Traditional #statistical and #algorithm-based methods used to analyze #bigdata often overlook small but significant evidence. #bayesian #statistics, driven by #conditional #probability, offer a solution to this challenge. The review identifies two main applications of Bayesian statistics in #finance: prediction in financial markets and credit risk models. The findings aim to provide valuable insights for researchers aiming to incorporate Bayesian methods and address the sample size issue effectively in #financial #research.
This study examines the use of #artificialintelligence (#ai) and #bigdata data analytics by #insurers in #belgium for segmentation purposes to determine #claims#probability for prospective policyholders. The implementation of AI and big data analytics can benefit insurers by increasing the accuracy of #riskassessment. However, pervasive segmentation can have negative implications and potentially harm policyholders if their risk is incorrectly calculated. Existing restrictions in #insurance#regulations fall short of protecting policyholders from inaccuracies in risk assessments, potentially resulting in incorrect #premiums or conditions.
"By employing Big Data and Artificial Intelligence (AI), personal data that is categorized as sensitive data according to the GDPR Art. 9 can often be extracted. Art. 9(1) GDPR initially forbids this kind of processing. Almost no industrial control system functions without AI, even when considering the broad definition of the EU AI Regulation (EU AI Regulation-E)."
"We argue that datafication of insurer processes may fuel excessive data collection in the context of insurance contracts, generating a substantial risk of harm to consumers, especially in terms of discrimination, exclusion, and unaffordability of insurance. "
"There is currently limited information on and a lack of a unified approach to AI and ESG, and a need for tools for systematically assessing and disclosing the ESG related impacts of AI and data capabilities. I here propose the AI ESG protocol, which is a flexible high-level tool for evaluating and disclosing such impacts..."
"Insurers are faced with a lack of consumer trust in whether premiums are established in an objective and fair manner and that claims are adequately dealt with and paid without delay. In trying to balance between consumers interests and business interests there is a risk that insurers will go too far using personal data and increasingly automated decision-making crossing the line between what is still legal and ethical."