Lecture 2: Flipped — Digital Disruption in Financial Services

Group presentations · token allocation · discussion

Prof. Dr. Andre Guettler Director of the Institute
Helmholtzstraße 22, Room 205
andre.guettler@uni-ulm.de
+49 731 50 31 030

Oliver Padmaperuma Doctoral Candidate
Helmholtzstraße 22, Room 203
oliver.padmaperuma@uni-ulm.de
+49 731 50 31 036

2.1 Course objectives

• 2.1 Course objectives
• 2.2 Recap: Foundations of Digital Disruption
• 2.3 Session agenda
• 2.5 Token allocation
• 2.6 Lecturer reflection
• 2.7 Wrap-up & next steps

• Welcome to
• Course Objective
• Course at a glance (1/3)
• Course at a glance (2/3)
• Course at a glance (3/3)
• Assignments / Exams

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

Week 1

22.10.2026

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

Week 2

29.10.2026

Group presentations · token allocation · discussion

• Recap of the foundations lecture
• Group presentations on digital disruption
• Token allocation & next steps

Agentic AI & LLMs in Finance

Week 3

05.11.2026

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

Week 4

12.11.2026

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

Week 5

19.11.2026

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

Week 6

26.11.2026

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

Week 7

03.12.2026

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

Week 8

10.12.2026

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

Week 9

17.12.2026

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

Week 10

07.01.2027

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

Week 11

14.01.2027

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

Week 12

21.01.2027

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

2.2 Recap: Foundations of Digital Disruption

• 2.1 Course objectives
• 2.2 Recap: Foundations of Digital Disruption
• 2.3 Session agenda
• 2.5 Token allocation
• 2.6 Lecturer reflection
• 2.7 Wrap-up & next steps

• What we covered last week
• Open questions to dig into today

What we covered last week

• Three waves of disruption — ATMs/electronic banking → online + mobile → AI / blockchain / programmable money (Philippon 2016).
• Today’s actors — incumbents (universal banks, asset managers), challengers (neobanks, BNPL, robo-advisors), Big Tech (Apple, Google, Amazon, Alibaba), and infrastructure layer (Stripe, Plaid, Marqeta) (Frost et al. 2019).
• Regulatory backdrop — PSD2 reshaped EU payments (European Parliament and Council 2015); MiCA crypto rules (European Parliament and Council 2023); EU AI Act for AI in finance (European Parliament and Council 2024).
• Why now — cloud, smartphones, generative AI, and a regulator base that explicitly invites entry (open-banking mandates) make the cost of starting a fintech the lowest in history (Goldfarb and Tucker 2019).

The headline from Lecture 1 was that disruption in finance is not new — what’s new is the pace and simultaneity. Three forces converged: cheap compute (cloud), universal distribution (smartphones), and regulators choosing competition over protection (PSD2, MiCA, the UK Open Banking mandate). The result is that a launchable fintech idea no longer needs a banking licence, a branch network, or a custom data centre — it can rent all three. As you research your group’s angle today, ask which of those rented layers is the most fragile, because that’s where the next disruption will hit.

Open questions to dig into today

• Which wave of disruption (mobile · AI · blockchain) has actually changed how you use financial services this year?
• Are incumbents losing — or are they quietly acquiring everything that matters?
• Where does the next regulatory frontier sit? Open Banking 2.0? AI liability? Quantum-safe payments?
• What’s a failed disruption (Wirecard, FTX, Greensill) and what does it tell us about the model?

These are deliberately open-ended. Your group does not need to answer all of them — pick the angle that lights you up and use the presentation to argue a clear thesis. Remember the rubric: peers and lecturers will reward a specific example over a general claim, a critical eye over a sales pitch, and a fresh angle over the obvious one.

2.3 Session agenda

• 2.1 Course objectives
• 2.2 Recap: Foundations of Digital Disruption
• 2.3 Session agenda
• 2.5 Token allocation
• 2.6 Lecturer reflection
• 2.7 Wrap-up & next steps

• Today’s flow
• Group presentation order
• What groups present today
• Group 1 — Neobank threat to an incumbent
• Group 2 — Regulator’s signature intervention
• Group 3 — Big Tech in finance
• Group 4 — A market that hasn’t been disrupted
• Group 5 — A failed disruption
• Group 6 — Today’s candidate

Today’s flow

• 14:00 — Welcome & recap (5 min)
• 14:05 — Group presentations (6 min + 2 min Q&A each — see order below)
• 15:00 — Lecturer reflection (10 min)
• 15:10 — Token allocation (5 min on Moodle)
• 15:15 — Wrap-up & prep for next regular lecture (5 min)

The 6-minute time-box is firm. The lecturer signals at 5:30 and stops you at 6:00. Practice ahead. A well-rehearsed 6-minute deck is far more effective than 10 minutes of meandering — and peer tokens flow to groups that respect everyone’s time.

