Stanbridge Advisory
Financial Services Advisory
Working with CEOs in financial services and fintech to grow revenue and build shareholder value.
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Commercial Advisory
Revenue architecture. Commercial strategy. Valuation outcomes.
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AI Transition
Operating model redesign. AI-enabled performance. Structural adoption.
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Commercial Advisory · Financial Services & Fintech
Working with CEOs inside their businesses, not advising from outside them. Strategy, execution, and access, owned by one person accountable for the outcome.
The situation
The businesses that call me share a pattern.
Revenue has plateaued and the diagnosis isn't clear, the team is working hard but the numbers aren't moving
A valuation target exists but no credible commercial path to it has been mapped
Growth is happening but the infrastructure to sustain it hasn't been built, and the gap is widening as the business scales
A significant opportunity, new market, product line, strategic repositioning, isn't being captured
Strategy has been defined and signed off. Execution isn't translating it into change.
These aren't execution failures. They're structural ones, and they require a different kind of response.
What this is
Not a consultant. Not an interim. Something more directly useful.
The typical advisor delivers a diagnosis and a deck. The typical interim fills a seat. What I do is different: I operate inside the business alongside the CEO, carrying the commercial problem from first diagnosis through to structural change.
That means owning the work through the organisation, driving the cross-functional alignment it requires, and remaining accountable for what actually changes, not for the quality of the advice. The model is closer to a senior operator sitting inside the leadership layer than anything advisory in the traditional sense.
This approach comes from 15 years as an operator in financial services and fintech, building, scaling, and turning around commercial functions at MD level. The credibility isn't academic. It's operational.
How an engagement works
Entry
A direct conversation. If the problem is one I can help with, we agree a defined scope, specific outcome, clear timeline, and a shared understanding of what success looks like.
Diagnosis
Before anything is proposed, I form an independent view, commercial data, direct conversations with the people who know, and an honest assessment of where the constraint actually is. No assumptions carried in.
Inside the business
From that point, I'm operating inside the business alongside you. Not visiting to review and report. Present in the leadership layer, accountable for what moves, and what doesn't.
Execution
The work runs until the outcome is delivered. I drive the cross-functional coordination, own the delivery against milestones, and bring in external capability, people, partners, counterparties, where the engagement requires it.
Structural change
The objective is a change that holds after I leave, not an ongoing dependency. When the work is done, the business should be structurally different: better positioned, better performing, with the commercial infrastructure to sustain it.
When to engage
Critical Intervention
Something isn't working and resolution requires fast, decisive action. I come in, identify the real constraint, and drive the fix, operating alongside the CEO and leadership team until the situation is resolved.
Strategic Initiative
A defined outcome needs to be owned from decision to delivery. Not scoped and handed off, built, driven, and delivered end-to-end, with full accountability for the commercial strategy, the execution, and the access layer where needed.
Where I work
Primarily financial services and fintech, payments businesses, FX and treasury, regulated lending, transaction banking, and growth-stage fintechs backed by private equity or venture capital.
The specificity matters. Commercial problems in financial services carry regulatory, structural, and market dynamics that make generic advisory unusable. This model is built around that context, not applied to it as an afterthought.
Background
15 years as an operator inside financial services and fintech businesses, not in consulting.
That includes leading an 85-person division at MD level with full P&L accountability and FCA regulatory responsibility, building a regulated institution from four people to $6m+ revenue, and leading commercial repositioning across FX, treasury, payments, and transaction banking across Europe.
The reason this model works is that it comes from someone who has sat in these seats, who understands what it costs when strategy doesn't translate into execution, and what it actually takes to close that gap. That's not a positioning statement. It's where this came from.
Selected Work
Each situation is different.
These are representative engagements, drawn from PE-backed growth and turnaround environments where commercial and structural decisions are directly tied to valuation outcomes.
Not best cases. Typical ones.
Strategic Repositioning & Shareholder Value Creation
Context
Mid-size FX and risk management business. Well-capitalised, experienced team, but operating model capped at a fraction of potential value. Growth had stalled and the board had a valuation target with no clear path to it.
Insight
The business was competing on price in a commoditised segment of a market it was capable of leading. Its actual capabilities, client relationships, regulatory infrastructure, product breadth, supported a fundamentally more valuable proposition.
Intervention
First-principles capability review. Complete commercial repositioning from offshore spot FX provider to integrated financial solutions business. New entity formation pursuing regulated banking infrastructure. Rebuilt market positioning and client proposition from the ground up.
Outcome
£32m+ uplift in shareholder valuation, independently validated by the client's investment bankers. The repositioning created a commercially coherent platform for the next phase of growth.
