Actuarial Sciences Risk And Data Analysis Milano

The course introduces to financial accounting, financial statements, and reporting systems of insurance companies under IFRSs and the Solvency II framework.
At the end of the first module the student will be able to:
Know and understand the complexity of the insurance reporting system;
Know and understand the basics of the Solvency II framework;
Know and understand the fair value measurement approach for bonds and technical provisions;
Apply its knowledge to solve some specific problems (e.g., bond and technical provisions measurement, asset liability management);
Know and understand the measurement bases used in IFRS 9 for financial instruments
The course introduces to financial accounting, financial statements, and reporting systems of insurance companies under IAS/IFRSs and the Solvency II framework.
At the end of the second module the student will be able to:
Know and understand the IFRS 17 and the structure of the insurance financial statement under IFRSs;
Know the second pillar of Solvency II;
Apply its knowledge to solve some specific problems (e.g., IFRS 17 financial statement).

The complexity of the insurance reporting system (local GAAPs, IAS/IFRSs, Solvency II, MCEV).
Introduction to Solvency II
Introduction to Solvency II;
The first pillar of Solvency II
Assets and liabilities: fair value measurement
Fair value, IFRS 13 and basics of fair value measurement for financial instruments and technical provisions
Plain vanilla financial instruments (bonds, stocks and financial options)
Fair value measurement techniques
Technical provision measurement (Solvency II)
Cash flows projection and expected cash flows computation
Risk-free interest rate term structure (discounting)
Risk margin (risk adjustment)
Stochastic vs. deterministic measurement of technical provisions
Market risks in insurance business and basics of Asset-Lability Management (ALM)
Solvency Capital Requirement and the Solvency Ratio
Market risks in insurance business and basics of Asset-Liability Management
The IFRS 9: classification and measurement of financial instruments
Lectures and numerical exercises. An optional teamwork will be assigned.
Introduction to IFRS Financial Statement and IFRS 17
The General Model: fulfilment cash flows (FCF) and contractual service margin initial measurement (CSM)
The IFRS 17 approach under the General Model
Main differences between the IFRS approach and the Solvency II approach in the measurement of insurance contracts
Fulfilment Cash Flows: the building block approach
The initial measurement of the Contractual Service Margin
Subsequent measurement of the insurance liability and the FCF and CSM dynamics
The (IFRS 17) balance sheet and the income statement
Financial Statement analysis and performance measurement
The Variable-fee approach
The premium allocation approach and the Liability for incurred claims
The second pillar of Solvency II
Lectures and numerical exercises. An optional teamwork will be assigned.

Written examination (50%) to assess the ability of the student in the resolution of some specific problems (e.g. bonds and insurance contracts fair value measurement, ALM, IFRS 9 measurement of financial instruments) and an oral interview (50%) to assess the knowledge and understanding of the topics. The optional teamwork contributes to the final grade (additional points).
Written examination to assess the ability of the student in the resolution of some specific problems (50%) and a oral examination (50%) to assess the knowledge and understanding of the topics. The optional teamwork contributes to the final grade (additional points).

A. Floreani, Lecturer notes, 2026-27, Available on BlackBoard.
A. Floreani, Lecturer notes, 2026-27, Available on course BlackBoard.

The course aims to provide students with a thorough and structured understanding of the main decision-making problems in property and casualty insurance, with particular reference to premium rating, claims reserving, technical liabilities, reserve risk and reinsurance.
The course is designed to equip students with the quantitative and actuarial tools required to analyse non-life insurance portfolios, evaluate premium rates and loss reserves, assess the variability of reserve estimates and understand the main regulatory implications under the Solvency II framework. Particular attention is devoted to the connection between theoretical models and practical applications based on empirical data and actuarial case studies.
At the end of the course, students will have acquired the following knowledge and skills.
Knowledge and understanding
Students will know and understand the main deterministic and stochastic actuarial methods for claims reserving, the principles underlying premium rating in non-life insurance, the evaluation of technical liabilities under Solvency II and the main features of reinsurance arrangements and pricing methods.
Applying knowledge and understanding
Students will be able to determine rate premiums and evaluate loss reserves using deterministic and stochastic methods, including Chain-Ladder, Bornhuetter-Ferguson, Fisher-Lange, Frequency-Severity, Mack, Bootstrapping, Over-Dispersed Poisson and Collective Risk Models. Students will also be able to estimate the volatility of reserve estimates and calculate the solvency capital requirement for reserve risk using standard formula approaches, undertaking-specific parameters and partial internal models.
Making judgements, communication and learning skills
Students will be able to interpret actuarial results, compare alternative reserving and risk assessment methods, evaluate the reliability and limitations of the models applied and discuss the implications of the results in a technically rigorous manner. They will also develop the ability to communicate actuarial analyses and methodological choices using appropriate terminology and to apply the acquired tools autonomously to practical insurance problems.

The course covers the following topics:
Main deterministic statistical-actuarial methods for claims reserve.
Paid and Incurred Chain-Ladder methods,
Bornhuetter-Ferguson method.
Average cost methods: Fisher-Lange and Frequency-Severity
Solvency II criteria for the evaluation of technical liabilities
Best estimate and risk margin.
Discounting
Premium reserve and claims reserve under Solvency II framework
Stochastic methods for claims reserving.
Distribution-Free Chain-Ladder - Mack formula.
Predictive distribution of claims reserve: Bootstrapping, Over-Dispersed Poisson methods, Collective risk model.

• Variability of run-off and one-year loss reserves and comparisons between alternative approaches.
  The Merz-Wuthrich formula
  Re-reserving approaches
• Estimation of capital requirement for reserve risk under Solvency II (standard formula and partial internal model).
• Aggregation and copula functions
  Case studies on the variability of the loss reserve and on the capital requirement for reserve risk
  Reinsurance: main forms, technical features and pricing methods.
  Premium rating for motor third-party liabilities: some practical aspects.
  The course is based on lectures, practical exercises and the discussion of actuarial case studies. Theoretical concepts will be introduced during lectures and then illustrated through numerical applications, empirical examples and Excel-based exercises.
  Some classes will be devoted to guided practical work aimed at consolidating the methods discussed in class and preparing students for the written examination. Seminars and applied case studies may also be used to deepen specific topics related to reserving, Solvency II and reinsurance.

The exam consists of both a written and an oral examination.
The written examination includes open-ended questions and exercises, also with the use of Excel software. The oral examination is compulsory and can be taken only after passing the written examination with a mark equal to or greater than 18/30.
The final mark is calculated as the weighted average of the written and oral examinations: 40% written examination and 60% oral examination.
If the exam is failed, both the written and oral examinations must be taken again.

Given the specific structure of the course and the long-term nature of some of the topics analysed, no single textbook covers the entire syllabus.
Compulsory teaching materials, including lecture notes, slides and Excel files, will be made available on the Blackboard platform throughout the course.
Additional readings and supplementary instructional materials will also be made available on Blackboard.
Optional further reading
Casualty Actuarial Society, Estimating Unpaid Claims using basic techniques, 2009.
P.D. England-R.J. Verrall, Stochastic claims reserving in general insurance, British Actuarial Journal 8/3, 443-518, 2002.
S.A. Klugman-H.H. Panjer-G.E. Willmot, Loss Models: From Data to Decisions, 4th Edition, Wiley, 2012.
T. Mack, Distribution-free calculation of the standard error of chain ladder reserves estimates, ASTIN Bulletin 23/2, 213-225, 1993.
M. Merz-M.V. Wüthrich, Modelling the claims development result for solvency purposes, CAS E-Forum, Fall 2008, 542-568, 2008.
G. Taylor, Loss Reserving: An Actuarial Perspective, Kluwer, 2000, Boston.
M.V. Wüthrich-M. Merz, Stochastic Claims Reserving Methods in Insurance, Wiley Finance, 2008.

