How Wealth Intelligence Supports Your Targeted Support Proposition

Purpose-Built Data for COBS 9B Compliance

Wealth Intelligence was designed from the ground up to provide the independent behavioural evidence that firms need to build, validate, and monitor targeted support segments under PS25/22. Unlike generic market research or survey data, every aspect of the Wealth Intelligence dataset is structured to map directly to COBS 9B requirements.

This article explains exactly how our data supports each stage of the targeted support lifecycle.

The Three Pillars of COBS 9B

The targeted support framework rests on three requirements, each of which demands specific types of evidence:

Pillar 1: Segment Design

Wealth Intelligence provides cross-provider behavioural data across six dimensions of the wealth lifecycle:

• Pension contributions and drawdown: Pot sizes, contribution patterns, withdrawal timing, tax-free cash decisions, and drawdown purpose across 57+ providers
• ISA behaviour: Wrapper preferences (Cash vs. Stocks & Shares), deposit patterns, transfer intent, and provider switching behaviour
• Credit and borrowing: Mortgage behaviour, credit utilisation, debt-to-income ratios, and credit management patterns
• Insurance and protection: Coverage needs, protection gaps, risk appetite indicators
• Inheritance and estate planning: Gifting behaviour, IHT threshold modelling, intergenerational transfer patterns
• Investment and platform behaviour: SIPP contributions, risk preferences, platform selection, and switching patterns

This breadth allows firms to identify common characteristics that span the full financial lifecycle, not just the products they happen to offer. When you define a segment as “consumers who are actively modelling drawdown while also carrying significant mortgage debt,” Wealth Intelligence provides the cross-provider evidence that this combination of characteristics defines a genuine consumer group.

Pillar 2: Segment Validation

Validation is where most firms struggle, because it requires evidence that your segments are not simply a reflection of your own product architecture. Wealth Intelligence supports validation by:

• Independent clustering: Our data reveals natural consumer groupings that exist across the market, regardless of which provider a consumer uses. You can test whether your internally defined segments align with market-wide behavioural clusters
• Excluding characteristic evidence: We provide quantitative evidence that the characteristics separating your segments are genuinely discriminating in market-wide data, not just within your book
• Methodology documentation: Every Wealth Intelligence delivery includes methodology documentation that explains data collection, aggregation, and anonymisation processes, providing the audit trail the FCA expects

For example, if you define an excluding characteristic as “consumers with transfer intent above 20%,” Wealth Intelligence can confirm whether that threshold meaningfully separates distinct behavioural groups in cross-provider data, or whether it is an arbitrary cutoff that happens to work in your book.

Pillar 3: Outcome Benchmarking

The “better position” test requires a benchmark against which to measure outcomes. Wealth Intelligence provides:

• Market-wide cohort benchmarks: Outcome metrics for comparable consumer groups across the market, enabling firms to demonstrate that consumers receiving targeted support are performing better than market peers
• Segment-level monitoring data: Ongoing behavioural data that tracks whether segment compositions and behaviours are stable, or whether recalibration is needed
• Trend analysis: 13+ months of longitudinal data showing how consumer behaviour is evolving, enabling proactive adjustment of targeted support propositions

How Our Data Is Different

Three characteristics make Wealth Intelligence distinct from other external data sources:

1. Behavioural, not survey: Every data point reflects a real consumer decision captured through financial modelling tools — not a survey response or stated preference. This matters because the FCA expects evidence based on observable behaviour
2. Cross-provider by design: Our modelling tools are provider-agnostic, capturing behaviour across 57+ providers. Consumers using our tools are actively comparing and modelling across the market, producing inherently cross-provider data
3. 100% first-party: All data is collected directly from consumer interactions with our own tools. There is no third-party data resale, no panel estimation, and no modelled or imputed data. The provenance is clean and auditable

Delivery and Integration

Wealth Intelligence data is available in formats designed for practical integration into your targeted support workflow:

• Segmentation-ready datasets: Pre-structured data organised around COBS 9B requirements, with segment-level aggregations and characteristic profiles
• Raw behavioural feeds: Granular, anonymised behavioural data for firms that want to run their own clustering and analysis
• Benchmark reports: Periodic reports comparing your segment outcomes against market-wide cohorts
• Methodology packs: FCA-ready documentation covering data provenance, collection methodology, anonymisation processes, and regulatory alignment