Lernziel-Analyse Learning Goal Analysis

Kursinhalt vs. Modulbeschreibung — Digital Finance Course Content vs. Module Description — Digital Finance

7LernzieleGoals 48LektionenLessons 14.9kTrefferHits

Modul: Digital Finance (BSc) · Umfang: 48 Lektionen, 4 Module, 1.151 Folien, 663 Charts
Ergebnis: Alle 7 Lernziele sind umfassend abgedeckt. Jedes Lernziel wird von 3–12+ dedizierten Lektionen adressiert. Die Inhalte sind modulübergreifend verankert. Module: Digital Finance (BSc) · Scope: 48 lessons, 4 modules, 1,151 slides, 663 charts
Result: All 7 learning goals are comprehensively covered. Each goal is addressed by 3–12+ dedicated lessons. Content is anchored across modules.

Abdeckungsmatrix Coverage Matrix

LG	LernzielLearning Goal	TrefferHits	Primäre LektionenPrimary Lessons	AbdeckungCoverage
LG1	FinTech-Geschäftsmodelle und deren Wertschöpfung erklären erklärenExplain FinTech business models and their value creation explain	813	L01 Intro FinTech, L04 Neobanks, L07 P2P Lending, L08 Robo-Advisors, L09 InsurTech, L12 Business Models	StarkStrong
LG2	Moderne Zahlungssysteme und deren Infrastruktur analysieren analysierenAnalyze modern payment systems and their infrastructure analyze	2,216	L02 Payments, L03 Mobile Wallets, L39 Payment Rails, L48 CBDC	Sehr starkVery strong
LG3	Open Banking und API-basierte Finanzdienstleistungen beschreiben beschreibenDescribe Open Banking and API-based financial services describe	947	L05 Open Banking, L38 Core Banking, L47 Data Vendors	GutGood
LG4	Grundlagen der Blockchain-Technologie verstehen verstehenUnderstand blockchain technology fundamentals understand	4,979	L13–L24 (gesamtes Modul 2: Hashing, Konsens, Smart Contracts, DeFi, Stablecoins, Sicherheit, Regulierung)L13–L24 (entire Module 2: Hashing, Consensus, Smart Contracts, DeFi, Stablecoins, Security, Regulation)	Sehr starkVery strong
LG5	Regulatorische Rahmenbedingungen (PSD2, MiFID II, Basel) einordnen einordnenContextualize regulatory frameworks (PSD2, MiFID II, Basel) contextualize	2,568	L10 RegTech, L11 Regulatory Frameworks, L24 Blockchain-Regulierung, L36 AI-Regulierung, L43 RegTech ComplianceL10 RegTech, L11 Regulatory Frameworks, L24 Blockchain Regulation, L36 AI Regulation, L43 RegTech Compliance	Sehr starkVery strong
LG6	Datengetriebene Ansätze in der Finanzbranche anwenden anwendenApply data-driven approaches in the financial industry apply	1,379	L25–L36 (gesamtes Modul 3: Regression, Klassifikation, NLP, Explainability, Fraud Detection)L25–L36 (entire Module 3: Regression, Classification, NLP, Explainability, Fraud Detection)	Sehr starkVery strong
LG7	Grundlagen traditioneller Finanzinfrastruktur erklären erklärenExplain traditional financial infrastructure fundamentals explain	2,013	L38 Core Banking, L39 Payment Rails, L41 Market Microstructure, L44 Capital Markets Tech, L45 Derivatives Tech	Sehr starkVery strong

Treffer = Anzahl Keyword-Matches in allen .tex-Dateien (Folien, Quizzes, Übungen). Primäre Lektionen = höchste Trefferdichte. Hits = keyword match count across all .tex files (slides, quizzes, exercises). Primary lessons = highest hit density.