Revenue Operations & Commercial Infrastructure Build
Context
Growth-stage financial services business. Revenue was growing, but without visibility, forecasting, or the structural foundation to sustain or accelerate it. The CEO and CRO had no unified view of pipeline, performance, or forward trajectory.
Insight
Growth was reactive, not managed. Commercial decisions were being made without the intelligence to make them well. The infrastructure needed to scale the business didn't exist, and the gap was becoming harder to close as the business grew.
Intervention
Full GTM review and structural audit. Built and embedded a Revenue Operations function from scratch. Redesigned compensation architecture, coverage models, and client segmentation. Introduced performance infrastructure and forecasting discipline across the commercial team.
Outcome
Return to 30%+ annual revenue growth, with rebuilt infrastructure providing a clear pathway to 50%+. Net new logo growth and materially improved conversion efficiency across all segments.
Divisional Revenue Turnaround
Context
Largest revenue-generating division of a regulated financial institution. 85 people. £36m revenue. In -40% year-on-year contraction. The division was the group's primary commercial engine, and it was failing.
Insight
The division was structured around legacy client profiles and coverage models that no longer reflected the firm's competitive strengths or the market it was actually competing in. The problem was architectural, not executional.
Intervention
18-month ICP transformation. Rebuilt GTM strategy, pricing frameworks, incentive structures, and origination model end-to-end. Built the full commercial leadership layer from scratch. Led international expansion and institutional desk build alongside the core turnaround.
Outcome
Reversed -40% contraction to +25% overall growth. 40% sales revenue growth. Average margin improved from 0.6% to 0.9% across the division, reaching 1.2% in top segments.
How I Work
The engagement model is built around accountability, not advice.
I operate inside the business alongside the CEO and leadership team, for as long as the work requires. I don't separate diagnosis from execution. Both happen together, and I remain accountable for what actually changes.
Three Layers
Strategy
Identifying the highest-value path. What needs to change, why it matters, and in what sequence.
Execution
Driving the work inside the organisation. Cross-functional ownership, leadership alignment, delivery against the outcome.
Access
Where the outcome requires capability that doesn't exist internally, people, partners, or counterparties, I bring it in. No misaligned incentives.
Types of engagement
Commercial Repositioning
Business is positioned below its potential valuation. The gap between capability and market perception needs to close.
Revenue System Redesign
Growth exists but won't scale. The commercial infrastructure needs to be rebuilt around what the business actually is.
Strategic Growth
A clear opportunity exists. What's missing is the structure to capture it, and someone to own the delivery.
Market Entry & Expansion
A new geography, segment, or channel, without the operating model to execute it credibly.
Capability Build
A critical commercial or product component is absent. It needs to be built, not described.
CEO Execution
Strategy has been decided. What's needed is someone to own the path from decision to permanent change.
Portfolio Application
This model applies at portfolio level.
For PE and growth equity investors, the same diagnostic rigour, execution framework, and access layer, applied consistently across portfolio companies. A repeatable mechanism for performance improvement, faster execution, and more defensible exit positioning built on operational substance rather than narrative.
I work with a small number of businesses at any one time. That is a deliberate choice, not a capacity constraint.
Strategic Access
Some outcomes depend on who you bring into the business, not just what you do inside it.
Internal change is often necessary. It is rarely sufficient. The businesses that reach their next valuation tier, or successfully enter a new market, almost always do so because the right person, partner, or counterparty was brought in at the right moment.
Key Strategic Hires
Identifying and securing the individuals whose presence materially changes what the business can do or become.
Senior commercial leaders, product and platform builders, institutional coverage, regulatory and licensing expertise.
Partnerships That Matter
Structuring and enabling the relationships that unlock growth or capability that doesn't exist inside the business.
Liquidity and banking partners, infrastructure and payment rails, embedded finance distribution, platform integrations.
Acquisition Target Identification
Identifying and shaping acquisition opportunities that are commercially coherent, not opportunistic.
Capability bolt-ons, market entry accelerators, product expansion via acquisition.
Exit Positioning & Buyer Identification
Understanding the right buyer universe and positioning the business to attract it at the right moment.
Strategic buyers, financial sponsors, platform acquirers.
I don't act as an intermediary or run formal processes. But where access is critical to the outcome, I help bring the right people, partners or counterparties into the situation, and ensure it serves the commercial objective, not a transaction.
AI Transition · Financial Services & Fintech
Working with fintech and financial services CEOs to restructure how the business operates, with AI embedded as a permanent capability layer, not a pilot that never scales.
