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My Work/ 01

I help enterprise merchants and payment providers find where good customers get declined, and fix the system that declines them.

Staff Optimization Consultant, Airwallex · Netherlands · Previously Checkout.com, Flywire, Financial Times, IMImobile/Cisco

13 years across the merchant and PSP sides. Moroccan, then British national, now living in the Netherlands.

Abstract amber arcs and connected nodes representing the flow of a payment transaction

A working view of payments

Approval is the output. The causes sit across the whole journey.

Follow the payment

The payment path

Start with the system

A decline is rarely one thing.

I trace a payment end to end and turn what I find into a short list of fixes, tests and playbooks a team can measure.

The path I trace — a decline is rarely one thing

  1. INT

    Integration

    integration quality and message completeness

  2. CHD

    Cardholder data

    data quality, tokens, recurring indicators

  3. 3DS

    Authentication

    3DS/SCA strategy, challenge behaviour

  4. RSK

    Risk decisions

    fraud controls vs. false declines

  5. ISS

    Issuer behaviour

    issuer-specific rules and decline patterns

  6. RTE

    Routing

    acquiring setup and routing strategy

  7. AUTH

    Authorisation

    approval rate, cost, customer experience

Expertise

Where I focus the work.

  • 01

    Acceptance & retention

    Improve approvals across the payment path, from cardholder data and authentication to issuer behaviour and routing.

    At the FT: issuer-level diagnostics, network tokens, account updater and retry strategy for subscriptions.

  • 02

    Risk & payment partners

    Balance fraud controls with conversion, and choose payment partners and methods that fit the market.

    Fraud strategy and 3DS routing at Airwallex; PSP and acquirer selection and commercial negotiation at the FT.

  • 03

    Insight & delivery

    Turn transaction data into clear actions, from go-live reviews to merchant reporting and repeatable optimisation playbooks.

    At Checkout.com: merchant insight reporting and client engagement for the Intelligent Acceptance launch.

Explore all work areas and professional skills

  • Authorisation uplift

    Full-funnel investigations: integration quality, failed-to-process outcomes, cardholder data, 3DS, risk decisions, issuer behaviour and routing. At the FT, I raised acceptance through issuer-level analysis, decline-code diagnostics and retry strategy.

  • Network tokenisation and recurring

    At the FT, I cut involuntary churn on subscriptions with account updater, network tokens, intelligent retry rules and targeted customer contact. Tokens also cut cost: Visa and Mastercard have added fees on non-tokenised transactions in several regions.

  • 3DS / SCA

    3DS message quality, authentication indicators, challenge behaviour and ACS outcomes. At Airwallex, I tune 3DS routing alongside risk rules so conversion holds without giving up chargeback performance. At the FT, I owned PSD2/SCA compliance.

  • Fraud mitigation

    Where fraud controls, issuer behaviour and acquiring setup meet, so risk rules stop declining good customers. At Airwallex, I own fraud strategy on the accounts.

  • Go-live and post-live

    Readiness reviews before payment-acceptance launches, then issue triage, monitoring and fixes after go-live.

  • Playbooks and applied AI

    At Airwallex, I design and refine the team's standard optimisation playbooks. I work with Product, Engineering and Data Science on AI/ML levers and diagnostic tooling, including dynamic SCA and ML-based anomaly alerting. At Checkout.com, I led client engagement for the launch of Intelligent Acceptance.

  • PSP and acquirer strategy

    At the FT, I chose PSPs and acquirers, negotiated contracts, and built the multi-PSP setup that secured domestic acquiring in key markets. At Flywire, I managed card acquiring and payment partner relationships.

  • Merchant intelligence and reporting

    At Checkout.com, I built the merchant-facing insight layer that turned transaction data into commercial conversations for Customer Success and Sales, including self-serve reporting and personalised insight reports for merchant QBRs.

  • Checkout conversion and payment methods

    At the FT, I optimised the signup and payment flow and matched the payment-method mix to each market.

The supporting toolkit

Payments & Risk
Authorisation rate uplift, Payment acceptance optimisation, Network tokenisation, Card account updater, Recurring and subscription billing, Involuntary churn and dunning, Retry strategy, 3DS, SCA and PSD2, Fraud and risk strategy, Issuer and decline-code analysis, Routing strategy, Card scheme rules and interchange, PCI DSS, Payment methods (PayPal, Apple Pay, direct debit, local methods), Direct carrier billing, Go-live readiness
Strategy
PSP and acquirer selection, Commercial negotiation, Stakeholder management
Data & AI
Transaction data analysis, Experimentation and A/B testing, Applied AI and LLM tooling
Product
Payments product management, Playbook design, Workflow automation

How I work

Payment performance is an end-to-end system, not a decline code on a dashboard.

