Arsene Lui is a Senior Quantitative Analyst in the Analytic Development Group, based in London.Full Bio
Arsene Lui is a Senior Quantitative Analyst in the Analytic Development Group, based in London. Arsene focuses on quantitative research and analytical development of various credit risk models, which are used by financial institutions and other credit-sensitive entities to manage their credit exposures.
Arsene is one the key developers of S&P Global Market Intelligence Credit Analytics Platform, which covers a set of cutting-edge models for the credit risk assessment of rated and unrated, public and private companies across the globe. Arsene is the major developer of CreditModel™, PD Model Fundamentals, PD Model Market Signals, PaySense, and Climate RiskGauge.
Arsene regularly speaks at internal and external organized webinars and writes thought leadership articles on topics including credit trends, default study, trade credit, and climate risk.
Arsene joined S&P Global Market Intelligence in 2018 in London, UK. Arsene holds a BSc in Quantitative Finance from The Chinese University of Hong Kong and a MSc in Scientific Computing from Ruprecht Karl University of Heidelberg. Arsene is a CFA Charterholder and a Certified FRM.
Delayed Policy Rate Cuts: A potential credit risk ripple effect for Europea
There is a consensus among economists that central banks’ policy rates have achieved their goal to tame post-Covid inflation in most countries, and they will be gradually decreased, from 2024 onwards. But what would be the potential impact if the easing cycle in each country was delayed by a quarter or more? The radar plot below shows the impact of a scenario where the start of...
Next in Tech | Episode 109 Dealing with uncertainty in risk modeling
Risk analytics can be powerful, but depend on the quality of data and the underlying model. How can we be certain that the results are valid? Arsene Lui, associate director for quantitative modeling, joins host Eric Hanselman to discuss the challenges of quantifying uncertainty - particularly important in these turbulent economic times. Credit risks are particularly complicated...
Using Credit Ratings Research to Filter Important Signals from Noise in New
In the past few years, macroeconomic factors have dominated the news headlines. This includes inflation, the COVID-19 pandemic, supply chain issues, geopolitics and, lately, climate change and natural gas disruptions in Europe. How can we find an objective metric to zero in on the themes that matter most from a credit risk perspective and track the importance of these themes ov...
