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Fed adviser denies plan to ‘euthanise’ Libor
IBA agreement to keep the benchmark alive would be welcomed but comes with risks, says Bowman
Large non-systemic US banks call for tailored liquidity rules
Two banks urge lawmakers to provide LCR relief because they do not fall into G-Sib category
Podcast: Richard Martin on EM debt, copulas, machine learning
Quant sceptical of machine learning algos and black boxes
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Risk Quantum
Data insights, delivered daily
Risk Quantum finds insights in data. The service tracks the public disclosures of over 120 banks, funds, insurers, corporates, and central counterparties – as well as reports from prudential and markets regulators – in Asia, Europe and North America.
Editors' choice
Swap spreads halve as dealers fight for corporate market share
US bank push, rate movements and evolving market practice driving spreads to “suicidal” levels
Big Figure
Big fraud
Fraud was the highest-volume operational risk event suffered by large UK banks in 2017, though the cost of execution, delivery and process management failures was more burdensome. Internal and external incidences of fraud accounted for 64% of all operational risk events at Barclays, Royal Bank of Scotland, Lloyds and Santander UK on average. However, these events made up just 14% of total losses in value.
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7 days in 60 seconds
Machine learning, stress tests and Sonia
The week on Risk.net, June 16–22, 2018
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Compliance must keep pace in AI arms race
Op risk data: Mexico bank hack fuels global payment network fears
Credit data: ‘dirty diesel’ woes weigh on autoparts firms
Energy transition: adapting to the unknown
Our Take
How machine learning could aid interest rate modelling
Asian NDF fixings threat signals yet another deadline drama
Replacing too big to fail with too small to survive
Modelling correlation: from zig-zag to zig-zig