Lecture 1: Foundations of Digital Disruption in Financial Services
What is ‘emerging tech in finance’, how did we get here, where is it going
1.1 Course objectives
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
Welcome to Emerging Technology & Finance
- This is a flipped-classroom Bachelor course: every regular lecture (odd weeks) is followed by a flipped session (even weeks) where all groups present on the same topic. There is no exam to register for — sign up on the course Moodle page by 15 October 2026 so you receive announcements and the token-allocation quiz links.
- Form a group of 4 by the end of Week 1 (Moodle sign-up sheet). Stragglers will be allocated by the lecturers.
- Grading is 100% cumulative across the 6 flipped sessions: each session = 50% peer-allocated tokens + 50% lecturer evaluation. Each group gets 20 fresh tokens every flipped week to allocate to other groups via a Moodle quiz within 5 minutes of the session ending.
- Submission per session: upload your slide PDF to Moodle before each flipped session starts. Ask questions during or right after each session — that is the preferred channel.
- Admin / studies / exam-eligibility questions go to the registrar’s office (Studiensekretariat) at studiensekretariat@uni-ulm.de.
- Course-content questions outside class: email oliver.padmaperuma@uni-ulm.de, CC andre.guettler@uni-ulm.de.
- We also recommend the student advisory service.
Course Objective
Scope
We will:
- Survey six emerging-technology modules at the cutting edge of finance: agentic AI · blockchain & DeFi · fintech business models · RegTech & cybersecurity · CBDCs
- Pair every regular lecture with a flipped session in which every group presents their angle on the topic
- Train critical evaluation, presentation, and peer-judgment skills via a transparent token-based peer-grading mechanic
- Place the technologies in a real-world business and regulatory context (PSD2/3, MiCA, EU AI Act, post-quantum standards)
We will NOT:
- Build production-grade fintech systems or trade live capital
- Cover deep technical implementations (we treat code as supplement, not core)
- Run a separate written exam or final-pitch competition — the cumulative flipped-session grade is the entire grade
Approach
Flipped-classroom alternation (12 weeks)
- Odd weeks (W1, W3, W5, W7, W9, W11): regular lecture introducing the topic
- Even weeks (W2, W4, W6, W8, W10, W12): flipped session — all groups present and allocate tokens
- Groups of 4, formed by end of Week 1
Token mechanic (the grading vehicle)
- 20 tokens per group per flipped session
- Each group allocates them to other groups, weighing insight · originality · clarity · critical depth
- Cumulative across 6 sessions = 50% of final grade · lecturer evaluation = 50%
Course at a glance (1/3)
Foundations of Digital Disruption in Financial Services
What is ‘emerging tech in finance’, how did we get here, where is it going
- Three waves of digital disruption in finance
- Today’s actors: incumbents, challengers, Big Tech, infrastructure
- Regulatory backdrop: PSD2, MiCA, EU AI Act
- Why now: structural drivers
- What this course will cover
Flipped — Digital Disruption in Financial Services
Group presentations · token allocation · discussion
- Recap of the foundations lecture
- Group presentations on digital disruption
- Token allocation & next steps
Agentic AI & LLMs in Finance
From LLMs to agents · applications · failure modes · EU AI Act
- LLMs in finance: architecture, training, capabilities
- Agentic AI: from answers to actions
- Applications: RAG, robo-advisors, AML, trading agents
- Failure modes: hallucination, drift, prompt injection
- Governance: EU AI Act and high-risk obligations
Flipped — Agentic AI & LLMs in Finance
Group presentations · token allocation · discussion
- Recap of the agentic AI lecture
- Group presentations on real LLM and agent deployments
- Token allocation & next steps
Blockchain, Crypto, DeFi & Tokenisation
From distributed ledgers to MiCA-regulated markets
- Blockchain primer: ledgers, consensus, smart contracts
- Crypto markets: BTC, ETH, stablecoins
- DeFi primitives: AMMs, lending, derivatives
- Tokenisation of real-world assets
- MiCA framework and EU enforcement
Course at a glance (2/3)
Flipped — Blockchain, Crypto, DeFi & Tokenisation
Group presentations · token allocation · discussion
- Recap of the blockchain & DeFi lecture
