Advances in Risk Analysis with Big Data

Abstract

With cloud computing, Internet-of-things, wireless sensors, social media, fast storage and retrieval, etc., organizations and enterprises have access to unprecedented amounts and varieties of data. Current risk analysis methodology and applications are experiencing related advances and breakthroughs. For example, highway operations data are readily available, and making use of them reduces risks of traffic crashes and travel delays. Massive data of financial and enterprise systems support decision making under risk by individuals, industries, regulators, etc. In this introductory article, we first discuss the meaning of big data for risk analysis. We then examine recent advances in risk analysis with big data in several topic areas. For each area, we identify and introduce the relevant articles that are featured in the special issue. We conclude with a discussion on future research opportunities.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 111 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.