Showing 1 - 9 of 9
The purpose of this paper is to survey recent developments in granular models and machine learning models for loss reserving, and to compare the two families with a view to assessment of their potential for future development. This is best understood against the context of the evolution of these...
Persistent link: https://www.econbiz.de/10012127545
Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...
Persistent link: https://www.econbiz.de/10012292870
Estimation of future mortality rates still plays a central role among life insurers in pricing their products and managing longevity risk. In the literature on mortality modeling, a wide number of stochastic models have been proposed, most of them forecasting future mortality rates by...
Persistent link: https://www.econbiz.de/10012015932
data across lines of business, and show that they improve on the predictive accuracy of existing stochastic methods. The …
Persistent link: https://www.econbiz.de/10012126426
In micro-lending markets, lack of recorded credit history is a significant impediment to assessing individual borrowers' creditworthiness and therefore deciding fair interest rates. This research compares various machine learning algorithms on real micro-lending data to test their efficacy at...
Persistent link: https://www.econbiz.de/10012508509
While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine...
Persistent link: https://www.econbiz.de/10013363030
This paper proposes a generalized deep learning approach for predicting claims developments for non-life insurance reserving. The generalized approach offers more flexibility and accuracy in solving actuarial reserving problems. It predicts claims outstanding weighted by exposure instead of loss...
Persistent link: https://www.econbiz.de/10014480914
Given the computational challenges associated with valuing large variable annuity (VA) portfolios, a variety of data mining frameworks, including metamodeling and active learning, have been proposed in recent years. Active learning, a promising alternative to metamodeling, enhances the...
Persistent link: https://www.econbiz.de/10014636846
Persistent link: https://www.econbiz.de/10012204355