Artificial intelligence
Reinventing regulatory reporting with intelligent innovations
Technology-led innovation to transform regulatory reporting solutions
Augmenting the reliability and fairness of AI in financial services
How AI propels business innovation and efficiency in financial services.
Shaping the future of risk and finance with analytics and integrated technology
This webinar explores how to enhance business planning activities, while accelerating regulatory demands with limited resources amid a need to derive greater value from the analytic lifecycle
Vulnerabilities arise in financial services as AI and machine learning use balloons
The scale at which financial services firms are adopting artificial intelligence and machine learning continues to grow, bringing with it new dimensions of risk and vulnerability. In a recent Risk.net webinar sponsored by TCS, experts discussed…
Derivatives house of the year: JP Morgan
Risk Awards 2022: Big bet on AI is delivering results
Digital transformation and the future of GRC
This Risk.net survey report explores the impact of digitalisation on financial firms, and the changing strategies, resources and technology deployed by the governance, risk and compliance function
Digital transformation and the future of GRC
Covid-19 is forcing the pace of digital adoption in financial firms, placing new pressure on digital channels and processes
Leveraging data in e-FX trading
A white paper explaining how, in a world where electronic trading has infiltrated virtually every aspect of today’s FX market, having access to data and the means to interpret it are fundamental components of a successful e-FX strategy
Four ways to bolster cyber risk management and compliance
Since the pandemic, cyber threats against organisations have intensified. Here are four best practices we believe will become increasingly important for organisations to strengthen cyber risk and compliance management
Data to anchor a new age of risk management
The growth of artificial intelligence and real-time compliance drives new requirements in data and analytics
Language barrier: quants slog to teach investing bots to read
Training models to interpret text can be dull; doing it badly can be costly
Moonshots and machines: can AI solve the problems of fincrime?
New technologies such as artificial intelligence (AI) and machine learning promise much in the battle against financial crime, but where are these solutions best deployed? A panel of anti-money laundering and analytics professionals convened for a Risk…
New breed of NLP model learns finance better, study finds
Models trained by looking at sentences beat conventional approaches that contextualise words
Quants see promise in Bayesian machine learning
Risk USA: probability theory may hold key to creating ‘self-aware’ AI
Scalability could trump complexity in machine learning debate
Risk USA: banks “on the precipice” of adopting more complex models, says Goldman exec
Operational resilience: charting evolution, strengthening impact
Arming a business in preparation for robust operational resilience measures is not a one-step solution – it continues to evolve. The key to strengthening defences against all events – especially the unlikely but plausible – is to build business agility…
Data and AI: addressing increasing regulation for smarter compliance
This webinar features leading compliance and risk management professionals and focuses on how firms can handle regulatory change management, fraud prevention, AML and other compliance needs through the use of an optimal data and AI foundation built for…
Fed: banks may need AI risk systems to cope with smart devices
Tenfold increase in web-enabled devices via 5G and IoT means explosion in cyber threats, says official
Technology vendor of the year: NICE Actimize
Asia Risk Awards 2021
House of the year, Australia: ANZ Bank
Asia Risk Awards 2021
A survey of machine learning in credit risk
This paper surveys the impressively broad range of machine learning methods and application areas for credit risk.
Axes that matter: PCA with a difference
Differential PCA is introduced to reduce the dimensionality in derivative pricing problems