- Group presentations on real protocols and deployments
- Token allocation & next steps
Fintech Business Models
Neobanks, embedded finance, BNPL, Open Banking, Big Tech in finance
- Neobanks: N26, Revolut, Monzo, Chime
- Embedded finance & BaaS
- BNPL: Klarna, Affirm, regulatory pushback
- Open Banking & PSD2 outcomes
- Big Tech in finance
Flipped — Fintech Business Models
Neobanks, embedded finance, BNPL · group presentations · token allocation
- Recap of the fintech business-models lecture
- Group presentations on real companies and unit economics
- Token allocation & next steps
RegTech, Cybersecurity & Privacy-Preserving Compute
Industrialising compliance · cyber-threat landscape · ZKPs, MPC, federated learning · post-quantum
- RegTech overview: industrialising compliance
- KYC/AML automation in production
- Cybersecurity threats in finance
- Privacy-preserving compute: ZKPs, MPC, federated learning
- Post-quantum cryptography & the migration
Flipped — RegTech, Cybersecurity & Privacy-Preserving Compute
Group presentations · token allocation · discussion
- Recap of the RegTech & security lecture
- Group presentations on vendors, incidents, and emerging tech
- Token allocation & next steps
Course at a glance (3/3)
CBDCs & the Future of Money
Wholesale vs retail design · Digital Euro · e-CNY · programmable money
- What’s a CBDC: wholesale vs retail
- The Digital Euro state of play
- China’s e-CNY and small-country implementations
- Programmable money: feature, threat, or both
- Stablecoins as private money: tension with CBDCs
Flipped — CBDCs & the Future of Money
Final session · group presentations · token allocation · course wrap-up
- Recap of the CBDCs lecture
- Group presentations on real CBDC projects
- Token allocation, final standings, and course retrospective
Assignments / Exams
Flipped-Classroom Presentation Series 100% of your grade
Six in-class group presentations across six emerging-tech topics, graded cumulatively. Each session: 50% peer-allocated tokens + 50% lecturer evaluation.
Group of up to 4.
Submit by emailing oliver.padmaperuma@uni-ulm.de, CC andre.guettler@uni-ulm.de. Subject pattern: Emerging Technology & Finance_assignment-1-flipped-classroom-presentations_surname1_surname2_…
21 January 2027
1.2 What is “emerging tech in finance”?
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
A working definition
- The technologies reshaping financial services in 2026 — not the technologies that have already finished their reshaping (online banking, mobile payments).
- Concretely in this course: agentic AI · blockchain & DeFi · fintech business models · RegTech & cybersecurity · CBDCs.
- Two filters: (a) commercially material — measurable money is flowing or being shifted; (b) regulatorily contested — the rules are still being written.
Notes
“Emerging” is a moving target. ATMs were emerging in 1970; online banking in 1995; mobile banking in 2008. Each of those is now infrastructure. The five modules we’ll cover are at the stage where the rules are still being written — which is exactly why they’re worth a Bachelor course in 2026, and why your group’s critical evaluations have actual research value rather than being a repeat of an old textbook. Notice the deliberate exclusion of quantum computing in finance and fully autonomous trading — those are at a different stage (research, not deployment).
What this course is NOT
- A technical implementation course — we won’t write smart contracts or fine-tune LLMs.
- An investing-in-crypto course — we won’t tell you to buy or short anything.
- A prediction course — we won’t claim to know which technology lands or when.
- A survey course — six modules, not twenty; depth over breadth.
- A conceptual course: what these technologies do, in plain language.
- A business-judgment course: which models work, which don’t, and why.
- A regulatory-awareness course: PSD2/3, MiCA, EU AI Act, DORA, post-quantum standards.
- A peer-evaluation course: half your grade comes from how groups judge each other.
Notes
The bachelor level of the course matters here. We avoid two common failure modes: over-promising technical depth (which would require a CS or maths background) and over-promising predictive certainty (which would be dishonest). What remains is the most useful thing for a finance student to acquire — the ability to read an emerging-finance product or research paper critically and place it in regulatory and business context.