I work with Sales, Account Management, Product, Engineering and Data Science to move from diagnosis to action. When something works, I write it down as a playbook so the next merchant gets it faster.

Marginal gains

A method, not a miracle

Seven small fixes beat one big one.

In Atomic Habits, James Clear describes how British Cycling pursued small improvements across the whole system. I apply that method to payments: isolate the friction, test a fix and measure the result.

Applied to payments · hypothetical

Seven levers. One illustrative outcome.

+2.2 percentage points

Illustrative, value-weighted authorisation-rate bridge on £400m in original attempted payment value: a 85.0% baseline to 87.2%. Each bar is an example increment, not a personal client result.

Illustrative uplift · percentage points (pp)

  1. Integration

    Complete messages; fewer failed-to-process payments.

    +0.3 pp

  2. Cardholder data

    Network tokens, account updater and recurring indicators.

    +0.5 pp

  3. Authentication

    Better 3DS message quality and challenge decisions.

    +0.4 pp

  4. Risk decisions

    Tune rules that decline good customers.

    +0.3 pp

  5. Issuer behaviour

    Diagnose decline codes and issuer-specific requirements.

    +0.2 pp

  6. Routing

    Use the acquiring route the issuer is more likely to approve.

    +0.3 pp

  7. Recovery

    Safe, eligible retries—not repeated attempts at any cost.

    +0.2 pp

Bar scale: 0 to 0.5 percentage points, starting at zero.

Rate illustration
85.0% → 87.2%
Increment per 1 pp
£4,000,000
Additional authorised value
£8.8m

Even if only 50% of this additional authorised value converts into completed payments, the estimate is £4,400,000. This is an illustrative conversion assumption, not a measured result or guaranteed revenue or profit.

£8,800,000 is additional authorised payment value in this hypothetical—not guaranteed revenue or profit. Additive increments assume non-overlapping wins within the same original cohort, counted once. Validate real gains against merchant data; retries must not inflate the denominator. AUTH remains the outcome in the funnel above; recovery is follow-through, not a new funnel stage.

The mathematics of compounding

These curves illustrate a habit, not a payment forecast. Real authorisation rates cannot grow beyond 100%; the payments example above uses percentage-point changes instead.

The compounding illustration

1% better, every day.

37.78×

1.01 to the power of 365. Starting level = 1×. Select a checkpoint to inspect its value.

One per cent better daily over 365 days, reaching 37.78× the starting level0×10×20×30×40×Day 0Day 90Day 180Day 365

Mathematical illustration only—not a forecast or an authorisation-rate claim. Real authorisation rates are bounded by 100%.

The compounding illustration

1% worse, every day.

0.03×

0.99 to the power of 365. Starting level = 1×. Select a checkpoint to inspect its value.

One per cent worse daily over 365 days, reaching 0.03× the starting level0×0.25×0.5×0.75×1×Day 0Day 90Day 180Day 365

Mathematical illustration only—not a forecast or an authorisation-rate claim. Real authorisation rates are bounded by 100%.

The British Cycling story

When Dave Brailsford arrived in 2003, the team had a thin record and no British rider had won the Tour de France. He looked for a 1% gain in each part of the system, rather than one breakthrough.

British Cycling · the original lesson

  1. 2003

    Start with the system

    Dave Brailsford became British Cycling performance director and pursued 1% gains across the whole performance system.

  2. 2008

    Beijing

    British Cycling won 7 of the 10 track cycling gold medals.

  3. 2010

    Team Sky forms

    The professional road team was established, carrying the same evidence-led approach onto the road.

  4. 2012

    A first for Britain

    Bradley Wiggins became the first British rider to win the Tour de France for Team Sky.

  5. 2013 · 2015 · 2016 · 2017

    Froome’s four wins

    Chris Froome won the Tour de France in each of these seasons for Team Sky.

Reading: James Clear, “Marginal Gains”.

Further chapters

A little more context.

The work makes more sense alongside the people, places and learning behind it.

Get in touch

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