FINTECH AND POLICY PROJECT - 2027/8

Module code: MANM492

Module Overview

This is a compulsory capstone module for the MSc in FinTech and Policy programme. It requires students to independently investigate a specific FinTech and policy issue, applying the analytical, regulatory, and research skills developed across the programme. Students produce a scaffolded Portfolio of Evidence comprising a Research Design Proposal, a Professional Analytical Report in a chosen industry format, and a Reflective Commentary with AI Transparency Statement. The research must be based exclusively on secondary data sources. The module builds directly on the Cases in FinTech and Policy module (MANM521), and students are encouraged to develop their earlier research pitch into a full project. Support sessions and weekly consultations with the Module Convenor are provided throughout the summer term to guide topic selection, research design, and professional report writing.

Module provider

Surrey Business School

Module Leader

TASIOU Menelaos (SBS)

Number of Credits: 30

ECTS Credits: 15

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 298

Lecture Hours: 1

Captured Content: 1

Module Availability

Semester 2

Prerequisites / Co-requisites

None.

Module content

Students select a FinTech and policy topic of interest, anchored in a specific jurisdiction, time period, firm or market segment, and/or regulatory instrument. Topics are drawn from a curated and annually updated menu covering areas such as open banking and payments innovation, crypto-asset regulation, AI governance in financial services, digital operational resilience, financial inclusion and alternative lending, and regulatory sandboxes, to name a few. Students formulate a precise research question and develop it through a staged process: an early-term Research Design Proposal establishing the question, scope, source strategy, and analytical framework; a Professional Analytical Report presented in one of three industry-relevant formats (policy brief, compliance/risk assessment, or market analysis); and a Reflective Commentary with a mandatory AI Transparency Statement demonstrating metacognitive engagement and responsible use of digital tools. The module is largely based on self-directed study and research conducted during the summer term.

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Research Design Proposal Pass/Fail
Project (Group/Individual/Dissertation) Individual project report 100
Coursework Reflective Commentary & AI Transparency Statement Pass/Fail

Alternative Assessment

None.

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate:

  • The ability to define and critically investigate a current FinTech and policy issue with specificity and rigour.
  • Competence in independent research using secondary sources, including the formulation of a viable research question, the selection and critical evaluation of academic and industry literature, and the application of an appropriate analytical framework.
  • The capacity to produce a professional analytical report in an industry-relevant format (policy brief, compliance/risk assessment, or market analysis), demonstrating both academic depth and professional communication skills.
  • Critical self-awareness through reflective commentary on the research process and transparent, responsible engagement with generative AI tools.

The summative assessment consists of three components. The Research Design Proposal is submitted early in the summer term and assessed on a pass/fail basis; it establishes the research question, source strategy, and analytical framework, and receives formative feedback. The Professional Analytical Report is the primary assessed output, carrying the full module mark, and requires students to analyse a specific FinTech and policy issue using a chosen professional format. The Reflective Commentary and AI Transparency Statement is assessed on a pass/fail basis and requires students to reflect on their learning and to declare and critically evaluate any use of AI tools during the project. All submissions are checked for plagiarism using an electronic detection system.

Formative assessment and feedback: Students receive formative feedback on the Research Design Proposal by Week 5 of the summer term. Weekly consultation hours provide ongoing guidance. Summative feedback on the final portfolio is provided via SurreyLearn.

Module aims

  • Develop a comprehensive and critically informed understanding of a FinTech-related issue in a business, regulatory, and policy context.
  • Analyse a specific FinTech-related problem or opportunity using appropriate finance, legal, and policy research tools, applying a clearly justified analytical framework.
  • Produce professional-standard research outputs that integrate academic rigour with industry-relevant communication formats, and demonstrate responsible digital literacy, including the transparent and critically reflective use of generative AI tools within the research process.

Learning outcomes

Attributes Developed
001 Formulate a specific, well-scoped research question and design a viable research strategy grounded in secondary data sources. CPT
002 Critically synthesise academic and industry literature to construct a coherent conceptual framework and identify gaps in current knowledge. KCT
003 Conduct rigorous analysis of a FinTech and policy issue, applying relevant theoretical models and interpreting secondary data with precision. KCPT
004 Produce a professional analytical report in an industry-relevant format, presenting findings, conclusions, and feasible policy or strategic recommendations. KPT
005 Reflect critically on the research process, including the limitations of the study, the role of generative AI tools, and the identification of areas for future investigation. KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to develop students' ability to conduct, document, and report independent research at a professional standard. It builds on the Cases in FinTech and Policy module (MANM521), allowing students to apply and extend the research principles and methods learned during the taught semesters.

Introductory support sessions in the opening weeks of the summer term cover topic selection, research question formulation, database search strategies, the requirements of the scaffolded portfolio, and guidance on the three professional report formats available. The Module Convenor provides a curated, annually updated menu of topic areas reflecting current developments in FinTech regulation and policy.

Weekly consultation hours (by appointment) provide individualised guidance throughout the summer term. Formative feedback on the Research Design Proposal supports students in refining their research direction before commencing the main analysis. The module platform on SurreyLearn is used for the distribution of resources, submission of assessed work, and the return of feedback.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MANM492

Other information

Digital CapabilitiesStudents will be exposed to real-world business problems which will allow them to evolve practical skills, such as data analysis and critical evaluation, and attributes to be forward-thinking in their application and implementation of digital solutions to meet diverse and complex challenges. Students are encouraged to use current media and data platforms such as Wharton Research Data Services (WRDS), Bloomberg, Financial Times, Tomson Reuters, and company’s website. Students will develop proficiency in all aspects of digital engagement.

Employability: Case study and project management is an essential tool in professional life. The module provides an opportunity for students to recognize and analyse real-world business issues and to present ideas confidently, clearly, and fluently in writing. In return, students develop and enhance their interpersonal and professional skills.

Global and Cultural Capabilities: The module is taught within a diverse group of students with different nationalities and backgrounds. Students are encouraged to engage with, and learn from, diverse perspectives through interaction. Students will demonstrate awareness of, and respect for, intercultural variations in the FinTech industry, respecting diversity and promoting equality, inclusion and social justice.

Resourcefulness & Resilience (R&R): Students will develop attributes such as confidence, adaptability, self-regulation, self-efficacy, problem solving and decision-making abilities, through developing worthwhile research objectives and frame relevant research questions plus utilizing appropriate research methodologies to the project at hand and presenting their report in a professional manner. The effectiveness of the R&R will be inherent in assessment design.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
FinTech and Policy MSc 2 Compulsory A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2027/8 academic year.