Mustafa Faiz Qadria (MFQ): Banking, insurance and payments. From requirements to adoption.

I structure requirements and business cases, prepare priorities and decisions, and coordinate delivery between business and IT. I’m looking for a full-⁠time role, with a particular interest in helping organisations adopt AI in everyday work.

See my experience LinkedIn

Based in: Germany
Works in: German and English

Background

Transformation governance at a European insurance group
Broker-platform concept and project setup
Payments and PSP delivery at a European insurer
Insurer-backed lending in a core banking platform
Training and enablement

Experience

I started in 2012 with a banking apprenticeship at Commerzbank and worked in corporate banking, credit and cash management until 2017. At Deloitte I then spent almost six years in client-facing consulting for banks and insurers: payments, lending integration, a broker-platform concept and transformation governance, latterly leading a workstream and preparing steering committees. In 2023 I managed regulatory change at HSBC.

01
Transformation governance at a European insurance group
Deloitte Consulting Senior Consultant · 2020–2023
In a transformation programme spanning several European countries, I led one workstream and coordinated business teams, IT and external partners across countries. I also contributed to client meetings and proposals, and coached two junior consultants.
- Delivery governance set up with its decision logic, committees, reporting and KPI set
- Roadmaps and portfolio, demand and dependency management at the country interfaces
- KPI- and RAID-based steering material and decision options for management
- Project controlling: schedule, budget tracking, risk and dependency management
What came out of it
Delivery governance, reporting and steering material for the workstream and its interfaces with the wider programme.
02
Broker-platform concept and project setup
Deloitte Consulting Senior Consultant · 2020–2023
As an external delivery lead for an insurer, I identified and interviewed stakeholders, developed a broker-platform concept and backlog, and set up the project.
- The insurer’s interests represented in recurring requirements and approval discussions with a partner organisation
- Diverging interests made visible and requirements sharpened
- Open approval points tracked for the next steps
What came out of it
Platform concept, backlog and project setup.
03
Payments and PSP delivery at a European insurer
Deloitte Consulting Consultant · 2017–2020
As payments product owner in an insurer’s payment service provider (PSP) implementation, I led the functional delivery of 3-D Secure and new payment methods, and translated the requirements of the PSP, the card schemes, mobile wallets and PayPal into backlogs, user stories and test cases, aligned with the insurer’s finance and cash-management systems.
- Functional requirements for OpenAPI-documented interfaces and operational-readiness material
- Settlement, reconciliation, refund, chargeback and direct-debit-return processes defined with operations
- Conversion, reconciliation and chargeback priorities set from existing dashboards and checkout analysis
- Support for the head of product in partner, SLA and framework-agreement discussions
What came out of it
The functional flows and token handling for mobile wallets and PayPal, and the supporting settlement, reconciliation, refund and chargeback processes.
04
Insurer-backed lending in a core banking platform
Deloitte Consulting Consultant · 2017–2020
For a large German banking group, I led a sub-project for integrating an insurer’s real-estate-secured loan product into the group’s existing core banking platform.
- Pre-study, scope and use cases, then the functional and test concept
- Interface and error handling between the core banking platform and the insurers’ back ends
- Requirements and interface workshops with the insurers; backlog and gap analysis
- Steering-committee preparation, milestone and risk planning, cost–benefit analysis
What came out of it
A concept and interface design the core team could build on inside the platform it already ran, and the documentation handed over to the client’s management.

Business cases and decision preparation

At Deloitte, I analysed checkout and sales data to prepare business cases with several scenarios, making benefit assumptions, uncertainty and decision options clear for management.

Training and enablement

In consulting and project management, I also helped people understand and use what we delivered, and co-wrote Deloitte articles on robotics in bank compliance and on OKR.