The course aims to provide students with sophisticated mathematical tools necessary for understanding banking, financial and insurance models, whose phenomena under consideration are expressed in quantitative terms.
Expected learning outcomes
The expected learning outcomes are the ability to read, interpret and manipulate the quantitative aspects of banking, financial and insurance phenomena.
At the end of the course, students will possess technical skills accompanied by an understanding of their specific applications. In particular:
They will be familiar with the mathematical tools necessary to to read, interpret and manipulate the quantitative aspects of banking, financial and insurance phenomena.
They will be able to solve differential equations, recognize a martingale in discrete or continuous time, analyze a Markov chain in discrete time
recognize which tool to use to model concrete situation
They will be able to understand and interpret a problem and its data, identifying the appropriate mathematical tool needed to model concrete situation.
They will be able to describe and analyze a model in clear and rigorous language.

The course syllabus is structured as follows:
First Module (4 credits)
Linear differential equations and systems with constant coefficients: solutions by means of characteristic equation or by means of Laplace transform.
Differential equation with separation of variables.
Second Module (5 credits)
Conditional expectation.
Stochastic processes in discrete times: marttingales, submartingales and supermartingales; stopping times and optional sampling theorem.
Time-homogenoeus Markov chains in discrete times: graph representation, transition matrix, classification of states, absorbing and stationary probabilities.
Stochastic processes in continuous time: martingales, submartingales and supermartingales; Wiener process (brownian motion) and Poisson process.
The course will consist of classroom lectures in which theoretical content will be presented, accompanied by extensive examples and exercises with a focus on financial and insurance applications.

The exam will be a written assessment consisting of open-ended questions and/or multiple-choice questions, both theoretical and applied, covering the topics of the entire course (first and second modules). The point value of each question will be indicated in the exam text. The maximum score is 32 points. The points obtained on the written exam, rounded to the nearest integer (rounded up if the decimal part is greater than or equal to 0.5), will constitute the final mark obtained in the course. Honors marks will be awarded in the event the student obtains a final rounded score of at least 31. A mock test with the same format as the actual exam will be published on Blackboard.
Alternatively, the exam can be passed by taking two partial exams, one for each module, administered at the end of the respective module. Further details regarding the structure and procedure of the partial exams will be provided during the course and on the Blackboard platform.
During the exam, students are expected to demonstrate knowledge they have acquired in the course. The ability to solve the exam exercises will demonstrate the student’s level of learning achieved, as well as their ability to apply knowledge and exercise independent judgment. The presentation of solutions will showcase their ability to communicate using technical language.

Selected materials (slides, exercises, mock exams) will be made available on the course Blackboard site.

The course is intended in two parts.
The first part will be mainly focused on an introduction to Python programming language with a special focus on examples from mathematical statistics (the aim is to recap, mostly from an applied pov, some results that will be necessary in the second part of the course) and how to manage datasets from the insurance market.
The second part is mostly focused on an introduction to GLM models. By using the standard frequency-severity approach, we will use the Poisson and Gamma GLM models to compute the net premiums on the basis of appropriate customers’ profile. Results will be compared with techniques based upon machine/statistical learning algorithms. Hints will be given in case of deviation from standard assumptions as well as extensions to include artificial intelligence tools.
On successful completion of the course participants are expected to possess:
knowledge of concepts, terms and methods of the most used statistical learning techniques and their strengths and weaknesses (DD1- Knowledge and understanding);
ability to correctly apply statistical learning methods to insurance, economics and management problems (DD2- Applying knowledge and understanding);
quantitative thinking addressed to make independent judgements, driven by application of statistical learning methods (DD3- Making judgements);
ability to present statistical learning arguments and the conclusions from them, by means of the extraction of qualitative information from quantitative data, with clarity and accuracy and in forms that are suitable for the audiences being addressed, both orally and in writing (DD4-Communication);
mastery of statistical learning methods, rigorous reasoning and data-driven decision-making, useful for quantitative analyses in other courses of the curriculum, as well as for analyses required in careers in insurance and in all fields involving management of data (DD5- Lifelong learning skills).

Introduction to Python programming and data analysis.
1. From Excel to Python.
2. Objects: data frame and “friends”. Functions. Libraries. Data import. Graphics tools
3. Some remarks from mathematical statistics useful for the master degree in Actuarial sciences.
4. Likelihood and inference: a recap
5. Some details about Linear and Nonlinear models. The Gauss-Newton algorithm.
Statistical learning
1.1Supervised and unsupervised learning. Assessing model accuracy.
2. From linear Gaussian models to Generalized Linear Models. Inference.
3. GLMs for count, continuous and categorical responses. Variable selection.
4. Tree based methods. Regression trees and classification trees.
5. Neural networks with a special emphasis on their application to insurance datasets.
Lectures with methodological results and applications with examples from actuarial, business, economic, financial, health case studies.

The exam will consist in two parts: a mix of problems on Python and a case study to be solved with Python and a written exam consisting of two open-ended questions on the methodological subjects. An optional question concerning the interpretation of a Python code can also be answered.
Aim of the exam is to assess reasoning analytic abilities on the course subjects. Language properties and communication abilities are also assessed.

Lecturer’s notes / slides
Elective readings
G. James-D. Witten-T. Hastie-R. Tibshirani, An Introduction to Statistical Learning with application in Python, Springer, New York, 2023, https://www.statlearning.com/.
Wuthrich, Mario V. et Al., AI Tools for Actuaries (>May 09, 2025). Available at https://ssrn.com/abstract=5162304

The course provides students with the econometric concepts necessary for the study of quantitative economic and financial phenomena, as well as the tools and techniques for empirical analysis. To this end, the lectures are accompanied by a cycle of practical tutorials. During practical exercises, the R software will be used to make the theoretical arguments presented operational.
At the end of the course, students will have acquired:
the necessary theoretical and practical knowledge to carry out independent empirical analyses with economic and financial data. In particular, they will be able to formulate empirical models for the verification of economic and/or financial hypotheses, estimate them, carry out appropriate diagnostic tests to verify the accuracy of the results obtained, and to use the estimated models for both descriptive and predictive purposes;
the necessary skills to understand empirical scientific articles on economic and financial issues;
familiarity with an econometric/statistical software to carry out autonomous calculations.

Linear regression model:
The linear regression model is introduced. The numerical properties of the least squares method are shown, highlighting the implications of the Frish-Waugh-Lovell theorem. The necessary conditions for the correctness of the OLS estimator are discussed. The Gauss-Markov theorem is presented and its implications are highlighted. The asymptotic properties of the OLS estimator are studied. The problems of multicollinearity, outliers, and influential observations are discussed.
Inference on OLS Estimates:
The main statistical tests regarding the regression model coefficients are presented. Exact and approximate confidence intervals for the estimates are introduced.
Interpretation and Comparison of Linear Regression Models:
The practical use of the linear regression model, the choice of regressors, the interpretation of coefficients, and specification tests are examined.
Heteroskedasticity and Autocorrelation:
The assumptions about errors underlying the classical linear model are removed. In particular, the possibility of heteroskedastic and autocorrelated errors is introduced. Their consequences, diagnostic tests, and possible solutions are examined. Specifically, robust inference methods and the GLS estimator are studied.
Estimation Using Instrumental Variables (IV):
Problems of estimating a parameter when the regressor is correlated with the error term are presented. The solution based on the use of instrumental variables is presented. The GMM estimator is introduced.
Maximum Likelihood Estimator (MLE):
The maximum likelihood estimator and diagnostic tests based on the likelihood method are introduced.
Models with Limited Dependent Variables:
Models for binary variables and count data are considered. The problem of causal inference is introduced. Duration models are considered.
Introduction to Time Series Analysis:
The notion of a stochastic process is presented; the estimation of an autoregressive model; the estimation of a moving average model; the random walk stochastic process is introduced. Finally, tests for checking the presence of unit roots in the data are presented.
Introduction to Panel Data Analysis:
Fixed effects and random effects models are presented. The Hausman test is introduced. Possible extensions of panel data models are considered.
The course is divided into theoretical lessons (49 hours) and supplemented with a cycle of tutorials. In the empirical analyses the software R will be used.