Group presentation order

• Angle: A neobank’s threat to an incumbent — pick one
• Slot: 14:05–14:13

• Angle: A regulator’s signature intervention (PSD2 / DORA / MiCA) — winners & losers
• Slot: 14:13–14:21

• Angle: Big Tech in finance (Apple Pay · Google Pay · Amazon Lending)
• Slot: 14:21–14:29

• Angle: A market that has not been disrupted yet — why?
• Slot: 14:29–14:37

• Angle: A failed disruption (Wirecard · FTX · Greensill) — what did failure teach?
• Slot: 14:37–14:45

• Angle: Today’s “third wave” candidate — AI agents · tokenisation · programmable money — which actually lands?
• Slot: 14:45–14:53

What groups present today

Presentation brief

Each group: 6 min + 2 min Q&A. Must include:

1. One specific angle within the topic (not the whole topic).
2. A concrete example — real company / product / regulation / incident.
3. A critical evaluation — what works, what doesn’t, who loses.
4. 1–2 discussion prompts for the room.

2.4 Group presentations

Group 1 — Neobank threat to an incumbent

• Live presentation slot.
• Suggested data points to bring: customer-acquisition cost vs LTV; CAGR; unit economics; regulatory licences obtained.
• Discussion prompt to leave hanging: “If the incumbent is forced to match the neobank’s price, can both survive?”

Live-fill slide — used to anchor the lecturer’s notes during the group’s slot. Peer tokens are not yet open; pay attention to which discussion prompts the room engages with most, because the strongest prompt usually wins disproportionate tokens.

Group 2 — Regulator’s signature intervention

• Live presentation slot.
• Pick one intervention: PSD2 (payments competition), DORA (operational resilience), MiCA (crypto-asset regulation), AI Act.
• Bring: a measurable outcome (Open Banking API call volumes; MiCA-registered firms; AI-Act enforcement actions).

Live-fill slide.

Group 3 — Big Tech in finance

• Live presentation slot.
• Pick one Big Tech product: Apple Pay, Apple Card, Google Pay, Amazon Lending, Alibaba’s Ant Group.
• Bring: penetration numbers and the strategic question (defensive moat vs offensive land-grab).

Live-fill slide.

Group 4 — A market that hasn’t been disrupted

• Live presentation slot.
• Candidates: small-business commercial lending, trade finance, syndicated loans, custody, life insurance underwriting.
• Bring: an honest analysis of why this market resisted disruption — is it regulatory? Network effects? Just unattractive economics?

Live-fill slide.

Group 5 — A failed disruption

• Live presentation slot.
• Candidates: Wirecard (2020 fraud), FTX (2022 customer-fund misappropriation), Greensill (2021 supply-chain finance collapse), 2008-era US online mortgage lenders.
• Bring: the timeline, the warning signs missed, the regulatory response.

Live-fill slide.

Group 6 — Today’s “third wave” candidate

• Live presentation slot.
• Candidates: agentic AI, RWA tokenisation, programmable money via CBDCs / stablecoins.
• Bring: the case for and the case against it landing as the next dominant force.

Live-fill slide.

2.5 Token allocation

• 2.1 Course objectives
• 2.2 Recap: Foundations of Digital Disruption
• 2.3 Session agenda
• 2.5 Token allocation
• 2.6 Lecturer reflection
• 2.7 Wrap-up & next steps

• How tokens work
• Allocation rubric
• Tonight’s leaderboard

How tokens work

• Each group receives 20 fresh tokens at the end of every flipped session.
• Distribute among the other groups — no self-allocation.
• Total must equal 20. Any distribution is allowed (all 20 to one; 5+5+5+5; etc.).
• Submit on the Moodle quiz within 5 minutes of presentations ending.
• One submission per group — nominate a representative.

The token mechanic is the grading vehicle: 50% of each session’s score comes from peer tokens, 50% from the lecturer. Tokens received are normalised against the top-scoring group that session, so an absolute number is less important than your relative standing. Submitting late means your group’s tokens for that week count as zero — you lose influence on the peer ranking but don’t penalise anyone else.

Allocation rubric

• Insight — did they teach you something you didn’t know?
• Originality — did they pick a fresh angle rather than the obvious one?
• Clarity — could you follow the argument without re-reading slides?
• Critical depth — did they appraise honestly or pitch uncritically?

These are the same axes the lecturers use — when peer and lecturer scores align, the system is working as intended. Notice that “polish” is not a rubric axis: a rough demo with sharp insight beats a slick deck with shallow content.

Tonight’s leaderboard

Group	Tokens received tonight	Cumulative
Group 1	—	—
Group 2	—	—
Group 3	—	—
Group 4	—	—
Group 5	—	—
Group 6	—	—

• This table is filled in live after the Moodle quiz closes.
• “Tonight” = tokens this week; “Cumulative” = running total across the term.
• The cumulative number is what determines the peer half of your final grade.
• A skewed distribution tonight just means the room found one or two presentations especially strong — it’s not a problem.

