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Quantum support vector regression for disability insurance

Djehiche, Boualem; Löfdahl, Björn - In: Risks : open access journal 9 (2021) 12, pp. 1-9

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The modeling of logistic disability inception probabilities is formulated as a support vector regression problem. Using a quantum feature map, the data are mapped to quantum...

Persistent link: https://www.econbiz.de/10012745406

An analysis of bank financial strength ratings and credit rating data

Ruddy, John A. - In: Risks : open access journal 9 (2021) 9, pp. 1-16

In this study, data from two credit rating agencies are analyzed to consider how different Bank Financial Strength Ratings and Credit Ratings from two rating agencies compare. To my knowledge, prior research has not analyzed Bank Financial Strength Ratings from different rating agencies, nor has...

Persistent link: https://www.econbiz.de/10012612481

Improving explainability of major risk factors in artificial neural networks for auto insurance rate regulation

Xie, Shengkun - In: Risks : open access journal 9 (2021) 7, pp. 1-21

In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing. However, due to the complexity of model specification and its implementation, model...

Persistent link: https://www.econbiz.de/10012598958

Mathematical model for choosing counterparty when assessing information security risks

Koltays, Andrey; Konev, Anton; Shelupanov, Alexander - In: Risks : open access journal 9 (2021) 7, pp. 1-13

The need to assess the risks of the trustworthiness of counterparties is increasing every year. The identification of increasing cases of unfair behavior among counterparties only confirms the relevance of this topic. The existing work in the field of information and economic security does not...

Persistent link: https://www.econbiz.de/10012599598

Machine learning approaches for auto insurance big data

Hanafy, Mohamed; Ming, Ruixing - In: Risks : open access journal 9 (2021) 2/42, pp. 1-23

The growing trend in the number and severity of auto insurance claims creates a needfor new methods to efficiently handle these claims. Machine learning (ML) is one of the methodsthat solves this problem. As car insurers aim to improve their customer service, these companieshave started adopting...

Persistent link: https://www.econbiz.de/10012483213

Loss reserving models : granular and machine learning forms

Taylor, Greg - In: Risks : open access journal 7 (2019) 3/82, pp. 1-18

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

Machine learning for multiple yield curve markets : fast calibration in the Gaussian affine framework

Gümbel, Sandrine; Schmidt, Thorsten - In: Risks : open access journal 8 (2020) 2/50, pp. 1-18

Calibration is a highly challenging task, in particular in multiple yield curve markets. This paper is a first attempt to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian process regression, a machine learning methodology having many...

Persistent link: https://www.econbiz.de/10012292851

Bankruptcy prediction and stress quantification using support vector machine : evidence from Indian banks

Shrivastava, Santosh Kumar; Ramudu, P. Janaki - In: Risks : open access journal 8 (2020) 2/52, pp. 1-22

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 available indicates that research is currently limited on banks' stress …

Persistent link: https://www.econbiz.de/10012292870

Address identification using telematics : an algorithm to identify dwell locations

Grumiau, Christopher; Mostoufi, Mina; Pavlioglou, Solon; … - In: Risks : open access journal 8 (2020) 3/92, pp. 1-12

In this work, a method is proposed for exploiting the predictive power of a geo-tagged dataset as a means of identification of user-relevant points of interest (POI). The proposed methodology is subsequently applied in an insurance context for the automatic identification of a driver's residence...

Persistent link: https://www.econbiz.de/10012293288

Machine learning in banking risk management : a literature review

Leo, Martin; Sharma, Suneel; Maddulety, K. - In: Risks : open access journal 7 (2019) 1/29, pp. 1-22

and many more being explored. Since the global financial crisis, risk management in banks has gained more prominence, and …

Persistent link: https://www.econbiz.de/10012015887

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