The exam consists of a compulsory written test for all students. Through the written test, students will have to demonstrate that they know the theoretical foundations the econometric theory, and that they have acquired the necessary skills to perform independent empirical analyses.
The written test is divided into two sections: the first section deals with econometric theory, while the second section deals with applied econometrics, in which students are asked to analyse and comment the estimation results of an empirical model.

Verbeek, Marno. A guide to modern econometrics. John Wiley & Sons, 2017. Buy from VP

This course provides the students with key quantitative tools for the analysis of financial markets and for the study of optimal decisions made by rational agents. We will examine a set of models that describe the dynamics of asset values under uncertainty. The common thread will be the principles of absence of arbitrage and of market completeness. We will then investigate the technical nature and the economic/financial nuances of the solutions to optimization problems that are associated with rational decision making. We will then carefully study the dynamics of asset values exposed to market risk, as well as to interest rate risk, with a particular focus on risk premia. Theory will be constantly exemplified with classroom applications.
At the end of the course, the student will be familiar with a series of models describing the dynamics of financial asset prices in the presence of different sources of risk. The student will be able to employ these models for asset pricing purposes, as well as for asset allocation decisions.

One-period financial markets
At the end of this part of the course students will be able to:

• construct investment strategies and spot first- and second-type arbitrage opportunities;
• associate the no-arbitrage assumption with the existence of a risk-neutral probability measure;
• relate the concept of market completeness to the one of payoff profiles’ replication;
• find no-arbitrage prices for claims that provide given payoff profiles.
  Optimization techniques for economics and finance
  At the end of this part of the course students will be able to:
• properly set up optimization problems related to the unconstrained/constrained objectives of rational agents;
• work out either paper-and-pencil or numerical solutions of such problems;
• appreciate the underpinnings of the solution techniques employed;
• grasp the economic/financial interpretation of the solutions obtained.
  Asset values: levels and dynamics
  At the end of this part of the course students will be able to:
• comprehend the quantitative nature of market risk as well as of interest rate risk;
• understand the equilibrium return on an asset exposed to one of such risks;
• understand the equilibrium price of a non-underlying asset exposed to market risk;
• understand the equilibrium price of a fixed-income asset exposed to interest rate risk.
  The course is based on frontal teaching with classroom applications of the theory covered.

The valuation mark is based on a final written exam, which is made of open and/or multiple-choice questions, aimed at assessing the understanding the theory and the applications of the topics studied. The score awarded for each question is specified in the text of the exam. The total score obtained in the written exam, rounded to the closest integer (i.e. ceiled if the decimal part is at least 0.5, floored otherwise), will be the final mark of the course. The “cum laude” mention will be awarded if the rounded score is at least 31 and the student shows complete mastery of the subject. A mock exam, representing the format of the final written exam, is published on Blackboard.

Lecture notes made available on Blackboard.
A. Sbuelz-A. Tarelli, Quantitative finance: Problems and solutions, Giappichelli, 2021. Buy from VP
A. Battauz-F. Ortu-F. Rotondi, Arbitrage theory in discrete and continuous time, World Scientific, 2026.
K. Sydsaeter-P.J. Hammond, Mathematics for economic analysis, Prentice-Hall, 1995. Buy from VP

The course aims at introducing statistical techniques and models widely used in Finance in general, but with particular focus on option pricing. In the course different types of options will be introduced and, for each of these, the specific complexities that modelling such derivatives entail will be analysed.
A vast part of the course is dedicated to the introduction of stochastic processes which can be used to model underlying assets and consequently to the problem of calibration of such stochastic models from financial data using estimation methods such as maximum likelihood estimation and method of moments. Various tests of fitting to verify the goodness of fit of each stochastic process will be carried out.
The course will then provide an in depth overview of risk neutralization methods to pass from the statistical parameters to the risk-neutral ones and the application of Monte Carlo simulations to price options (both European and American).
The presentation of each topic will be accompanied by a demonstration on how to compute each problem through the use of the R/Python environment.
By the end of the course students are expected to be able to understand the complexities that evaluating different derivatives entail and to comprehend which model grants the most accurate results, based on the specific characteristics of the financial product that they have to evaluate. Students are also expected to be able to use R/Python to set the specific problems and to reach numerical results.
Main goal of the course: to give students a comprehensive knowledge of the main tools for economic time-series forecasting, tackling novel developments in the field as well. The course will cover both theoretical concepts and practical case studies.

• Random number generation and variance reduction techniques.
• Calibration and estimation of financial models from the data using method of moments and maximum likelihood estimation.
• The main stochastic processes used to model stock prices in finance, such as the Geometric Brownian motion and Lévy processes.
• Black and Scholes formula, implied volatility and volatility smile.
• The problems arising if we assume normality of returns.
• Girsanov theorem and the risk neutral transformation (Esscher transform and mean correcting martingale).
• Introduction to stochastic calculus.
• Monte Carlo methods with applications to (European and American) option pricing.
• Fast Fourier transform method with applications to European option pricing under different stochastic processes.
• Longstaff-Schwartz method with applications to American option pricing.
• Greeks letters for individual options and for a portfolio of options.
• Introduction to liquidity.
• Introduction to Multi-Asset options and the problem of structuring the dependence between the various underlying assets.
  The course is highly focused on the use of the R/Python environment.
  Lectures with computer labs and classes. The classes will be held by Professor Lorenzo Oltolini.
  Detailed programme
  Topic
  Description
  Time series basics
  Definition of a time series; Stationary and non-stationary time series; Univariate and multivariate time series; White noise; Level, Trend, Stagionality and erratic components of a time series; Forecasting and decomposition of time series.
  ARMA models
  Autoregressive (AR), Moving Average (MA) and ARMA representations of stationary time-series; Specification and estimation of ARMA models; Forecasting AR, MA and ARMA models.
  ARIMA and SARIMA models
  Integrated time series and ARIMA representation; Seasonal time series (SARMA and SARIMA representations). Forecasting.
  Unobserved Component Models
  Random walks and Random walks with drift; Building an unobserved component model in ETS form; Estimation, decomposition and forecasting.
  Nonparametric Forecasting: Conformal Prediction and Time Series
  Basics of Conformal Prediction, Conformal Prediction for Dependent Data, Applications to economic time series..
  Methods for financial time-series (hints)
  ARCH and GARCH models.
  Frontal lessons and practical sessions.

Written exam: it will consist of a series of questions requiring straight to the point type of answers with a limited number of rows to answer available.
Individual exam on the whole program, with a mix of theoretical questions and exercises.