Detailanalyse pro Lernziel Detailed Analysis per Learning Goal

LG1 — FinTech-Geschäftsmodelle und deren Wertschöpfung erklärenExplain FinTech business models and their value creation

Kernlektionen: L01 (Intro FinTech), L04 (Neobanks), L07 (P2P Lending), L08 (Robo-Advisors), L09 (InsurTech), L12 (Business Models — 33 Treffer, höchste Dichte)
Modul 1 ist vollständig diesem Lernziel gewidmet. L12 behandelt explizit Revenue Models, B2B/B2C, Plattformökonomie und Wertschöpfungsketten. Core lessons: L01 (Intro FinTech), L04 (Neobanks), L07 (P2P Lending), L08 (Robo-Advisors), L09 (InsurTech), L12 (Business Models — 33 hits, highest density)
Module 1 is entirely dedicated to this learning goal. L12 explicitly covers revenue models, B2B/B2C, platform economics, and value chains.

LG2 — Moderne Zahlungssysteme und deren Infrastruktur analysierenAnalyze modern payment systems and their infrastructure

Kernlektionen: L02 (Payments Fundamentals — 96 Treffer), L03 (Mobile Wallets — 29 Treffer), L39 (Payment Rails — 125 Treffer, höchste Dichte), L48 (CBDC — 40 Treffer)
SWIFT, SEPA, Visa/Mastercard, Apple Pay, Real-Time Payments und Cross-Border-Zahlungen sind umfassend repräsentiert. Abdeckung sowohl aus FinTech-Perspektive (L02–L03) als auch aus Infrastruktur-Perspektive (L39). Core lessons: L02 (Payments Fundamentals — 96 hits), L03 (Mobile Wallets — 29 hits), L39 (Payment Rails — 125 hits, highest density), L48 (CBDC — 40 hits)
SWIFT, SEPA, Visa/Mastercard, Apple Pay, real-time payments, and cross-border payments are comprehensively represented. Covered from both the FinTech perspective (L02–L03) and the infrastructure perspective (L39).

LG3 — Open Banking und API-basierte Finanzdienstleistungen beschreibenDescribe Open Banking and API-based financial services

Kernlektion: L05 (Open Banking — 67 Treffer, mit Abstand höchste Dichte)
Unterstützend: L38 (Core Banking — 14 Treffer zu APIs), L47 (Data Vendors — 26 Treffer)
PSD2, AISP, PISP, TPP, Account Aggregation und Screen Scraping sind alle präsent. Der Schwerpunkt liegt auf L05, mit ergänzenden Querverweisen in anderen Lektionen. Core lesson: L05 (Open Banking — 67 hits, by far the highest density)
Supporting: L38 (Core Banking — 14 API-related hits), L47 (Data Vendors — 26 hits)
PSD2, AISP, PISP, TPP, account aggregation, and screen scraping are all present. The focus is on L05, with supplementary cross-references in other lessons.

LG4 — Grundlagen der Blockchain-Technologie verstehenUnderstand blockchain technology fundamentals

Kernlektionen: L13 (What is Blockchain — 94 Treffer), L14 (Hashing — 82), L15 (Public Key Crypto — 29), L16 (PoW — 62), L17 (PoS — 54), L18 (Bitcoin — 45), L19 (Ethereum/Smart Contracts — 40), L20 (Tokens — 92), L21 (DeFi — 45), L22 (Stablecoins — 51), L23 (Security — 32), L24 (Regulierung — 86)
Gesamtes Modul 2 (12 Lektionen) = am stärksten abgedecktes Lernziel mit 4.979 Treffern. Core lessons: L13 (What is Blockchain — 94 hits), L14 (Hashing — 82), L15 (Public Key Crypto — 29), L16 (PoW — 62), L17 (PoS — 54), L18 (Bitcoin — 45), L19 (Ethereum/Smart Contracts — 40), L20 (Tokens — 92), L21 (DeFi — 45), L22 (Stablecoins — 51), L23 (Security — 32), L24 (Regulation — 86)
Entire Module 2 (12 lessons) = most heavily covered learning goal with 4,979 hits.

