The Complete Banking Masterclass

Explore asset liability management (ALM) in banking, aligning assets and liabilities to optimize risk, liquidity, capital adequacy, and profitability while ensuring regulatory compliance.

Explain funds transfer pricing (FTP) and its role in allocating funding costs across bank units at arm's length prices, aligning prices with risk, measuring profitability, and managing interest rate risk.

Explore a simplified fund transfer pricing example across deposit, lending, and treasury divisions. Learn how the ftp rate, cost of funds, maturity, and net interest margin shape internal pricing.

Banks manage credit risk by assessing borrowers, applying underwriting standards, and using diversification, collateral, monitoring, covenants, and stress testing to limit loan losses and protect profitability.

Explore how credit default swaps transfer or hedge credit risk by linking a reference obligation to a protection seller, with premiums, notional amounts, and potential cash or physical settlement.

Explore securitization by packaging illiquid assets into tradable securities (abs, mbs, cdos, cds) to boost liquidity and transfer risk to investors.

Explore the securitization process, from asset selection through SPV structures and tranching, and examine how subprime mortgage securitization and rating agency failures contributed to the 2008 global financial crisis.

Explore how credit spread risk affects banks' profitability, asset valuations, liquidity, funding costs, and capital adequacy, and how diversification, hedging, and stress testing mitigate these impacts.

Identify currency risk in banks' cross-border activities, trading, loan portfolios, and investment holdings, and learn hedging, diversification, netting, and stress testing to manage foreign exchange exposure.

Execute liquidity actions such as asset liquidation and liabilities management, access interbank and repo funding, central bank facilities, and government guarantees, while communicating with regulators and stakeholders.

Explore how repurchase agreements work, including types, collateral, haircuts, and margin calls, and examine their role in funding liquidity and central bank policy.

Explain how maturity transformation and liquidity transformation intertwine. Show how short-term funding funds long-term illiquid assets and creates run risk, driving fragility and potential systemic crises.

Explore Basel III's three pillars—pillar one minimum capital requirements for credit, market, and operational risk—along with pillar two's supervisory review and pillar three's market discipline through disclosure.

Explore how data management and data governance reinforce each other to secure, cleanse, and analyze banking data through ETL, data quality, data security, privacy, and regulatory compliance.

Boost data governance and secure integration in banking by eliminating silos, ensuring data quality through validation and AI-powered cleansing, and applying API-driven ETL to compliant data lakes and warehouses.

Discover how data warehouses and data lakes serve banking analytics: warehouses store structured data for reporting and compliance, while lakes hold unstructured data for AI, machine learning, and real-time insights.

Explore why legacy banking systems persist as the system of record, driven by regulatory trust and complex dependency chains, and compare modernization, transformation, and the hybrid approach to improve agility.

Unify banking data with master data management to create a single trusted golden record, ensure data quality, and enable real time, compliant data integration across core banking, CRM, and channels.

Unify data from core banking, CRM, risk, and compliance for real-time, 360-degree customer insights. Enable AI-driven personalization, fraud detection, regulatory reporting, and secure integration across legacy and modern systems.

Explore how BI, data analytics, ML, and AI differ and overlap in banking, with use cases like profitability and risk reporting, churn analysis, and fraud detection.

Explain three banking BI pillars: risk management dashboards (default probability, expected credit loss, value-at-risk), bank steering with granular profitability insights, and regulatory reporting with data lineage and audit trails.

Apply a data-driven, AI-powered framework to detect, prevent, and report financial crime in banking using data analytics, real-time transaction monitoring, AML, KYC, sanctions screening, and RegTech technologies.

Banking uses customer data analytics and personalization to tailor products from transaction history and demographics, segment by needs and life stage, and deliver predictive AI offers while ensuring privacy.

Learn how banking architecture under pressure adapts across technology, regulation, customer experience, cost, and legacy constraints, using APIs, modular event-driven design, strangler pattern, RegTech, and cloud-based resilience.

Understand how banking shifts to a platform, real-time, data-driven, cloud-based system, with embedded finance, APIs, and new money and trust models reshaping services, risk, and governance.

Examine why legacy systems persist as the system of record and how modernization and transformation reshape regulatory trust, risk, and interdependencies through a hybrid two-speed approach.

Explore how cloud computing and modular banking transform modern banks into scalable, flexible platforms by using APIs, modular services, infrastructure abstraction, and rapid deployment.

Explore the cloud vs on-prem tradeoffs for banks, balancing control, agility, security, data residency, and regulatory compliance. Understand scalability, cost dynamics, governance, and the role of hybrid or multi-cloud strategies.