1.3 Three waves of disruption
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
The waves at a glance
- Wave 1 (1970s–1990s) — Electronification. ATMs, electronic settlement, retail bank-branch automation, early Bloomberg terminals. Cost of operations falls; access broadens; but business models stay intact.
- Wave 2 (2000s–2010s) — Internet & mobile. Online brokerage, mobile banking, payments digitisation, first neobanks, robo-advisors v1. Distribution decouples from physical branches; new business models emerge.
- Wave 3 (2020s) — Programmability & intelligence. Agentic AI, smart contracts, programmable money, fully API-driven banking, tokenisation. Money and contracts themselves become programmable (Philippon 2016).
Notes
Each wave didn’t replace the last — it layered. The branch network is still there, mobile banking is now table stakes, and Wave-3 technologies are being added on top. The interesting question is which Wave-3 component genuinely reshapes the stack versus which is rebranded Wave-2. The Course Objective slide we just covered is honest about this: we’ll spend the term separating the substantive shifts from the rebranded marketing.
What each wave shifted
| Wave | Distribution | Operations | Trust model | Business model |
|---|---|---|---|---|
| Wave 1 (electronification) | Branch + ATM | Mainframe automation | Bank-as-counterparty | Mostly unchanged |
| Wave 2 (internet/mobile) | App + web | Cloud-augmented | Bank-as-counterparty | Neobanks, robo-advisors |
| Wave 3 (programmability) | API + agent | AI + on-chain settlement | Code / cryptography | Embedded finance, DeFi, agentic services |
- Trust model is the most consequential shift: from “trust the regulated counterparty” to “trust the cryptography + the code.”
- Distribution moving to APIs means non-financial firms can now offer financial services — embedded finance.
- Operations shifting to AI means previously-headcount-intensive workflows (AML, customer service, research) become marginal-cost.
Notes
The trust-model shift is the deepest change. Wave-1 and Wave-2 fintech kept the basic deal — “a regulated entity holds your money and is liable when it goes wrong” — and just rewrote how you interacted with it. Wave-3 fintech sometimes severs that contract: in DeFi, code is the counterparty and there is no liability backstop; in embedded finance, the consumer interacts with a non-bank front-end and may not realise who the regulated bank actually is behind the scenes. This matters for regulators, who have to decide whether the new arrangements need new rules or whether existing rules cover them.
1.4 Today’s actors
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
The four-way landscape
- Universal banks (JPM, HSBC, Deutsche Bank), asset managers (BlackRock, Vanguard), insurers (Allianz, AXA).
- Strength: regulatory licences, customer base, balance sheet.
- Weakness: legacy stack, slow product cycles.
- Neobanks (Revolut, N26, Chime), robo-advisors (Wealthfront, Scalable), BNPL (Klarna, Affirm).
- Strength: digital-native UX, speed, attractive unit cost.
- Weakness: profitability hard; customer-acquisition expensive.
- Apple (Pay, Card, Cash), Google (Pay), Amazon (Lending), Alibaba (Ant), Tencent (WeChat Pay).
- Strength: distribution, data, ecosystem lock-in.
- Weakness: regulatory caution, conflict-of-interest concerns.
- Stripe, Adyen, Plaid, Marqeta, TrueLayer, Tink, ChainAnalysis, Circle.
- Strength: API-first, neutral, used by many other actors.
- Weakness: low margins, commodified pieces over time.
Notes
A useful way to read any fintech story is to ask: which of these four is the company, and which of the four is its customer? A neobank (challenger) selling to retail customers is one story; an infrastructure provider selling to challengers is another; an incumbent buying a fintech is a third. The competitive dynamics differ wildly across these combinations, and the four-way landscape changes faster than industries usually do — Big Tech’s role today is very different from 2018, and infrastructure providers like Stripe now do more in financial services than many banks (Frost et al. 2019).
How the four interact
- Neobanks vs incumbents on retail accounts (challenger eats incumbent revenue).
- Stablecoin issuers vs banks on dollar deposits (a new form of disintermediation).
- Big Tech vs banks on payments distribution (Apple Pay sits on the bank’s card; who owns the customer?).
- Incumbents acquire challengers (BBVA → Atom Bank stake, JPM → various fintechs).