Slides and laboratory handouts will be distributed during the course and I will refer to some textbooks. These are references that are supportive information but are not required to follow:

• Stefano M. Iacus (2008), Simulation and Inference for Stochastic Differential Equations with R Examples, Springer New York.
• Stefano M. Iacus (2011), Option Pricing and Estimation of Financial Models with R, Wiley & Sons, Chichester.
• Wim Schoutens (2021), Lévy Processes in Finance: Pricing Financial Derivatives, Wiley Series in Probability and Statistics.
• Steven Shreve, Stochastic Calculus for Finance (Parts 1 and 2), Springer Finance.
• John Hull, Options, Futures, and Other Derivatives, Global Edition, 11th edition.
  J.D. Cryer, K. Chan, “Time Series Analysis, With Applications in R”, Springer.
  Rob J. Hyndman, Anne B. Koehler, J. Keith Ord, Ralph D. Snyder “Forecasting with Exponential Smoothing: the State Space Approach”, Springer.
  Anastasios N. Angelopoulos, Rina Foygel Barber, Stephen Bates “Theoretical Foundations of Conformal Prediction”, Cambridge University Press

The course is designed to provide the students with actuarial and quantitative skills relevant for pricing and reserving of life insurance contract. For this purpose, the course starts from the analysis of traditional life insurance policies. A specific focus will be given to the actuarial life table and to survival models useful for describing mortality patterns.
Subsequently, the course deals with more advanced contracts available in the market. In particular, the actuarial and financial structure of both with-profit and linked policies will be analysed.
A special emphasis is given to loss and profit decomposition in order to emphasize main components of technical profit of a life insurance company. To this end, a specific focus will be given to the embedded value of an insurance company.
The course also gives an overview of the Solvency II framework, with specific focus on Best Estimate Liability and Solvency II Capital Requirement.
The course will mainly be taught through theoretical lectures with specific classes dedicated to exercises. Focus is on both theory and practice. At the end of the course, the students should be able to define rate premiums for life insurance contracts, to evaluate mathematical reserves, to analyze the results deriving from the sensitivity evaluation, to understand the effects on the different components of technical profit, to understand the assumption, the process and the methodology underlying the Best Estimate Liability and Life and Market SCR calculation.
Throughout the course a special focus will be placed on the analysis of practical applications and empirical data with respect to the topics studied.
During the course specific in-depth seminars could be held to promote a greater understanding of the topics covered.
Instructional objectives of the course
1. Basic concept of life insurance contracts
After having completed the study of the material, the student is expected to be capable of:

• having a knowledge of the actuarial structure of traditional life insurance contracts
• computing single, regular and natural premiums of traditional life insurance contracts
• computing pure mathematical reserves of traditional life insurance contracts
  2. Mortality Models
  After having completed the study of the material, the student is expected to be capable of:
• modelling residual lifetime random variable
• understanding the distinction between cohort and period life tables
• having a knowledge of the concepts of survival function and force of mortality
• having a basic knowledge of main methodologies for forecasting mortality rates
  Understanding of selected and projected mortality tables
  Unit and Index Linked Products
  After having completed the study of the material, the student is expected to be capable of:
• having a knowledge of the financial and actuarial structure underlying unit and index linked policies
• computing single and recurrent premiums of unit and index linked policies
• computing the mathematical reserve for survival and death benefits of a linked contract
• having a knowledge of the Brennan and Schwartz model
  Financial Option Pricing
  After having completed the study of the material, the student is expected to be capable of:
• having a knowledge of the derivative security types
• having a knowledge of the difference between a Risk-Neutral and a Real-World approaches
  5. Participating (with profit) Policies
  After having completed the study of the material, the student is expected to be capable of:
• having a knowledge of legal and regulatory framework defined for with-profit policies and segregated funds
• computing the revaluation rate and having a knowledge of different methods used for defining the participation rule
• computing pure mathematical reserves of participating life insurance contracts
  6. Actuarial Profit
  After having completed the study of the material, the student is expected to be capable of:
• having a knowledge of the concepts of first order and second order technical bases
• computing the expected present value of in and out cash-flows related to life insurance contracts
• splitting the technical profit into the main components
• performing a sensitivity analysis to identify the main drivers of technical profit for alternative life insurance contracts
  7. Valuation methods of a Life Insurance Company
  After having completed the study of the material, the student is expected to be capable of:
• having a knowledge of the concept of Market Consistent Embedded Value (MCEV)
• calculating the Technical Provisions (BEL & Risk Margin) for a life insurance portfolio
• having a knowledge of the SCR calculation for an Insurance Company using the Standard Formula

1. Basic concept of life insurance contracts
characteristics of basic life insurance contracts: technical bases, different types of traditional life insurance contracts
single and regular premiums of basic life insurance contracts
natural premiums and pure mathematical reserves of basic life insurance contracts
2. Mortality Models
random variable residual lifetime
cohort and period life table
survival function and force of mortality
forecasting mortality rates and projected/selected mortality tables
3. Unit and Index Linked policies
Main characteristics of linked policies
Financial and Actuarial Structure of unit and index linked policies
Mathematical reserves of linked policies
Brennan and Schwartz model
4. Financial Option Pricing
Derivative securities: forwards, futures, swap, option
Option most popular valuation methods
Risk-Neutral and Real-World approaches
5. Participating (with profit) Policies
Financial and actuarial structure of participating policies
Participation rules and revaluation rate
Mathematical reserves of participating policies
6. Actuarial Profit
First order and second order technical bases
Technical profit and loss and decomposition.
Mortality and financial profit
7. Valuation methods of a Life Insurance Company
Technical Provisions (BEL & Risk Margin)
Life and Market SCR calculation within the Standard Formula
Market Consistent Embedded Value (MCEV)

• Appraisal Value
• New Business Value
  The course is divided into a cycle of lessons carried out with the aid of slides and other support material. The course includes frontal lectures by the lecturers as well as tutoring hours for practical exercises.

The exam is based on both a written and an oral examination.
The written examination includes questions on the fundamental topics lasting usually 1 hour and 30 minutes and could be based on the excel software.
The written examination is based on both open-ended questions and exercises.
The compulsory oral exam can be taken only if the written exam has been passed (i.e. with a mark greater or equal than 18).
The final mark is the weighted average of grades of written and oral exam (respectively 40% and 60%)
In case the exam has been failed, both written and oral examination must be taken again.
The examination regards the entire course syllabus. The examination is aimed at assessing reasoning, analytical rigour with regard to course topics.

Given the particular structure of the course and the analysis of certain practical topics over a long term horizon, it is not possible to identify specific textbooks that cover all course topics.
Instructional material will be made available on the Blackboard platform throughout the course.
Series of readings and supplemental instructional materials will be made available on the course site of the Blackboard platform or in the references of the provided teaching material.

Aim of the course is to provide a knowledge about actuarial techniques for the evaluation of public pension-schemes and pension funds.
The following topics will be tackled: the structure of the Italian public and complementary pension systems, the development of regulations and main reforms of the public pension-scheme, the financial systems for managing the public pensions, the determination of premiums and actuarial reserves within the framework of an IVS system (disability, retirement and survivor), the methods for computing contributions and benefits for a defined benefit pension fund.
The course contemplates lectures as well as seminars involving experts so as to illustrate some of the issues linked to the management of the public pension and pension funds.
By the end of the course, students should be able to compute pension benefits and contribution levels for an IVS system and a defined benefit pension plan.