LG5 — Regulatorische Rahmenbedingungen (PSD2, MiFID II, Basel) einordnenContextualize regulatory frameworks (PSD2, MiFID II, Basel)

Kernlektionen: L10 (RegTech — 77 Treffer), L11 (Regulatory Frameworks — 72), L43 (RegTech Compliance — 99, höchste Dichte), L24 (Blockchain-Regulierung — 43), L36 (AI-Regulierung — 34)
PSD2, MiFID II, Basel, GDPR, DORA, AML und KYC sind alle explizit vorhanden. Regulierung wird in jedem Modul adressiert: FinTech (L10–L11), Blockchain (L24), AI/ML (L36), Traditionell (L43). Exzellente modulübergreifende Integration. Core lessons: L10 (RegTech — 77 hits), L11 (Regulatory Frameworks — 72), L43 (RegTech Compliance — 99, highest density), L24 (Blockchain Regulation — 43), L36 (AI Regulation — 34)
PSD2, MiFID II, Basel, GDPR, DORA, AML, and KYC are all explicitly present. Regulation is addressed in every module: FinTech (L10–L11), Blockchain (L24), AI/ML (L36), Traditional (L43). Excellent cross-module integration.

LG6 — Datengetriebene Ansätze in der Finanzbranche anwendenApply data-driven approaches in the financial industry

Kernlektionen: L25 (Intro AI/ML — 35 Treffer), L27 (Regression — 57), L28 (Klassifikation — 45), L29 (Algorithmischer Handel — 19), L30 (Credit Scoring — 9), L31 (Fraud Detection — 11), L32 (NLP — 65), L35 (Explainability — 30)
Gesamtes Modul 3 (12 Lektionen) diesem Lernziel gewidmet. ML, NLP, SHAP, Feature Importance, Random Forest, Neural Networks, Regression und Klassifikation sind alle präsent.
Das Verb «anwenden» wird durch interaktive Demos (demos/module_03_ai_ml/) und Projekte (Projekt 3: Credit Risk, Projekt 6: Fraud Detection) unterstützt. Core lessons: L25 (Intro AI/ML — 35 hits), L27 (Regression — 57), L28 (Classification — 45), L29 (Algorithmic Trading — 19), L30 (Credit Scoring — 9), L31 (Fraud Detection — 11), L32 (NLP — 65), L35 (Explainability — 30)
Entire Module 3 (12 lessons) is dedicated to this learning goal. ML, NLP, SHAP, feature importance, random forest, neural networks, regression, and classification are all present.
The verb «apply» is supported by interactive demos (demos/module_03_ai_ml/) and projects (Project 3: Credit Risk, Project 6: Fraud Detection).

LG7 — Grundlagen traditioneller Finanzinfrastruktur erklärenExplain traditional financial infrastructure fundamentals

Kernlektionen: L37 (Financial Markets — 24 Treffer), L38 (Core Banking — 41), L39 (Payment Rails — 56), L40 (Electronic Trading — 20), L41 (Market Microstructure — 7), L44 (Capital Markets Tech — 78, höchste Dichte), L45 (Derivatives Tech — 34)
Core Banking, Clearing, Settlement, RTGS, ACH, Correspondent Banking, CSD, CCP, Order Books, Matching Engines und FIX Protocol sind alle präsent. Modul 4 ist vollständig diesem Lernziel gewidmet. Core lessons: L37 (Financial Markets — 24 hits), L38 (Core Banking — 41), L39 (Payment Rails — 56), L40 (Electronic Trading — 20), L41 (Market Microstructure — 7), L44 (Capital Markets Tech — 78, highest density), L45 (Derivatives Tech — 34)
Core banking, clearing, settlement, RTGS, ACH, correspondent banking, CSD, CCP, order books, matching engines, and FIX protocol are all present. Module 4 is entirely dedicated to this learning goal.