- Banks license BaaS APIs from infrastructure providers (Solaris, Marqeta, Treasury Prime).
- Big Tech partners with banks for BaaS rails (Goldman + Apple Card; Citi + Google Pay backend).
Notes
The headline question — “is fintech disrupting banking?” — has aged into a more nuanced answer: fintechs are competing with banks on the customer-facing layer while simultaneously depending on banks for the regulatory layer (licences, settlement, deposit insurance). The interesting cases are when this two-layer arrangement breaks down — either because the infrastructure provider gets a banking licence and competes directly, or because the customer-facing fintech gets so big that regulators decide it should be treated as a systemic firm. Both scenarios are happening in 2026.
1.5 The regulatory backdrop
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
Four reshape-the-game regulations
- PSD2 (2015, EU) — mandated bank-to-third-party data sharing via APIs. Catalysed Open Banking; created Plaid/Tink/TrueLayer ecosystem (European Parliament and Council 2015).
- MiCA (in force 2024–25, EU) — first comprehensive crypto-asset regulation in a major jurisdiction. Stablecoin caps, CASP licensing, market-abuse rules (European Parliament and Council 2023).
- EU AI Act (in force progressively, 2025–27) — risk-based AI regulation. Finance use cases (credit decisions, fraud detection, robo-advisor) often land in “high-risk” with documentation, oversight, monitoring obligations (European Parliament and Council 2024).
- DORA (in force January 2025, EU) — Digital Operational Resilience Act. ICT-risk management, incident reporting, resilience testing, third-party-risk oversight for financial entities.
Beyond EU: UK Open Banking & Open Finance, US’s evolving stablecoin framework, NIST’s post-quantum cryptography standards (National Institute of Standards and Technology 2024), India’s UPI / Account Aggregator framework — each materially reshapes its market.
Notes
A common mistake in fintech analysis is to treat regulation as friction. In every one of these four cases the regulation created the opportunity by mandating openness (PSD2), legitimacy (MiCA), accountability (AI Act), or resilience (DORA). Companies that read the regulatory text early — and built around it — captured disproportionate value. Reading regulation is a core skill of this course; we’ll come back to specific clauses across the term (Arner, Barberis, and Buckley 2017).
What regulators are choosing
- Competition — open banking, open finance, mandatory data portability.
- Resilience — operational, cyber, third-party.
- Consumer protection — disclosure rules on BNPL, robo-advisor; AI Act on credit scoring.
- Legitimacy — bring stablecoins and crypto exchanges inside the regulated perimeter.
- Systemic risk — stablecoin caps, BNPL credit reporting, AI-Act high-risk obligations.
- Surveillance — AML thresholds, FATF Travel Rule, transaction-monitoring requirements.
- Cybersecurity — DORA, post-quantum migration deadlines.
- Algorithmic accountability — AI Act human-oversight, documentation, post-market monitoring.
Notes
The regulatory dual-track is a defining feature of 2026: on one hand, regulators are opening finance to more competition and innovation; on the other hand, they are tightening accountability and resilience requirements. The net effect is that the cost of starting a fintech is low but the cost of scaling one is rising fast as compliance obligations bite. This dynamic shapes who survives the next 5 years.
1.6 Why now: structural drivers
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
What’s changed since 2015
- Cloud is now the default substrate — a fintech can rent enterprise-grade infrastructure for cents per transaction. No capex barrier.
- Smartphones are universal in OECD and most emerging markets — distribution decoupled from physical presence.
- Open data + APIs — PSD2 in EU, Open Banking in UK, Account Aggregator in India: regulators mandated the plumbing.
- Generative AI — the cost of writing decent first-pass code, summarising a long document, or answering a customer query has fallen by an order of magnitude since 2022.
- Blockchain as infrastructure — stablecoins now settle real volumes; tokenisation of T-bills is happening at major institutions (BlackRock BUIDL).
Notes
The “why now” question matters because past predictions of fintech disruption (early 2000s, 2014–17) were partly premature — the underlying conditions weren’t fully there. By 2026 several conditions converged: distribution (smartphones), cost (cloud), data access (PSD2 / Open Banking), intelligence (generative AI), and on-chain settlement (stablecoins). The convergence is what makes this period genuinely different from prior fintech booms (Goldfarb and Tucker 2019).