Training sessions for internal and client teams
Stakeholder demos, for example at sprint reviews
New tools introduced together with my team
Guides, FAQs and documentation for rollouts

Career

Since 2024MFQ Consulting (mfqconsulting.com)Founder; developing my own consulting offering and independent AI and learning projects
2023HSBC Continental EuropeIT Project Manager, regulatory change in capital markets and payments infrastructure: IAM- and SWIFT-related changes from user acceptance testing to go-live and hypercare, with an implementation team in India and business, technology, operations and compliance stakeholders in Germany; set up and maintained resource and budget registers in Clarity PPM, bringing together risks, dependencies and project status for reporting
2020–2023Deloitte ConsultingSenior Consultant, financial-services transformation; workstream lead and project manager on client engagements
2017–2020Deloitte ConsultingConsultant, digital payments and operations; product owner and sub-project lead on client engagements, including a functional concept for the end-to-end digitisation of a mortgage product
2012–2017CommerzbankBanking apprenticeship (Bankkaufmann, IHK), then corporate banking: credit analysis, cash management and trade finance, and business analysis in a core-system programme

Qualifications

BA Business Administration, FOM University of Applied Sciences
Banking Professional (Bankkaufmann, IHK)
Project Management Professional (PMP), PMI
Professional Scrum Product Owner II (PSPO II), Scrum.org

Next role

I’m looking for work where delivery and adoption meet: transformation, portfolio or programme roles in financial services, or helping organisations put AI to practical use.

Launches taught me that adoption takes more than going live. People need to understand what has changed, try it in their own work and get help when something does not fit. That is as true of a new payment method or a portfolio process as it is of an AI assistant, and AI adds questions of its own: which tasks it helps with, what users should check and who stays responsible for the result.

My background is in requirements, business cases, governance, testing, launches and training across banking, insurance and payments, working with business, operations and compliance teams. Bringing AI into an organisation takes the same work: finding the tasks where it helps, shaping the use case and the business case, aligning the people involved and preparing the rollout. My AI experience is independent: I build my own projects with AI assistants, including LearningHub and this website, and I follow closely how teams actually take these tools up.

Looking for: A full-time role in transformation, delivery or technology adoption, in financial services or in AI enablement
Sectors: Banking, insurance and payments
Languages: German (native) and English (business fluent)

Contact me on LinkedIn

LearningHub

Independent project · prototype

Start with what you want to be able to do.

The idea: LearningHub is my own product idea. The aim is for someone to name a goal and get useful explanations, practice when it helps and a clear next step, without first assembling a curriculum from different courses and tools.
What exists today: A working prototype with two prepared journeys. In one of them, learners run real SQL on synthetic data in the browser and get rule-based feedback; any hint, or a second try after feedback, is recorded as help. Progress stays on their own device, with pause, resume and a notebook export. There is no live AI model or voice input. Its learning benefits have not yet been evaluated in a user study.
How it was built: I set its goals and scope and decide what is published. Claude Code wrote and tested most of the code. ChatGPT helped develop the product design and acceptance criteria in later iterations, and Codex reviewed parts of the work.
Status: Not yet publicly available, and not affiliated with any AI provider.

Examples

One prepared example from the LearningHub prototype and one illustrative concept for a banking workflow. Neither is a production AI deployment or a measured customer outcome.

Investigate a payout discrepancy

LearningHub prototype · synthetic data

The task

Explain why these payout totals do not reconcile.

Using a fictional affiliate-payout dataset, learners run SQL to find duplicate payments and missing reversals, reconcile the totals and assemble a finding from prepared sentences.

Inspect
Query synthetic records in the browser and compare the results.
Practise
Use prepared explanations and rule-based feedback to work through the discrepancy.
Continue
Return to progress saved in the same browser, or export a readable notebook of the work.

What I want to test

Does a learning path built around a specific goal take less effort than one that learners assemble themselves? Can they then solve a fresh case without help?

Prepared content and synthetic data, with rule-based feedback rather than a live AI tutor.

A clearer application for a letter of credit

Illustrative concept · synthetic example

The task

Resolve an inconsistent application before specialist review.

An invented application says EUR 100,000, while its supporting quotation says USD 100,000. The proposed assistant would point to both fields and help prepare a clarification question.

Compare
Show the conflicting source fields and the uncertainty they create.
Clarify
A documentary credit specialist reviews the question and the corrected response.
Hand over
Prepare the evidence and changes for the authorised workflow; the specialist owns the decision.

What I want to test

Could this reduce clarification rounds and returned cases? I would count missed issues and unnecessary flags as well as time saved.

A concept on invented data, not a bank connection or service. It would help improve an application before specialist review; it would not be a credit decision, document examination under an issued credit, sanctions clearance or export-control approval.

Contact

Hiring for transformation, delivery or AI adoption?

Contact me on LinkedInlinkedin.com/in/mqadria Contact me by emailmustafa@mfq.me

Profiles and writing

MFQ stands for Mustafa Faiz Qadria. I use my initials for my personal work online.