1. General information about pensions
In this section we deal with the following topics:
understand and know the concept of pensions;
know which risks are covered by public pensions schemes and which kind of benefits are provided;
understand Italy's three-pillar pension system.
2. The Italian private and public pension system
In this section we deal with the following topics:
understand the Italian pension system;
know the main reforms made to the Italian pension system in recent years;
be able to compare different financial management systems;
understand the impact of the different reforms and any individual initiative on the balance of a financial system.
understand current legislation about private pension funds;
compare Italian complementary pension system to European framework;
understand the financial management methods for pension funds;
3. Actuarial Models for public pensions (disability, retirement and survivor)
In this section we deal with the following topics:

• choose appropriate technical bases for the determination of the premium in an IVS (disability, retirement and survivor) system;
• calculate the estimated present value of the benefits and wages related to a group pension plan with specific characteristics;
• understand and calculate capitalisation coefficients;
• determine the contributions for a hypothetical IVS system for different financial management systems;
• determine the actuarial reserves of an IVS system for different financial management systems;
• evaluate the equilibrium of a financial system for a specific accounting year;
• evaluate the relationships between the capitalisation coefficients and the transformation coefficients introduced by the Dini reform.
  4. Finance for a DC complementary pension fund
  In this section we deal with the following topics:
• understand the financial scheme of a DC pension fund when a financial guarantee is embedded in: best of vs. cliquet guarantees;
• evaluate the financial guarantee as an European option: CRR model vs. Black-Scholes model;
• evaluate the fair value of the cost of the financial guarantees: the Brennan and Schwartz model for pension funds;
• understand the financial strategies for managing a pension fund: buy and hold strategies vs. constant proportion portfolio insurance strategies;
• understand and evaluate risk-adjusted performance measures for investments of a pension fund;
• insight to the Directive IORP II.
  Lectures

The exam is based on a written examination. The examination regards the entire course syllabus. The examination is aimed at assessing the knowledge, the reasoning, the analytical rigour with regard to course topics.

Given the particular structure of the course and the analysis of certain topics over a long term horizon, it is not possible to identify specific textbooks that cover all course topics.
Instructional material will be made available on the Blackboard platform throughout the course.
Reading materials for further study (optional)
A. Tomasetti et alii, Tecnica attuariale per collettività, Kappa, Rome, 1995, vol. I.
C. Mottura, Un’analisi della commissione di garanzia nei Fondi Pensione, Atti VII Congresso Nazionale degli Attuari, 2004.
M. De Felice-F. Moriconi, Definizione dei benchmark, Misurazione delle performance e Valutazione dei costi nei Fondi Pensione con minimo garantito, CONSOB – Quaderni di Finanza n. 36, 1999.
N. Savelli, Modelli attuariali per schemi pensionistici a prestazioni definite con capitalizzazione individuale, Kappa, Rome, 1984.
N. Bowers, H. Gerber, J. Hickman, D. Jones, C. Nesbitt, Actuarial mathematics, The Society of Actuaries, Schaumburg, Illinois, 1997.
Ph. Bertrand Ph., J.L. Prigen, Portfolio Insurance Strategies: OBPI versus CPPI, GEQAM et Université Montpellier 1, Preprint, 2002.

The course addresses the study of monetary policy from a strategic and operational perspective. Under the first profile, the student learns the macroeconomic and strategic context in which monetary policy operates, as well as its transmission channels to the economic system. Under the second profile, the student learns about the instruments and techniques of monetary policy management, with a focus on their evolution. The European institutional context will be particularly deepened, but the US system will also be covered. An in-depth study is devoted to 'unconventional' monetary policy measures and convergence towards the 'new normal'. Issues of monetary microeconomics are also addressed, in particular the problems of liquidity and credit risk in the banking sector in the presence of information asymmetries.
At the end of the course, the student will be able to answer theoretical questions and solve exercises related to: monetary policy strategy and operational framework, transmission channels, credit and liquidity risk. The student should also be able to answer questions related to the institutional set-up of central banks: organization, strategy, operational framework of the Eurosystem and the Federal Reserve System.

1. The macroeconomic framework of monetary policy:
a. the IS-AD-AS model
b. central bank reaction functions: inflation targeting and Taylor rule
c. zero lower bound (ZLB)
2. Monetary policy in an open economy
3. The strategic approach to monetary policy: rules, discretion, reputation
4. The European System of Central Banks: structure and tasks
5. The ECB's strategy until 2020 and the 2021 review
6. The operational framework of monetary policy:
a. ECB instruments and supply of bank reserves
b. The demand function of bank reserves
c. The money market model under three implementation frameworks: interest rate steering, quantitative easing, and new normal
7. The unconventional measures adopted in the euro area and the convergence towards the new normal; the 2024 review of the operational framework
8. The Federal Reserve System: organization, strategy, evolution over time
9. A view on other central banks: Bank of England and Bank of Japan
10. Monetary policy transmission channels: interest rate channel, banking channel, exchange rate channel
11. Central Bank Digital Currency (CBDC)
12. Monetary policy, climate-related risks and environmental sustainability (green monetary policy)
13. Liquidity risk and lender of last resort
14. Credit risk and rationing – the role of collateral
Lessons and exercises solved together with the teacher in classrooms.

Written examinations, testing the ability of students to solve simple exercises focusing on the models studied during the course. The written examinations can also include questions related to both the theoretical and the institutional topics addressed in the course.

Baglioni A.: Monetary policy implementation. Exploring the “new normal” in central banking, Palgrave – Springer 2024 (https://link.springer.com/book/10.1007/978-3-031-53885-8)
Additional reading material available in blackboard

Conoscenza e comprensione
Il corso si propone di formare gli studenti alle competenze orali e scritte di livello B1/B2 del Quadro Comune Europeo di Riferimento per le Lingue relativamente a due ambiti del FOS (Français sur Objectifs Spécifiques): la comunicazione professionale e le relazioni internazionali.
Capacita' di applicare conoscenza e comprensione
Alla fine del corso, lo studente sarà in grado di comprendere varie tipologie di testi informativi e argomentativi: saggi, discorsi e conferenze sui temi trattati, articoli di stampa e trasmissioni televisive sull’attualità internazionale.
Abilità comunicative
Alla fine del corso, lo studente potrà esprimersi oralmente in modo chiaro e dettagliato su alcuni temi relativi alla comunicazione professionale in ambito internazionale e alle relazioni internazionali e potrà esporre il suo punto di vista su un tema di attualità. Riguardo all’abilità di produzione scritta, lo studente saprà riassumere un testo informativo o argomentativo, riformulare e tradurre dal francese brevi testi tratti da articoli di stampa e da siti internet di informazione.

La comunicazione professionale in francese nei contesti internazionali. Il francese lingua delle relazioni internazionali.
Revisione e approfondimento dei seguenti argomenti di grammatica: le frasi subordinate; il discorso indiretto; la formazione e l’uso del congiuntivo; la formazione e l’uso di gerundio e participio presente; la forma passiva del verbo; i pronomi relativi; i pronomi personali, i pronomi “en” e “y”; gli aggettivi e pronomi indefiniti.
Studio del lessico specifico della comunicazione professionale: ricerca/offerta di un posto di lavoro; pianificazione delle attività; relazioni gerarchiche e organigramma; riunioni di lavoro; eventi e conferenze.
Attività di comprensione scritta e orale su documenti autentici: conferenze, discorsi, trasmissioni televisive di attualità.
Attività di produzione scritta di testi brevi: lettera di motivazione, CV, mail a contenuto professionale, riassunto, traduzione dal francese.
Attività di produzione orale: presentazione di una rassegna stampa; analisi e commento di testi argomentativi (tipologia e tecniche retoriche).
Lezioni in lingua francese incentrate sulla presentazione dei contenuti del corso. Attività di comprensione e produzione scritta e orale con supporti e fonti multimediali (audio/video). Le lezioni si svolgono in aula e in presenza. La frequenza è vivamente raccomandata a tutti gli studenti.