2.6 Lecturer reflection

• 2.1 Course objectives
• 2.2 Recap: Foundations of Digital Disruption
• 2.3 Session agenda
• 2.5 Token allocation
• 2.6 Lecturer reflection
• 2.7 Wrap-up & next steps

• Standout insights & common gaps
• Concepts to revisit next regular lecture

Standout insights & common gaps

• Standouts (live-fill): the lecturer names 2–3 groups whose specific example, critique, or framing was particularly strong.
• Common gaps (live-fill): what every group could have done better — usually one of (a) too broad an angle, (b) no concrete example, (c) no critical voice, (d) over-running the time box.

The lecturer’s commentary here is the most valuable feedback you get all term. Take notes — these are the levers you adjust next week.

Concepts to revisit next regular lecture

• Pattern recognition — which “third wave” candidate the room collectively bet on (and why) feeds directly into Lecture 3’s framing of agentic AI as the next dominant force.
• Regulatory framing — every disruption story we heard tonight had a regulator either enabling, gating, or trailing it. Lecture 3 picks up the EU AI Act thread.
• Hype vs. reality — when a group struggled to find a concrete example, that’s the signal that the hype is running ahead of deployment. Track this across the term.

The job of this slide is to bridge from tonight’s debate to next Thursday’s lecture. If your group’s presentation hit a wall on “where’s the actual deployment?”, that’s exactly the question Lecture 3 will tackle for AI specifically.

2.7 Wrap-up & next steps

• 2.1 Course objectives
• 2.2 Recap: Foundations of Digital Disruption
• 2.3 Session agenda
• 2.5 Token allocation
• 2.6 Lecturer reflection
• 2.7 Wrap-up & next steps

• Course at a glance (1/3)
• Course at a glance (2/3)
• Course at a glance (3/3)
• Prepare for next regular lecture
• See you next time
• References

Course at a glance (1/3)

Foundations of Digital Disruption in Financial Services

Week 1

22.10.2026

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

Week 2

29.10.2026

Group presentations · token allocation · discussion

• Recap of the foundations lecture
• Group presentations on digital disruption
• Token allocation & next steps

Agentic AI & LLMs in Finance

Week 3

05.11.2026

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

Week 4

12.11.2026

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

Week 5

19.11.2026

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

Week 6

26.11.2026

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

Week 7

03.12.2026

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

Week 8

10.12.2026

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

Week 9

17.12.2026

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

Week 10

07.01.2027

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

Week 11

14.01.2027

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

Week 12

21.01.2027

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

Prepare for next regular lecture

1. Skim Agrawal, Gans, and Goldfarb (2022) (Ch. 1–2) or Chen, Yang, and Liu (2023) for an LLMs-in-finance primer.
2. Track one news story about an LLM deployment in finance this week (BloombergGPT, IndexGPT, FinGPT, a regulator action). Bring the link.
3. Group discussion Sunday: pick a tentative angle for the Week-4 flipped session on Agentic AI.

The flipped session on Agentic AI runs the same format — pick your angle early, find a real deployment (not a press release), and dig for the failure modes. The strongest Week-4 presentations will be the ones that don’t take an AI vendor’s claims at face value.

See you next time

Reminder

• Token allocation: Moodle quiz is open now — submit within 5 minutes.
• Slide PDFs from all groups will be archived under Week 2 on the course site.
• Lecture 3 (next Thursday): Agentic AI & LLMs in Finance — what they actually do, where they fail, what the EU AI Act changes.

References

Agrawal, Ajay, Joshua Gans, and Avi Goldfarb. 2022. Prediction Machines: The Simple Economics of Artificial Intelligence. Updated. Boston, MA: Harvard Business Review Press.

Chen, Hongyang, Hongyang Yang, and Xiao-Yang Liu. 2023. “FinGPT: Open-Source Financial Large Language Models.” arXiv preprint arXiv:2306.06031. https://arxiv.org/abs/2306.06031.

European Parliament and Council. 2015. “Directive (EU) 2015/2366 on Payment Services in the Internal Market (PSD2).” Official Journal of the European Union, L 337/35. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32015L2366.

———. 2023. “Regulation (EU) 2023/1114 on Markets in Crypto-Assets (MiCA).” Official Journal of the European Union, L 150/40. https://eur-lex.europa.eu/eli/reg/2023/1114/oj.

———. 2024. “Regulation (EU) 2024/1689 Laying down Harmonised Rules on Artificial Intelligence (AI Act).” Official Journal of the European Union, L 2024/1689. https://eur-lex.europa.eu/eli/reg/2024/1689/oj.

Frost, Jon, Leonardo Gambacorta, Yi Huang, Hyun Song Shin, and Pablo Zbinden. 2019. “BigTech and the Changing Structure of Financial Intermediation.” BIS Working Paper 779. Bank for International Settlements. https://www.bis.org/publ/work779.htm.

Goldfarb, Avi, and Catherine Tucker. 2019. “Digital Economics.” Journal of Economic Literature 57 (1): 3–43. https://doi.org/10.1257/jel.20171452.

Philippon, Thomas. 2016. “The FinTech Opportunity.” NBER Working Paper 22476. National Bureau of Economic Research. https://doi.org/10.3386/w22476.