Which drivers are accelerating, which plateauing
| Driver | 2015 status | 2026 status | Direction |
|---|---|---|---|
| Cloud penetration | Growing | Default | Plateauing |
| Smartphone penetration | OECD-led | Near-universal | Plateauing |
| Open Banking APIs | Mandated, nascent | Live, contested outcomes | Accelerating |
| Generative AI | Research | Production with caveats | Accelerating |
| Stablecoin settlement | Speculative | Material in DeFi & B2B | Accelerating |
| Quantum threat | Theoretical | NIST standards published | Accelerating |
- Cloud and smartphones are enablers that have done their work — they’re necessary but no longer a competitive advantage.
- AI and on-chain settlement are new fronts — where competitive advantage is being built today.
- Quantum is a deadline driver — it shapes who must invest in post-quantum primitives this decade (National Institute of Standards and Technology 2024).
Notes
A surprising amount of fintech analysis is still framed around enablers that have already plateaued (cloud, mobile). In 2026 the active competitive fronts are AI deployment, on-chain settlement adoption, and post-quantum-readiness. If your group’s flipped-session presentation focuses on a “fintech using cloud”, that’s not interesting in 2026; if it focuses on an LLM-driven AML workflow with a measurable false-positive change, that’s interesting.
1.7 What this course will cover
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
Six modules, twelve weeks
- This lecture · today
- Flipped W2: groups present specific disruption stories
- L3: LLMs, agents, RAG, robo-advisors, EU AI Act
- Flipped W4: deployed-LLM case studies
- L5: consensus, smart contracts, stablecoins, RWA, MiCA
- Flipped W6: protocol deep-dives + hack postmortems
- L7: neobanks, embedded finance, BNPL, Open Banking
- Flipped W8: unit-economics presentations
- L9: KYC/AML, cyber, ZKPs, federated learning, post-quantum
- Flipped W10: vendor & incident case studies
- L11: wholesale/retail design, Digital Euro, e-CNY, programmable money
- Flipped W12: CBDC project deep-dives
Notes
The structure is deliberately a survey with depth in each module. Every module has a regular lecture introducing the topic, then a flipped session where your group brings a concrete case. Half your grade comes from the cumulative quality of those six flipped sessions, judged 50/50 by your peers and the lecturers. No exam, no separate capstone — the work happens in those six sessions.
Course mechanics
- Groups of 4 — form by end of Week 1 via the Moodle sign-up.
- Every flipped week: each group presents (6 min + 2 min Q&A) on the topic of the prior regular lecture.
- Token mechanic — 20 tokens per group per session, allocated to other groups via a Moodle quiz within 5 min of session end.
- Per-session grade = 0.5 × (your group’s tokens received / max tokens received that week) × 100 + 0.5 × lecturer score (0–100).
- Final grade = mean of the 6 session grades, mapped to the German scale.
Full details in the presentation series brief and syllabus.
Notes
The mechanic is novel and might feel uncomfortable at first — peer evaluation can feel exposed when 50% of your grade is at stake. In practice, peer scores and lecturer scores tend to converge once everyone has done one or two rounds: the room collectively recognises sharp analysis and honest critique. The anti-collusion check at end of term keeps the system fair.
1.8 Conclusion of Lecture 1
- 1.1 Course objectives
- 1.2 What is ?