La prova scritta (50% del voto finale) é composta da diverse parti : 1. Test morfosintattico e lessicale ; 2. Traduzione dal francese all’italiano di un testo giornalistico; 3. Riassunto. L’uso del dizionario monolingue e / o bilingue è ammesso solo per le prove di traduzione e riassunto.
Criteri di valutazione delle prove di traduzione e riassunto. La valutazione della traduzione prenderà in considerazione i seguenti aspetti : linguistico (comprensione della lingua francese e correttezza della traduzione) ; testuale (adeguatezza rispetto al genere e al contesto) ; stilistico (stile dell’autore e registro linguistico) ; terminologico (conoscenza e uso adeguato dei termini specialisitici) ; referenziale (destinatario ed elementi extralinguistici). Nella valutazione del riassunto si verificheranno i seguenti aspetti : chiarezza e correttezza formale; sintesi delle informazioni e degli argomenti.
L’esame orale (50% del voto finale) è suddiviso in due parti : 1. Presentazione di una rassegna stampa preparata dallo studente (25% del voto finale) ; 2. Discussione con il professore su uno o più testi scritti /audio / video di tipo argomentativo affrontati durante il corso (25% del voto finale) .
Criteri di valutazione della prova orale : nelle due parti dell’esame orale saranno valutate la conoscenza avanzata della lingua francese, la qualità dell’argomentazione, la gestione del tempo, la conoscenza dei testi e dei contesti culturali di produzione. In particolare, nella presentazione della rassegna stampa saranno valutati i seguenti punti: capacità di riferirsi ai testi scelti e di metterli in relazione tra loro, pertinenza delle risposte a domande formulate dal docente, approfondimento della riflessione sulla tematica scelta ; nella discussione sui testi argomentativi sarà valutata la presentazione dell’organizzazione argomentativa del testo (strutturazione in parti, distribuzione e tipologia degli argomenti, scelte sintattiche e lessicali).

Testi obbligatori:
M. Soignet, Le français des relations européennes et internationales B1 / B2 Objectif Diplomatie 2, Hachette Français Langue Etrangère, Paris, 2011 Acquista da VP
Una lista di ulteriori testi scritti / audio / video e di riferimenti bibliografici sarà illustrata dalla docente durante il corso e pubblicata nella pagina Blackboard del corso.
Testi consigliati:
Dizionario monolingue:
Le Petit Robert 2027 (ou éditions précédentes), Editions Le Robert, Paris.
Le Robert Maxi de la langue française, Editions Le Robert, Paris.
Dizionario bilingue:
R. Boch, Il Boch minore, Dizionario Francese-Italiano Italiano-Francese (Settima edizione o edizioni precedenti recenti), Zanichelli, Bologna.
Libro di grammatica:

• per studenti di madrelingua italiana :
  F. Bidaud, Grammaire du français pour italophones (versione cartacea o digitale), 4e édition, UTET, Torino, 2020. Acquista da VP
  F. Bidaud, Exercices de grammaire du français pour italophones (versione cartacea o digitale), 4e édition, UTET, Torino, 2021. Acquista da VP
  C. Mirabelli, Grammatica attiva della lingua francese. Fonetica - Morfologia - Sintassi - Esercizi + cd-audio, Hoepli, Milano, 2017. Acquista da VP
• per studenti di madrelingua non italiana:
  A. Akyuz, B. Bazelle-Shahmaei, J. Bonenfant, M.F. Orne-Gliemann, Grammaire du français B1/B2, collection Focus, Hachette FLE, Vanves, 2022. Acquista da VP

Il corso intende sviluppare e approfondire le competenze linguistico-comunicative a livello generale, per quanto riguarda le strategie di comunicazione interculturale, e a livello specifico nell’ambito sociopolitico ed economico. Obiettivo è il consolidamento di una competenza linguistica di livello B1/B2 del Quadro di Riferimento Europeo, con particolare attenzione alla trattazione di argomenti di attualità.
Conoscenza e comprensione
Al termine del corso, lo studente avrà acquisito una più approfondita conoscenza della lingua tedesca e del mondo germanofono e una migliore comprensione della cultura tedesca, della sua storia ed evoluzione, oltre che del ruolo del tedesco nel panorama linguistico europeo.
Capacità di applicare conoscenza e comprensione
Al termine del corso, lo studente avrà migliorato la sua capacità di interazione orale grazie alla preparazione e presentazione di argomenti selezionati (discussione, presentazione di progetti ecc.), e avrà perfezionato la competenza di comprensione e produzione di testi scritti, accompagnata da un ampliamento del lessico.

Attraverso lo studio approfondito delle strutture linguistiche, il corso intende introdurre alla cultura della Germania e dei paesi germanofoni, con particolare attenzione ai temi di attualità. Saranno trattati in particolare i seguenti argomenti:

• Cenni di storia della lingua tedesca;
• il ruolo del tedesco in Europa e le sue varianti nazionali (DACH);
• elementi di Landeskunde (cultura, tradizione e geografia);
• i moderni strumenti di comunicazione e di informazione;
• situazioni quotidiane (salute, natura, lavoro);
• cenni di storia e politica della Germania.
  Lezioni (in lingua tedesca) incentrate sulla trasmissione di contenuti e sull’interazione tra i partecipanti, in cui verrà dato ampio spazio alle discussioni. Le lezioni saranno tenute nel I semestre dal prof. Vincenzo Damiazzi, nel II semestre dalla prof.ssa Laura Balbiani. I materiali saranno messi a disposizione sulla piattaforma Blackboard.

La frequenza delle lezioni è vivamente consigliata, come per tutti i corsi di lingua.
L’esame finale consiste in una prova scritta e in una prova orale, incentrate sugli argomenti trattati durante il corso.
La parte scritta prevede la verifica delle competenze morfo-sintattiche e grammaticali mediante la scrittura di un testo ed esercizi di accertamento grammaticale; durante il colloquio sarà verificata la competenza comunicativa su temi trattati a lezione e su un argomento a scelta dello studente.

A lezione verrà utilizzato regolarmente il seguente testo:
AA.VV., Panorama Deutsch als Fremdsprache. B1. Berlin: Cornelsen 2017.
ISBN Kursbuch: 978-3-06-120523-2
ISBN Übungsbuch:978-3-06-120479-2
Informazioni attuali sulla Germania sono reperibili in:
AA.VV., Tatsachen über Deutschland, http://www.tatsachen-ueber-deutschland.de/de/inhaltsseiten-home/zahlen-fakten.html
Grammatica consigliata:
Monika Reimann, Grammatica di base della lingua tedesca. München: Hueber 1999.
Dizionario consigliato:
Luisa Giacoma / Susanne Kolb, Il nuovo dizionario di tedesco. Quarta edizione. Bologna: Zanichelli/Klett 2019.
Ulteriore bibliografia verrà indicata durante il corso.

Il corso si propone di formare gli studenti alle competenze orali e scritte di livello B1/B1 del Quadro Comune Europeo di Riferimento per le Lingue ; inoltre, intende fornire le competenze linguistiche e culturali adeguate per la gestione delle strategie di comunicazione in contesti professionali internazionali.
Alla fine del corso, lo studente sarà in grado di comprendere varie tipologie di testi informativi e argomentativi : saggi, discorsi e conferenze sui temi trattati, articoli di stampa e trasmissioni televisive sull’attualità internazionale.
Alla fine del corso, lo studente potrà esprimersi oralmente in modo chiaro e dettagliato su alcuni temi relativi alla comunicazione professionale in ambito internazionale e alle relazioni internazionali e potrà esporre il suo punto di vista su un tema di attualità. Riguardo all’abilità di produzione scritta, lo studente saprà riassumere un testo informativo o argomentativo, riformulare e tradurre dal francese brevi testi tratti da articoli di stampa e da siti internet di informazione.

