Andrea Landini portrait
About me

Andrea Landini.

Bocconi graduate and M.Sc. student at Universität Liechtenstein, based in Vaduz. I research quantitative finance and computational modeling, with a focus on stochastic volatility models and Monte Carlo simulations. I develop and test models using Python and C++, bridging academic theory with practical market applications.

Education
  • M.Sc. Finance, Universität Liechtenstein
  • B.Sc. Finance, Bocconi University
Skills
  • Python / C++
  • Stochastic Calculus
  • Monte Carlo Simulation
  • Machine Learning
  • Risk Modeling
Interests
  • Volatility Surface Modeling
  • Derivatives Pricing
  • Algorithmic Trading
  • Alternative Data
Experience

Career path.

July 2026 - Nov. 2026

AXA

Market/Credit Risk Analyst

Winterthur, ZH (CH)
  • MotivationI wanted to see credit and market risk from the side of a large insurer, where long-dated liabilities mean risk is managed as a portfolio rather than deal by deal. Credit assessment is where quantitative models meet judgement: a default probability or loss distribution is only useful if you understand the obligor, the structure and the assumptions behind the number.
  • ContributionThe credit risk engine and the market risk work on this site grew from the same interest. This role is a chance to bring that modelling approach to how risk is measured and reported in practice.
  • ExperienceApplying credit and market risk analysis in an insurance setting, and testing my own models against real reporting and portfolio-level requirements.
Sept. 2023 - March 2024

Deloitte

Financial Services Industry, Audit & Assurance

Milan (IT)
  • MotivationI joined to learn how banks and asset managers value their positions and judge their own risk, and to be challenged on that by people who review it for a living. Working on banking clients, I kept coming back to how credit exposures are assessed, provisioned and hedged, which is where my interest in credit risk and credit assessment began.
  • ContributionA habit of questioning every input and documenting why a model output can be trusted, which I carry into the models I build and test today.
  • ExperienceAudit & Assurance for financial services clients in Milan: a demanding way to learn what sits behind the numbers in financial statements and how assumptions move reported values.