- 1.3 Three waves of disruption
- 1.4 Today’s actors
- 1.5 The regulatory backdrop
- 1.6 Why now: structural drivers
- 1.7 What this course will cover
- 1.8 Conclusion of Lecture 1
Course at a glance (1/3)
Foundations of Digital Disruption in Financial Services
What is ‘emerging tech in finance’, how did we get here, where is it going
- Three waves of digital disruption in finance
- Today’s actors: incumbents, challengers, Big Tech, infrastructure
- Regulatory backdrop: PSD2, MiCA, EU AI Act
- Why now: structural drivers
- What this course will cover
Flipped — Digital Disruption in Financial Services
Group presentations · token allocation · discussion
- Recap of the foundations lecture
- Group presentations on digital disruption
- Token allocation & next steps
Agentic AI & LLMs in Finance
From LLMs to agents · applications · failure modes · EU AI Act
- LLMs in finance: architecture, training, capabilities
- Agentic AI: from answers to actions
- Applications: RAG, robo-advisors, AML, trading agents
- Failure modes: hallucination, drift, prompt injection
- Governance: EU AI Act and high-risk obligations
Flipped — Agentic AI & LLMs in Finance
Group presentations · token allocation · discussion
- Recap of the agentic AI lecture
- Group presentations on real LLM and agent deployments
- Token allocation & next steps
Blockchain, Crypto, DeFi & Tokenisation
From distributed ledgers to MiCA-regulated markets
- Blockchain primer: ledgers, consensus, smart contracts
- Crypto markets: BTC, ETH, stablecoins
- DeFi primitives: AMMs, lending, derivatives
- Tokenisation of real-world assets
- MiCA framework and EU enforcement
Course at a glance (2/3)
Flipped — Blockchain, Crypto, DeFi & Tokenisation
Group presentations · token allocation · discussion
- Recap of the blockchain & DeFi lecture
- Group presentations on real protocols and deployments
- Token allocation & next steps
Fintech Business Models
Neobanks, embedded finance, BNPL, Open Banking, Big Tech in finance
- Neobanks: N26, Revolut, Monzo, Chime
- Embedded finance & BaaS
- BNPL: Klarna, Affirm, regulatory pushback
- Open Banking & PSD2 outcomes
- Big Tech in finance
Flipped — Fintech Business Models
Neobanks, embedded finance, BNPL · group presentations · token allocation
- Recap of the fintech business-models lecture
- Group presentations on real companies and unit economics
- Token allocation & next steps
RegTech, Cybersecurity & Privacy-Preserving Compute
Industrialising compliance · cyber-threat landscape · ZKPs, MPC, federated learning · post-quantum
- RegTech overview: industrialising compliance
- KYC/AML automation in production
- Cybersecurity threats in finance
- Privacy-preserving compute: ZKPs, MPC, federated learning
- Post-quantum cryptography & the migration
Flipped — RegTech, Cybersecurity & Privacy-Preserving Compute
Group presentations · token allocation · discussion
- Recap of the RegTech & security lecture
- Group presentations on vendors, incidents, and emerging tech
- Token allocation & next steps
Course at a glance (3/3)
CBDCs & the Future of Money
Wholesale vs retail design · Digital Euro · e-CNY · programmable money
- What’s a CBDC: wholesale vs retail
- The Digital Euro state of play
- China’s e-CNY and small-country implementations
- Programmable money: feature, threat, or both
- Stablecoins as private money: tension with CBDCs
Flipped — CBDCs & the Future of Money
Final session · group presentations · token allocation · course wrap-up
- Recap of the CBDCs lecture
- Group presentations on real CBDC projects
- Token allocation, final standings, and course retrospective
Further reading
- Philippon (2016) — “The FinTech Opportunity” — concise, NBER-style framing of why fintech is more than a buzzword.
- Goldfarb and Tucker (2019) — “Digital Economics” — a Journal of Economic Literature survey of the economics of the digital shift; required for placing fintech in a broader frame.
- Arner, Barberis, and Buckley (2017) — RegTech and the reconceptualisation of financial regulation — the canonical piece on why technology and regulation co-evolve.
- Frost et al. (2019) — BIS WP on BigTech in financial intermediation — the structural-shift framing.
Prepare before next flipped session (Week 2)
- Form your group of 4 by end of this week via the Moodle sign-up sheet. Don’t form? You’ll be allocated.
- Choose your angle for Week 2 from the six in the presentation series brief — or propose your own (clear it with the lecturers via Moodle).
- Research one specific company, regulation, product, or failure. Bring concrete numbers, not vendor narrative.
- Draft slides — ≤ 10 slides, 6-minute time-box. Run a dry-run.
- Upload your slide PDF to Moodle before 14:00 next Thursday.
See you next time
- Group formation: by 29 October 2026 via the Moodle sign-up.
- Next session: Lecture 2 — Flipped: Digital Disruption in Financial Services on 29 October 2026. Each group presents.
- Slides due on Moodle before 14:00 that day.