La comunicazione professionale in francese nei contesti internazionali. Il francese lingua delle relazioni internazionali.
Revisione e approfondimento dei seguenti argomenti di grammatica : le frasi subordinate; il discorso indiretto ; la formazione e l’uso del congiuntivo ; la formazione e l’uso di gerundio e participio presente; la forma passiva del verbo; i pronomi relativi; i pronomi personali, i pronomi “en” e “y” ; gli aggettivi e pronomi indefiniti.
Studio del lessico specifico della comunicazione professionale: ricerca/offerta di un posto di lavoro ; pianificazione delle attività; relazioni gerarchiche e organigramma; riunioni di lavoro ; eventi e conferenze.
Attività di comprensione scritta e orale su documenti autentici : conferenze, discorsi, trasmissioni televisive di attualità.
Attività di produzione scritta di testi brevi: lettera di motivazione, CV, mail a contenuto professionale, riassunto, traduzione dal francese.
Attività di produzione orale: presentazione di una rassegna stampa ; analisi e commento di testi argomentativi (tipologia e tecniche retoriche).
Lezioni in lingua francese incentrate sulla presentazione dei contenuti del corso. Attività di comprensione e produzione scritta e orale con supporti e fonti multimediali (audio/video). Le lezioni si svolgono in aula e in presenza. La frequenza è vivamente raccomandata a tutti gli studenti.

La prova scritta (50% del voto finale) é composta da diverse parti : 1. Test morfosintattico e lessicale ; 2. Traduzione dal francese all’italiano di un testo giornalistico ; 3. Riassunto. L’uso del dizionario monolingue e / o bilingue è ammesso solo per le prove di traduzione e riassunto.
Criteri di valutazione delle prove di traduzione e riassunto. La valutazione della traduzione prenderà in considerazione i seguenti aspetti : linguistico (comprensione della lingua francese e correttezza della traduzione) ; testuale (adeguatezza rispetto al genere e al contesto) ; stilistico (stile dell’autore e registro linguistico) ; terminologico (conoscenza e uso adeguato dei termini specialisitici) ; referenziale (destinatario ed elementi extralinguistici). Nella valutazione del riassunto si verificheranno i seguenti aspetti : chiarezza e correttezza formale; sintesi delle informazioni e degli argomenti.
L’esame orale (50% del voto finale) è suddiviso in due parti : 1. Presentazione di una rassegna stampa preparata dallo studente (25% del voto finale) ; 2. Discussione con il professore su uno o più testi scritti /audio / video di tipo argomentativo affrontati durante il corso (25% del voto finale) .
Criteri di valutazione della prova orale : nelle due parti dell’esame orale saranno valutate la conoscenza avanzata della lingua francese, la qualità dell’argomentazione, la gestione del tempo, la conoscenza dei testi e dei contesti culturali di produzione. In particolare, nella presentazione della rassegna stampa saranno valutati i seguenti punti: capacità di riferirsi ai testi scelti e di metterli in relazione tra loro, pertinenza delle risposte a domande formulate dal docente, approfondimento della riflessione sulla tematica scelta ; nella discussione sui testi argomentativi sarà valutata la presentazione dell’organizzazione argomentativa del testo (strutturazione in parti, distribuzione e tipologia degli argomenti, scelte sintattiche e lessicali).

Testi obbligatori :
M. Soignet, Le français des relations européennes et internationales B1 / B2 Objectif Diplomatie 2, Hachette Français Langue Etrangère, Paris, 2011 Acquista da VP
Una lista di ulteriori testi scritti / audio / video e di riferimenti bibliografici sarà illustrata dalla docente durante il corso e pubblicata nella pagina Blackboard del corso.
Dizionario monolingue consigliato :
Le Petit Robert 2026 (ou éditions précédentes), Editions Le Robert, Paris.
Le Robert Maxi de la langue française, Editions Le Robert, Paris.
Dizionario bilingue consigliato :
R. Boch, Il Boch minore, Dizionario Francese-Italiano Italiano-Francese (Settima edizione o edizioni precedenti recenti), Zanichelli, Bologna.
Testi consigliati :
Per studenti di madrelingua italiana :
F. Bidaud, Grammaire du français pour italophones (versione cartacea o digitale), 4e édition, UTET, Torino, 2020. Acquista da VP
F. Bidaud, Exercices de grammaire du français pour italophones (versione cartacea o digitale), 4e édition, UTET, Torino, 2021. Acquista da VP
C.Mirabelli, Grammatica attiva della lingua francese. Fonetica - Morfologia - Sintassi - Esercizi + cd-audio, Hoepli, Milano, 2017.
Per studenti di madrelingua non italiana :
A. Akyuz, B. Bazelle-Shahmaei, J. Bonenfant, M.F. Orne-Gliemann, Grammaire du français B1/B2, collection Focus, Hachette FLE, Vanves, 2022. Acquista da VP

The course aims to introduce students to:
the study of insurance law and regulation
the international and European dimension of this discipline
At the end of the course students will know the dynamics and the discipline concerning the relations between insurance companies, insurance intermediaries, supervisory authorities, customers/policyholders.

The course programme is structured as follows:
Italian law to be studied
Civil Code (articles 1882-1932). These rules essentially govern the insurance (and reinsurance) contract
Foreign students can, alternatively, study the Principles of European Insurance Contract law (PEICL) which can be found at the following link https://www.uibk.ac.at/zivilrecht/forschung/evip/restatement/sprachfassungen/peicl-en.pdf
Private Insurance Code
IVASS Regulations no. 45/2020, 41/2018, 40/2018, 38/2018, 10/2018
Letters to the IVASS market dated 28 March 2024 and 5 July 2018
European law to be considered
Directive 2009/138 of 25 November 2009 (Solvency II) as amended by the Directive 2025/2
Title I (articles 1-177)
Title II (articles 178-211)
Title III (articles 211-217 and 247-264)
Title IV (articles 267 – 296)
Directive 2016/97 of 20 January 2016 (IDD)
Commission Delegated Regulation (EU) 2017/2358 of 21 September 2017
Commission Delegated Regulation (EU) 2017/2359 of 21 September 2017
Regulation (EU) 1286/2014 of 26 November 2014
Directive 2025/1 (IRRD)
The course includes classroom lessons for theoretical in-depth study, discussions on specific topics, and interventions by experts.

An oral exam consisting of an interview on the course programme.
The oral interview aims to ascertain the student's ability to navigate the themes and issues included in the course programme, including those covered in the experts’ testimonies during lectures.

I Module (Prof. Nino Savelli) TBC
II Module (Prof. Diego Zappa)
In the Insurance Statistics module, by using the standard frequency-severity approach, we will use the Poisson and Gamma GLM models to compute the net premiums on the basis of appropriate customers’ profile. Results will be compared with techniques based upon Generalized additive models and machine/statistical learning algorithms. Hints will be given in case of deviation from standard assumptions as well as extensions to include artificial intelligence tools.
On successful completion of the module participants are expected to possess:
knowledge of concepts, terms and methods of the most used statistical model techniques to fit frequency and severity components and grasp of their strengths and weaknesses (DD1- Knowledge and understanding);
ability to correctly apply statistical methods to real insurance problems (DD2- Applying knowledge and understanding);
quantitative thinking addressed to make independent judgements, driven by application of statistical learning methods (DD3- Making judgements);
ability to present statistical learning arguments and the conclusions from them, by means of the extraction of qualitative information from quantitative data, accuracy and in forms that are suitable for the audiences being addressed, both orally and in writing (DD4-Communication);
At the end of this module students will learn how to handle linear/not linear components to estimate risk components.