The situation
The pattern in financial services and fintech is consistent.
AI is on the board agenda, but hasn't moved past the pilot stage, and the gap between what was promised and what exists is widening
Processes that should be automated are still manual, consuming time, generating errors, and limiting the business's ability to compete on cost and speed
Data exists across the business but isn't connected to the decisions it should be informing
A competitor has deployed something that changes the cost structure or client experience, and the response plan isn't clear
AI spend is rising but competitive position isn't improving, capability is being built without a clear connection to commercial outcomes
The problem is almost never technical. It's structural, where AI sits relative to the operating model, and who owns making it real.
What this is
Not a technology project. Not a consulting engagement. An operating model change.
Deploying AI tools is the easy part. The hard part is restructuring how the business operates around them, the workflows, the data architecture, the decision-making layer, and the commercial logic that determines what the business can now compete for.
I work inside the business with the CEO and leadership team, operating at the level where commercial intent and operational reality meet. I own the transition from commercial brief through to embedded adoption, as the person responsible for both the design and the delivery, not just one or the other.
Technology is always in service of the operating model, never the other way around. The outcome isn't a tool that's been installed, it's a business that works differently.
How an engagement works
Entry
A direct conversation about what the business needs to do differently. If the problem is one I can help with, we agree a defined scope, specific outcome, clear timeline, shared criteria for success.
Diagnosis
Before any solution is proposed, I form an independent view: where the manual effort is concentrated, what the data shows, what the real constraint is. No assumptions carried in. The diagnosis drives the design.
Inside the business
I operate inside the business from that point, working directly with the CEO, the leadership team, and the operational functions affected. Not advising from outside. Accountable from inside.
Execution
Design, implementation, and adoption, driven end-to-end. I bring in the technical capability the work requires, manage it entirely in the client's interest, and remain the single point of accountability throughout.
Embedded adoption
The work ends when AI is embedded as a permanent part of how the business operates, not when the tools have been installed. Adoption is the outcome, not a follow-on project.
When to engage
Critical Intervention
AI is already on the agenda but isn't moving, or isn't working. Fast entry, independent diagnosis, decisive action. I come in, identify what's actually happening, and drive the resolution.
Strategic Initiative
A defined AI capability needs to be built into the business from the ground up, owned end-to-end, from the first conversation with the CEO through to embedded operational adoption.
Where I work
Financial services and fintech, payments processors, FX and treasury businesses, regulated lenders, transaction banking platforms, and growth-stage fintechs backed by private equity or venture capital.
AI adoption in financial services carries compliance, data governance, and integration complexity that doesn't exist in other sectors. This work is built around that context, not adapted to it after the fact.
Background
15 years as an operator inside financial services and fintech, not in technology consulting.
That includes MD-level leadership of an 85-person commercial division, building a regulated institution from four people to $6m+ revenue, and leading commercial and operational transformation across FX, treasury, payments, and transaction banking across Europe.
The reason AI adoption in the hands of an operator produces different results than in the hands of a technology consultant: the entry point is always the commercial outcome, and the person delivering it has run the functions being changed. That context is not transferable.
Selected Work
Each situation is different.
Applied across financial services, payments, and fintech, where the operating model, the data, and the commercial stakes are specific enough to demand precision rather than generic AI deployment.
These are representative engagements. Not edge cases.
Revenue & Sales Transformation
Context
Payments business with strong inbound demand but poor conversion and inconsistent pipeline quality. Sales capacity was being consumed by low-probability opportunities while high-value segments were systematically underserved.
Insight
Data existed across the business but was not being used to prioritise or guide commercial behaviour. Sales effort was misaligned with value potential, not through poor management, but through absent intelligence.
Intervention
AI-driven lead scoring and prioritisation embedded into the CRM. Automated outreach support built around client profile and buying behaviour. Real-time pipeline intelligence surfaced to leadership for the first time. Full alignment of sales team to the new model.
Outcome
20–30% conversion uplift. Materially improved pipeline quality. Meaningful reduction in wasted sales effort. Enabled expansion into higher-value client segments and improved revenue quality across the book.
Risk & Treasury Intelligence
Context
Treasury function at a regulated institution operating reactively, with delayed insight into exposure and client activity. Decisions were being made without the intelligence the business had already generated.
Insight
Data existed across multiple systems but was disconnected. There was no mechanism to translate it into actionable intelligence at the speed decisions needed to be made. The bottleneck was not capability, it was connectivity.
Intervention
AI-driven monitoring of exposure and client activity across systems. Alerting architecture for anomalies and risk threshold breaches. Decision-support layer embedded directly into hedging and client action workflows.
