What our invited experts talked about at a breakfast on targeted support and personalisation.
The FCA’s Targeted Support guidance is set to reshape how financial services firms interact with their customers.
This initiative is aimed at improving outcomes for people who don’t take financial advice. But it also opens up a strategic opportunity for the whole sector. That’s because firms can start to use more personalised, needs-based engagement to boost satisfaction, loyalty, and conversion at key moments. The challenge for the industry will be finding the right balance between innovation and compliance.
At our recent breakfast event held in partnership with Planda.ai, invited guests from across the pensions and financial services spectrum debated some of these issues.
We were joined by Monica Kalia and Sam Brown of Planda, and special guest speaker Dr Philip Courtenay of Humans & Money.
We covered a wide range of topics, but here are some of the highlights:
Personalisation needs good data
Technology capabilities have been transformed in the last 2 or 3 years as AI has improved and been adopted more widely. This means that hyper-targeting at a scale that was previously impossible is now possible. But poor quality data creates shaky foundations for the decisions and content that are built on it. While it’s exciting to think about the vast amount of data that we can make use of with these new tools, more important than how much data you hold, is how accurate it is.
Data is bigger than demographics
The most common approach to building data sets for personalisation focuses on things like pot size and demographics. That misses the opportunity to use behavioural data – information about people’s emotional relationship with money and their past financial behaviour. Building communications and interventions on behavioural data can unlock the behaviour change so many businesses are looking for.
However, this data can be hard to collect. People don’t always share their fears and feelings in a questionnaire. They share things in conversations. So one way to get high quality personal data might be to capture what people say out loud, not just what they write on a form. Modern tech can achieve this, with the ability to have conversations at scale, perhaps conducted and analysed by AI.
Trust depends on more than technical competence
Research shows that financial education rarely leads to a change in actual behaviour, even if knowledge increases. It’s not enough on its own – we also need to address emotional and practical barriers to dealing with money well. A major barrier is the lack of trust in financial services. To build it, we need to show that we’re competent, transparent, and acting in customers’ interests. If targeted support becomes perceived as just another channel to upsell, it will lose trust quickly.
People like AI because it doesn’t judge them
Financial topics are the second most popular queries on ChatGPT. (The number one topic is health.) This has a lot to do with people feeling embarrassed asking wealth advisors or employers basic questions, preferring AI’s non-judgmental interface. Around two-thirds of adults feel anxious about engaging with financial professionals; digital channels can remove the fear of judgment and the emotional burden of admitting your ignorance about money.
Despite all the industry’s efforts, people still trust friends, family and “people down the pub” more than financial services companies. When told to “get financial advice,” many people’s response is simply “from where? Who do I ask?”. AI plugs into this mindset, managing to feel like a trusted friend.
Regulation may clash with personalisation
True personalisation isn’t just about static segments that you set and forget. It’s about making strategic communication decisions every time. Segments need to evolve with customer lifecycles and campaign goals rather than remaining fixed.
Targeted support will operate under regulatory rules which are likely to limit how personalised the experience can be. So there is a risk that the regulated portion around targeted support could feel at odds with the fluid nature of real customer journeys. This will be a new version of the familiar, delicate balancing act between being helpful and being compliant.
Be guided by data, not product development
A successful approach to targeted support needs to start with users to design products and journeys, rather than creating products and then seeking validation for them. Building these propositions is going to need cooperation across functions that can traditionally be rather siloed. There’s scope for industry-wide cooperation on this, as organisations face common challenges around data quality, regulatory constraints and customer trust.
Conversational AI presents an opportunity to scale the feeling of being listened to – something usually limited to the 9% who take financial advice. Targeted support could fill the crucial gap between general guidance and full advice, providing direction to those who need it most. The key lies in creating experiences that feel genuinely helpful rather than another initiative or intervention that the poor end users need to navigate.
