Data mining
Operational risk – Unleashing the power of AI to mitigate financial crime and manage conduct risk
Big data, data mining, machine learning and artificial intelligence have revolutionised how industry manages and mitigates risk. In light of the Covid-19 pandemic, what impact has this had on financial crime, what risks does remote working pose and how…
Basel NMRF changes don’t solve Asian data challenges
Isda AGM: Asian regulators may still need to soften FRTB standards locally, warn bankers
An optimized support vector machine intelligent technique using optimized feature selection methods: evidence from Chinese credit approval data
This paper focuses on feature selection methods for support vector machine (SVM) classifiers, checking their optimality by comparing them with some statistical and baseline methods.
The future of operational risk management
As the efficiency of operational risk management remains a top priority and pressure to maximise value increases, emerging technology could prove crucial. Nitish Idnani, leader of oprisk management services at Deloitte, explores how the oprisk management…
Making machine learning work for AML
Banks’ anti-money laundering teams are starting to utilise machine learning to combat financial criminals. Risk hosted a webinar in association with NICE Actimize to explore whether these bots can be trusted
Use-cases for Mifid II data prove elusive
Banks running market share analysis from trade reports, but data quality hampering other projects
Honesty is key to machine learning’s future – Roberts
Oxford-Man Institute director on why tomorrow’s models will gracefully admit defeat
Risk premia strategies do not reward downside
Study says alt premia approaches do not compensate for exposure to rough markets; hints at data mining
FRTB spurs data mining push at StanChart
Bank building “single golden source” of trade data in a bid to lower NMRF burden
Banks scan chat and web for trading intel
Market-makers seek new signals on volatility and direction via natural language processing
Systematic testing of systematic trading strategies
This study reviews the various statistical methodologies that are in place to test multiple systematic trading strategies and implements these methodologies under simulation with known artificial trading rules in order to critically compare and evaluate…
A call to arms – How machine intelligence can help banks beat financial crime
The revolution in artificial intelligence promises new leads in banks’ fight against dirty money. Alexander Campbell of Risk.net hosted a live online forum, in association with NICE Actimize, to investigate the applications of this emergent technology
Banks discreetly seek personnel to mine alt data riches
Citi, Credit Suisse, HSBC and Morgan Stanley are hiring data scientists for a plethora of new initiatives
AllianceBernstein digs into its own data, looking for alpha
Firm combs through information about its portfolio managers for signs of bias and bad habits
Podcast: Lo on adaptive regulation, machine learning, bitcoin
MIT quant says next project will be to combine behavioural science with tech such as machine learning
JP Morgan data scientist on mining and machine learning
Asset management arm looks to trawl internal data for investment edge
Falling margins force energy firms to expand data use
Verification and model challenges arise as volatility and margins dry up
Correspondent Banking in Euro: bank clustering via self-organizing maps
Volume 2, Issue 4 (2014)
From big data to smart data
Sponsored forum: State Street Global Exchange