Global Risk Institute is a preeminent source of ideas on the management of emerging risks and trends for financial services organizations
27 November 2019 | Risk Management Practices
Even the most casual observer will notice that newspaper headlines continue to be fueled by a steady stream of corporate scandals, malfeasance, and other assorted conduct and risk management “missteps”. A commonly recurring theme in much of the ensuing narrative and analysis is that these events are often directly attributable to some form of material “failure of (risk) culture”. In this paper, we explore a working definition of a “strong risk culture” as a guide to identify key management practices and conditions that can often play a critical role in shaping an organization’s risk culture.
13 November 2019 | Climate Risk and Sustainable Finance
In our latest publication, we review the current practices that financial institutions are employing, globally, to comply with the recommendations developed by the Task Force on Climate-related Financial Disclosure (TCFD). We call for continued actions by the financial sector, governments, and standard-setting organizations and highlight six key areas of improvement to accelerate climate action and reporting.
13 November 2019 | Climate Risk and Sustainable Finance
We develop a top-down strategic pathway towards green investing and show that eco-investing should not be a puzzle or a sacrifice if investors consider the unknown impact of climate change on different asset classes.
13 November 2019 | Climate Risk and Sustainable Finance
Robert Engle, statistician, winner of the 2003 Nobel Memorial Prize in Economic Sciences, and his team of researchers, undertook a project, in collaboration with GRI, to use the tools of modern finance and risk management to measure and model environmental risk. They have contributed significantly to the bourgeoning literature that studies how climate change affects asset markets and, in turn, how asset markets may affect the dynamics of climate change.
13 November 2019 | Climate Risk and Sustainable Finance
Assessing the hazard and exposure of dams in the U.S. This report provides visibility as to the types of risks that could emerge and is an important read for investors, asset managers and insurance providers analyzing portfolio level risk.
3 October 2019 | Cyber security and Fraud
The 'quantum race' is on and the race course and timeline are partially unknown. The creation of a scalable, fault-tolerant quantum computer that poses a significant risk to cyber security may be closer than we think. Although quantum attacks are not here yet, critical decisions need to be made today in order to respond to these threats in the future.
3 October 2019 | Cyber security and Fraud
The Distribution Analysis for Information Risk (DAIR) is a cyber quantification methodology that maps cyber events with a hierarchical risk taxonomy to evaluate operational, business & systemic risk economic capital. DAIR will help organizations quantify cyber risk in a consistent and meaningful way, giving consideration to asset vulnerabilities as well as business and systemic considerations.
21 August 2019 | Climate Risk and Sustainable Finance
The overall goal of this study is to develop a framework for rapidly assessing the hazard (i.e. the probability and magnitude of a dam failure) and the exposure (what gets affected by a failure), scalable over many regions for a preliminary ranking of the priority areas of concern. The intended application is for a portfolio level risk analysis by investors, asset managers, and insurance providers.
21 August 2019 | Cyber security and Fraud
Recent headlines about cyber-attacks and massive data breaches are revealing the fragility of the digital infrastructure and the impossibility of assuring the integrity of computer systems, even for organizations such as financial institutions that maintain the most mature cyber security programs.
21 August 2019 | Technology Innovations
A recent surge of interest in Machine Learning (ML) tools within the financial services industry has exposed many challenges of ML applications in financial modelling
