Vida Maver joined EconLab Consulting team in 2019. Her work for EconLab includes development of stress testing models and other credit risk models among other provided consulting services. She has been involved in construction of macroeconomic scenarios for ICAAP stress testing, support in development and upgrade of various stress test-related models and IFRS9 impairment calculation. She holds an undergraduate degree in Financial mathematics from Faculty of Mathematics and Physics and is currently finishing the Quantitative finance and actuarial sciences master’s programme at School of Economics and Business. In both of her studies she has been a consistent top achiever. Before joining EconLab, she worked in the banking, insurance and consulting industries in the fields of risk and finance. Her previous expertise includes working in a central bank, where her main focus was on econometric modelling. Prior to that, she worked for the Slovenian multinational insurance company where her main focus was Brownian motion based stochastic process modelling and multivariate process modelling. Besides being an experienced user of R and Python, her competences include Matlab, Stata, Mathematica, and SageMath.


Selected references

Development of stress testing models (EBA; credit risk stress testing methodology).

PD and LGD modelling (BACE-ARDL modelling). Support in development and upgrade of various stress test-related models and tools.  Forecasting and back-casting of key stress testing parameters.

IFRS9 impairment calculation (including ECL, lifetime loss rates and P&L calculation). ECL benchmarking. LRA modelling. Econometric analysis of macroeconomic drivers of DR’s using ECB STAMP€ methodology and BMA.

Stage transition methodology (top-down construction of IFRS9 stage transition rates, as well as calculation of stage transition probabilities). Development of models to incorporate sector concentration into systemic PD model.  Construction of macroeconomic scenarios for ICAAP stress testing.

CVAR modelling. AR-GARCH modelling.

Stochastic process modelling (ABM, GBM, jump diffusion models). Modelling based on copulas. Multivariate process modelling.