Module I: Risk Theory (Prof. Nino Savelli)
Module II: Insurance statistics (Prof. Diego Zappa)
Remind of linear models, Generalized linear models, Generalized additive models, Classification Trees, Ensemble methods, Neural networks with a special emphasis on their application to insurance datasets. Most of lectures will be provided in the computer lab using Python codes.
On successful completion of the course participants are expected to learn:

• The use of non-linear models and general linear models (GLM) for insurance pricing.
• The use of Neural Network modelling for non linear insurance pricing.
• At least a basic knowledge of machine/statistical learning methods for insurance.
• (Special topic) Stochastic reserving using GLMs.
  Module I:
  Module II: lectures will benefit of codes written in the Python language and applications by using ad hoc software.

For Module I:
For Module II: for those attending regularly the lectures, the exam will consist of questions on theory and the completion of a case study to be solved in the PC lab.
The final mark will be the weighted average of tha marks in the 2 modules: I module=6cfu, II module=5cfu. If the final score does not correspont to an integer, the mark will be rounded up to the nearest larger integer.

Module I
Module II
Notes available at the corresponding Blackoard course webpage.
Elective readings:
P. De Jong-G.Z. Heller, Generalized Linear Models for Insurance Data, Cambridge University Press, 2008.
Y. Tse, Nonlife actuarial models: theory, methods and evaluation, Cambridge University Press, 2009.
Wuthrich, Mario V. et Al., AI Tools for Actuaries (May 09, 2025). Available at SSRN: https://ssrn.com/abstract=5162304

Il corso ha come obiettivo il consolidamento e l’arricchimento di conoscenze a livello fonetico, morfosintattico e lessicale, finalizzate allo sviluppo dell’abilità di interazione, comprensione e produzione orale e scritta dell’italiano usato nella vita quotidiana, nel contesto accademico e nella formazione professionale. Le competenze previste si collocano a un livello B1/B2 secondo quanto indicato dal Quadro Comune Europeo di Riferimento per le lingue (QCER).
Particolare attenzione è data anche alla presentazione di aspetti della società e della cultura italiana, ponendo le basi per un confronto interculturale.
Pertanto, lo studente dovrà essere in grado di:
comprendere testi in lingua standard su argomenti inerenti allo studio, al mondo del lavoro e del tempo libero;
comprendere ed utilizzare le principali strutture morfosintattiche della lingua italiana;
produrre testi coesi e coerenti su argomenti di interesse personale, esponendo ragioni e fornendo spiegazioni su opinioni e progetti;
interagire in contesti comunicativi inerenti alla vita quotidiana, accademica e professionale;
esprimersi con pronuncia chiara e comprensibile;
comprendere ed utilizzare le principali strutture morfosintattiche della lingua italiana;
riflettere a livello metalinguistico sulle strutture grammaticali e morfosintattiche.
The course aims to consolidate and enrich knowledge at the phonetic, morphosyntactic and lexical levels, aimed at developing the skills of interaction, comprehension and oral and written production of Italian used in everyday life, in the academic context and in professional training. The expected skills are at a B1/B2 level according to the Common European Framework of Reference for Languages (CEFR).
Particular attention is also given to the presentation of aspects of Italian society and culture, laying the groundwork for cross-cultural comparison.
Therefore, the student should be able to:
understand texts in standard language on topics related to study, work and leisure;
understand and use the main morphosyntactic structures of the Italian language;
produce cohesive and coherent texts on topics of personal interest, stating reasons, giving explanations and expressing opinions and plans;
interact in communicative contexts inherent in daily, academic and professional life;
express themselves with clear and understandable pronunciation;
understand and use the main morphosyntactic structures of the Italian language;
reflect at the metalinguistic level on grammatical and morphosyntactic structures.

Attraverso un approccio orientato all’azione, all’interazione e alla collaborazione tra studenti si propongono attività mirate alla comprensione, all’analisi e alla produzione di differenti generi comunicativi in contesti quotidiani e correlati al mondo dello studio e del lavoro, scoprendo e attivando strategie per l’apprendimento autonomo della lingua.
Il corso è organizzato in 30 ore di lezioni interattive in aula, che si svolgono durante il secondo semestre, e prevede i seguenti contenuti:
approfondimenti sulla discriminazione e produzione dei fonemi e delle strutture ritmico-intonative della lingua italiana;
lessico di base e settoriale;
approfondimenti di tipo morfologico e sintattico;
attività di comprensione, interazione e produzione orale e scritta relativamente a contesti di vita quotidiana, accademica e professionale.
La didattica si sviluppa richiedendo la partecipazione attiva degli studenti con lavori individuali, a coppie e/o in gruppi e lo studio autonomo monitorato sulla piattaforma di apprendimento del corso. Tutti dettagli saranno forniti dai docenti in aula.
Si consiglia l’utilizzo della Grammatica pratica della lingua italiana, di Susanna Nocchi, Alma edizioni.
Through an approach oriented to action, interaction and collaboration, students will be engaged in activities aimed at comprehension, analysis and production of different communicative genres in everyday and work-related contexts, in order to discover and activate strategies for autonomous language learning.
The 30-hours course is organized into interactive classroom lectures, which take place during the second semester, and includes the following content:
insights into the discrimination and production of the phonemes and the rhythmic-intonative structures of the Italian language;
basic and specialised vocabulary;
morphological and syntactic insights;
oral and written comprehension, interaction and production activities related to everyday, academic and professional life contexts.
The teaching methodology requires active student participation through individual work, pair work, and/or group work as well as monitored independent study on the course learning platform. All details will be provided by the instructors in class.
The use of Grammatica pratica della lingua italiana, by Susanna Nocchi (Alma edizioni) is recommended.

L’esame è composto da:
una prova scritta a computer che consiste in: un esercizio di comprensione orale; esercizi di comprensione di testi scritti (risposte a scelta multipla e vero/falso); test di grammatica (cloze); test di comprensione delle funzioni e strutture comunicative.
una prova orale che consiste in: una presentazione di sé, una presentazione su una tematica scelta dallo studente e legata al Corso di Studio (4 minuti), una breve interazione con la docente sulle tematiche affrontate nel corso di lingua italiana (3 minuti). Criteri di valutazione:
efficacia espositiva e comunicativa
accuratezza morfosintattica
padronanza del lessico
Si è ammessi alla prova orale solo dopo aver superato la prova scritta. Una volta superata la prova scritta, è indispensabile concludere l’esame con la prova orale nel medesimo appello.
La valutazione finale dell’esame è un voto in trentesimi.
The exam consists of:
a written test on computer comprising: a listening comprehension exercise; reading comprehension exercises (multiple-choice and true/false); grammar test (cloze); and a test of communicative functions and structures;
an oral test comprising: a self-presentation, a presentation on a topic chosen by the student and addressed in the Degree Programme (4 minutes), a short conversation with the lecturer on topics covered in the Italian language course (3 minutes).
Assessment criteria are as follows:
effectiveness in presentation and interaction
grammatical accuracy
lexical mastery
Students are admitted to the oral test only after passing the written test. After passing the written test, students must take the oral test within the same appello.
The final mark is graded on a scale of thirty points.