Outcome
Faster decision-making across the treasury function. Materially improved risk management. Increased responsiveness enabled proactive positioning and meaningfully strengthened client advisory capability.
Operations & Client Onboarding Redesign
Context
Scaling fintech where manual onboarding processes had become a structural constraint on commercial growth. Delays, increasing cost-to-serve, and inconsistent SLA performance were eroding competitive position.
Insight
Operational workflows were fragmented and heavily reliant on manual review at every stage. The issue was not headcount, it was architecture. The process had been built for a business a fraction of the size.
Intervention
AI-driven document processing, validation, and decision-support. Automated workflow routing integrated into existing onboarding systems. Full alignment with the operations team throughout, the change was designed to be adopted, not imposed.
Outcome
Significant reduction in onboarding time. Lower cost-to-serve. Improved SLA performance. Enabled scaling without proportional headcount growth and materially improved the client experience.
How I Work
The objective is not delivery. The objective is outcome.
I work inside the business, directly with the CEO and leadership team. The entry point varies, sometimes it's a specific function, sometimes the full operating model. What doesn't vary is the level of involvement, or the accountability for what actually changes.
Three Layers
Strategy
Aligning AI to where the business is going, not just what it does today. The commercial objective drives the design.
Execution
Driving design, implementation, and adoption inside the organisation. Cross-functional ownership, not project management.
Access
Where the work requires technical capability that doesn't exist inside the business, I bring it in, with full alignment to the outcome, not the provider.
Types of engagement
AI Operating Model Design
Redesigning how the business operates with AI embedded as a structural layer, not sitting alongside existing processes, but replacing the logic behind them.
Workflow Simplification
Identifying where complexity and manual effort are concentrated. Eliminating friction. Building workflows that scale without proportional cost.
Revenue Optimisation
Applying AI to commercial performance, conversion, pipeline quality, client targeting, pricing, and revenue predictability.
Data Activation
Most businesses hold significantly more data than they use. Connecting it, interpreting it, and turning it into decisions rather than reports.
Capability Build
Building the internal AI capability that continues to improve after the engagement ends. Not dependency on external providers, genuine organisational capability.
CEO Execution
AI as a board-level priority with no credible execution plan. I close that gap, from commercial design through to embedded operational adoption.
Portfolio Application
This work is available at portfolio level.
For PE and VC investors, the model creates a repeatable mechanism for AI-enabled performance improvement across portfolio companies, consistent diagnostic rigour, faster execution, and exit positioning built on operational substance rather than a narrative about future AI potential.
Strategic Access
Transformation at this level sometimes requires capability that doesn't exist inside the business. That's expected, not a problem.
What matters is that external capability is sourced correctly, managed without misaligned incentives, and integrated into the engagement in a way that serves the outcome.
Technical Specialists
Engineers, AI/ML specialists, data architects, and integration experts, sourced for the specific situation, not from a fixed roster.
Selected based on fit, not relationship. Engaged in the client's interest.
Tooling Selection
There is no platform I am incentivised to recommend. Selection is driven entirely by what fits the business, build vs buy, integration complexity, cost structure, and long-term capability implications.
Independent assessment. No referral arrangements.
Implementation Partners
Where the scale of delivery requires a broader team, I identify and orchestrate the right external capability. Vendor relationships managed in the client's interest throughout.
No misaligned incentives. Full accountability remains with me.
Strategic Connections
Access to the people, partners, and counterparties that expand what's possible, data providers, infrastructure partners, regulatory expertise, and sector-specific networks relevant to the transition.
Connections made because they serve the outcome.
I remain the single point of accountability throughout. External capability is brought in to serve the outcome, not to take over the engagement.
Perspectives
High-signal thinking. Not a blog.
About
I've spent 15+ years operating inside financial services businesses, building, restructuring, and turning around how they generate revenue and compete.
That includes leading an 85-person division at MD level with full P&L accountability and FCA regulatory responsibility, building a regulated institution from a four-person entity to $6m+ revenue, and leading strategic repositioning across treasury, FX, payments, and transaction banking across Europe and beyond.
The reason this is different from traditional advisory is that it comes from someone who has sat in these seats, who understands what it costs when strategy doesn't translate into execution, and what it actually takes to close that gap.
I now work with a small number of CEOs and leadership teams at a time, on the commercial and AI adoption problems where that experience is directly relevant.
Three Layers
Strategy
I know what the highest-value path looks like.
Execution
I drive it inside the business.
Access
I bring in what's missing externally.
Selected Experience
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