Lektion-zu-Lernziel-Zuordnung Lesson-to-Learning-Goal Mapping

LektionLesson	LG1	LG2	LG3	LG4	LG5	LG6	LG7
L01 Intro FinTech	P	S	S		S		S
L02 Payments Fundamentals	S	P			S		P
L03 Mobile Wallets	S	P
L04 Neobanks	P				S
L05 Open Banking	S	S	P		S
L06 Digital Identity	S				S
L07 P2P Lending	P				S
L08 Robo-Advisors	P					S
L09 InsurTech	P				S
L10 RegTech	S				P
L11 Regulatory Frameworks			S		P
L12 Business Models	P
L13 What is Blockchain				P
L14 Hashing				P
L15 Public Key Crypto				P
L16 Proof of Work				P
L17 Proof of Stake				P
L18 Bitcoin Architecture				P
L19 Ethereum & Smart Contracts				P
L20 Tokens				P
L21 DeFi				P
L22 Stablecoins				P
L23 Security				P
L24 Regulation & Future				P	P
L25 Intro AI/ML						P
L26 Financial Data						P
L27 Regression						P
L28 Classification						P
L29 Algorithmic Trading						P
L30 Credit Scoring						P
L31 Fraud Detection & AML					S	P
L32 NLP in Finance						P
L33 Robo-Advisors ML						P
L34 Market Prediction						P
L35 Explainability & Bias					S	P
L36 AI Regulation					P	S
L37 Financial Markets		S	S		S		P
L38 Core Banking		S	P		S		P
L39 Payment Rails		P					P
L40 Electronic Trading			S		S		P
L41 Market Microstructure							P
L42 Risk Management					P
L43 RegTech Compliance		S	S		P		S
L44 Capital Markets Tech	S		S				P
L45 Derivatives Technology							P
L46 Wealth Management	S				S
L47 Data Vendors			P			S
L48 CBDC & Future		P		S

P = Primär (Hauptfokus der Lektion) · S = Sekundär (relevanter Nebenbezug) P = Primary (main focus of lesson) · S = Secondary (relevant supporting reference)

Bloom-Taxonomie-Abgleich Bloom's Taxonomy Alignment

LG	Verb (Bloom-Stufe)Verb (Bloom Level)	Nachweis im KursEvidence in Course
LG1	erklären (Verstehen)explain (Understand)	Deskriptive und erklärende Inhalte in L01–L12: Geschäftsmodell-Diagramme, Wertschöpfungsketten, FallstudienDescriptive and explanatory content in L01–L12: business model diagrams, value chains, case studies
LG2	analysieren (Analysieren)analyze (Analyze)	Vergleichende Charts und Case Studies in L02, L03, L39: Kostenvergleiche, Infrastruktur-Diagramme, Benchmark-AnalysenComparative charts and case studies in L02, L03, L39: cost comparisons, infrastructure diagrams, benchmark analyses
LG3	beschreiben (Verstehen)describe (Understand)	Architektur-Diagramme und Flussdarstellungen in L05: API-Architektur, PSD2-Flows, Aggregation-PatternsArchitecture diagrams and flow charts in L05: API architecture, PSD2 flows, aggregation patterns
LG4	verstehen (Verstehen)understand (Understand)	Progressive Vertiefung über 12 Lektionen: von Grundkonzepten (L13) über Kryptografie (L14–L15) bis zu Anwendungen (L19–L22)Progressive depth across 12 lessons: from fundamentals (L13) through cryptography (L14–L15) to applications (L19–L22)
LG5	einordnen (Analysieren)contextualize (Analyze)	Vergleichende Regulierungsrahmen über Jurisdiktionen: EU vs. US vs. Asien in L10, L11, L24, L36, L43Comparative regulatory frameworks across jurisdictions: EU vs. US vs. Asia in L10, L11, L24, L36, L43
LG6	anwenden (Anwenden)apply (Apply)	Interaktive Demos (`demos/module_03_ai_ml/`), Projekte (P03 Credit Risk, P06 Fraud Detection), Jupyter Notebooks mit Hands-on-CodeInteractive demos (`demos/module_03_ai_ml/`), projects (P03 Credit Risk, P06 Fraud Detection), Jupyter notebooks with hands-on code
LG7	erklären (Verstehen)explain (Understand)	Infrastruktur-Diagramme, Systemarchitekturen und Prozessflows in L38–L45: Core Banking, Payment Rails, Capital MarketsInfrastructure diagrams, system architectures, and process flows in L38–L45: Core Banking, Payment Rails, Capital Markets

Analyse erstellt am 12. März 2026 · Methodik: Keyword-Matching über alle .tex-Dateien (Folien, Quizzes, Übungen) der 48 v3-Lektionen Analysis created March 12, 2026 · Methodology: keyword matching across all .tex files (slides, quizzes, exercises) of the 48 v3 lessons