Machine learning for financial risk management

A framework for estimating Basel IV capital requirements.

A systems-thinking essay arguing that most optimization quietly trades away buffers, slack, and resilience to make present metrics look better. It reframes efficiency as borrowing stability from the future, and shows how education, workforce, infrastructure, markets, and hardware all get optimized into fragility.

The repo contains the main topics carried out in my master's thesis on operational risk. In particular, it is described how to implement the so called Loss Distribution Approach (LDA), which is considered the state-of-the-art method to compute capital charge among large banks.

Risk-based SLA compliance and remediation pressure monitoring framework built in Power BI with custom prioritization logic.

⚖️ Explore how optimizing systems can borrow stability from the future, emphasizing resilience and balance over short-term gains.

Business Continuity Plan and organizational Risk Profile for the simulated AtlasPay environment. Includes critical process analysis, recovery priorities, impact assessment, and resilience strategies aligned with governance and operational risk best practices.

Analytical portfolio demonstrating transaction monitoring, judgment-based alert review, and Excel-driven risk analysis across fraud, AML, and KYC workflows, with a focus on regulator-safe decisioning and operational consistency.

A quantitative framework for modeling Operational Risk Capital under Basel III standards using the Loss Distribution Approach (LDA). Implements Monte Carlo convolution of Poisson frequency and Generalized Pareto (Heavy-Tailed) severity distributions to calculate the 99.9% Value at Risk (VaR).

Operational risk Monte Carlo (Poisson/Lognormal) for collision losses—methods, R code, and 99.9% capital estimate.

Strategic ROI Framework for SecOps Governance & Automation for Infrastructure Governance & Workflow Automation. Optimized for Healthcare (HIPAA-aligned) and Enterprise operations. Built to quantify "Manual Leakage" and operational risk

LDA probabilistic risk profiling — latent risk archetypes, portfolio mix drift, book-transfer segmentation

🔍 Analyze transaction data to identify fraud risks, streamline alert reviews, and ensure compliance in AML and KYC contexts using Excel-driven techniques.

A practical checklist for identifying fragile Excel spreadsheets, structural risks, and reliability issues in operational workflows.

📊 Model operational risk capital using the Loss Distribution Approach (LDA) and Monte Carlo methods for accurate economic risk assessment.

Monitor and prioritize operational risk by tracking SLA compliance, backlog growth, and escalation to detect issues before impact occurs.