour aligns with long-term stability.

Interpreting them requires context, for example, fewer logins might mean disengagement, or it might mean greater confidence.

How can firms evaluate interventions effectively?

Traditional methods like A/B tests and RCTs offer rigour but struggle with personalisation and emotional variability. Machine learning provides greater adaptability, analysing thousands of signals to detect subtle patterns and personalise interventions at scale. Used together, these approaches allow both broad testing and fine-grained, real-time insight.

How should firms handle attribution and ethical concerns?

Behavioural changes often overlap with market events, making attribution complex. Longitudinal tracking helps separate noise from trend. Ethical measurement requires data minimisation, transparency, and privacy-by-design, ensuring algorithms optimise for client welfare rather than short-term sales. Firms must explain clearly what data are collected, why, and how they’re safeguarded.

What are the regulatory and practical implications?

Under the FCA’s Consumer Duty, firms must evidence that communications and tools deliver good outcomes, not just activity. That means documenting why interventions are designed as they are, monitoring who they help, and addressing foreseeable harm. Practically, firms should expect phased deployment, cross-functional collaboration, and continuous calibration to embed behavioural measurement into real systems.

Subscribe to watch

Access this and all of the content on our platform by signing up for a 7-day free trial.

Greg B Davies

Greg B Davies is a behavioural finance specialist and Head of Behavioural Finance at Oxford Risk, a fintech company focused on building behavioural technology to help people make better financial decisions. He started the first behavioural finance team at Barclays back in 2006 and has been working in this space for nearly two decades. He holds a PhD in Behavioural Decision Theory from Cambridge, and has spent his career turning academic insights into practical tools, such as measuring risk tolerance and designing nudges. He is also the creator of The Art of Behavioural Investing, a course designed to help everyday investors build better habits.

There are no available Videos from "Greg B Davies"