Lesley Li
Market and investor insight
More than a decade in financial services, connecting sustainable-investment intent with real investor needs.
Meet Lesley →Evidence. Explanation. Testable action.
Three connected layers take a team from structured investor signals to a change it can measure. AI may improve the prose, but it never invents a finding.
01
Profile
An evidence-informed, continuously calibrated model of competence × ambiguity tolerance. Nine memorable profiles help explain patterns without turning them into fixed personality types.
02
Diagnose
Compare cohorts, journey stages and calibration gaps. A curated library turns detected patterns into ranked candidate hypotheses, clearly labelled as explanations to investigate, not causes already proven.
03
Test
Design a specific intervention for a named segment, with an agreed outcome and review point. If the cohort does not move as expected, the evidence changes the hypothesis rather than being explained away.
Three ways to put the insight to work
Choose the route that matches the moment: improve a real investor journey, activate a live audience, or bring the thinking to your stage.
01 · Implementation
Build it into the investor journey
Apply the assessment to a defined cohort, diagnose patterns and turn the findings into interventions your team can test.
Explore implementation → 02 · Event activationLet the room experience it
Run a branded live assessment with private individual results and an anonymised cohort conversation.
Explore event activations → 03 · SpeakingPut investor behaviour on the agenda
Invite Lesley for a keynote, panel, workshop or hosting brief shaped around the audience in the room.
Explore speaking →After the diagnostic
And it keeps working between every diagnostic
For implementations that continue beyond the assessment, behavioural nudges and AI-assisted advisor support can carry the insight into the moments where decisions are made.
Always-on layer
Behavioural nudges, always on
Once we know the archetype and the blindspot, we deliver tiny, contextual interventions in the channels your client already uses, such as checking a balance, opening the app or reading the newsletter. Each nudge is measured. The next diagnostic sees what landed and what didn’t.
One investor view
Chat, survey, portfolio: one advisor view
Your AI copilot or human advisor sees every relevant signal at once: what the client revealed in the assessment, what their portfolio actually holds, what the conversation just surfaced. No more tab-switching between tools. It is one coherent investor view, built on the open Model Context Protocol (MCP) standard.
Product experiences
Behaviour-aware fund exploration
Three exploration surfaces we’ve shipped, designed around how humans actually navigate uncertainty, not how databases serialise. They’re examples, not the menu: we continuously design new ways for investors to engage with their money.
Star Map
Funds as a navigable universe
Eight hundred line items collapse into thirty stars, clustered by what the investor actually cares about. Decision fatigue drops; orientation appears. Choice architecture, applied to the fund universe.
Radar
What the client picks reveals what they value
Configurable axes for “distance” and “size” include ESG fit, ten-year return, drawdown and ticket size. As the client adjusts the lens, the interactions themselves become a behavioural signal, feeding the next session with what they actually look at.
DNA Helix
What the money is actually doing
Each fund becomes a double helix coloured by its top SDGs, drillable down to constituents. Investors stop seeing tickers and start seeing impact. The shift from abstract to concrete is itself a confidence intervention.
Three surfaces built on the same logic as the diagnostic: visuals that respect how humans actually think, paired with nudges that arrive in the moments choices are made. The result is exploration that closes the intention–action gap instead of widening it.
Built for the people asking the question
Wealth managers, fintech product teams and investment platforms: if you have a board, a roadmap or a quarterly conversion review, this is built for you.
Wealth managers & private banks
Understand your client base by investor archetype. Activate higher-conviction segments. Measure conversion uplift by profile and blindspot pattern.
Financial-services product teams
Embed client profiling into onboarding. Segment nurture by archetype. Ship targeted journeys with a measurement loop instead of A/B guessing.
Distributors & platforms
Run board-grade diagnostics on a customer cohort, including activation gaps, drop-off stages and archetype skew, then export the intervention as a brief, not a slide.
Why this isn’t another quiz tool
Research rigour first. AI amplification second. In that order, on purpose.
Three sources of signal
Self-report, objective knowledge checks and standardised hypothetical scenarios contribute different evidence. No single question decides the profile.
Blindspot detection
We compare confidence with demonstrated knowledge, and stated comfort with scenario choices. The result is a possible calibration gap, not a claim about hidden truth.
Deterministic scoring
The classifier is rules-based and reproducible. Same answers, same result, every time. AI may write the narrative, but never the numbers.
Continuous calibration
We review the model after every survey project and at regular intervals as new aggregate data becomes available, updating it where the evidence supports a change.
See the thinking behind the product
Trust should not depend on a claim alone. Explore the method, the people responsible for it, and the evidence that informs our work.
Methodology
What we measure and what we do not
Inputs, scoring, calibration, AI boundaries, limitations and appropriate use.
Explore the method → LearnFinancial investment behaviour, with its evidence attached
How knowledge, confidence, uncertainty, trust and the decision environment interact.
Read the field guide → PeopleResearch, finance and delivery experience
Meet the founders responsible for turning the research into a working assessment.
Meet the team →Built by people who can challenge each other
Market insight, research architecture and delivery discipline in one founding team.
Dr Clemens Chaskel
Platform and research
Global innovation strategy, applied research at the Institute for Manufacturing, University of Cambridge, and experience founding InnovationFlow.
Meet Clemens →
Alistair Hume
Delivery and methodology
15+ years delivering finance, data, systems and regulatory change across banks and start-ups.
Meet Alistair →Ongoing partnership
Partnering with NTT DATA
We went live together at Mirai 2026 in London, bringing investor profiling to a live audience. Our partnership continues beyond the event as we explore how behavioural insight can support more relevant and engaging financial experiences.
Mirai 2026 milestone · 9–10 June · London
Bring us a question your board keeps asking.
We’ll show you what the answer looks like through evidence, explanation and a testable next step, using a real cohort of yours.
Bring us the question