This case study reveals how Mirabaud Asset Management is using IHS Markit’s Enterprise Data Management (EDM) platform to establish a strong foundation for the its long-term SRI-ESG (socially-responsible / environmental, social and governance investing) strategy. This includes empowering Mirabaud’s…
Only a couple of months into the year, we have been surprised by the coronavirus. How will the recent monetary policy actions and market reaction affect your FY2020 plan and beyond? In this report, MORS Software have called for an extraordinary meeting of their demo bank "IBSM-Bank's” ALCO to…
This whitepaper explores some of the most exciting data analytics solutions out there. If you want to harness machine learning, plug in forecasts to your own systems, or completely overhaul your forward curve management systems, keep reading - we have a solution for you.
In our 2020 risk management guide, we provide our expert view on the market outlook and outline how you can solve your risk challenges with Risk as a Service – the easy way to manage risk across the enterprise, from complex risk calculations, modeling, analytics, managing risk data and reporting.
Model Risk Management for a Trading Firm’s Calculations - A Data Centric View of Model Risk Management
This white paper appraises four pieces of regulation that directly address the management of risk within models. It further gives an overview of the importance of data lineage in a modeling ecosystem and provides background to some key data lineage concepts.
Read this article on how IFRS 17 can help you to achieve greater alignment across the organization in driving both top- and bottom-line growth. Review the components to be included in a complete solution design to support the new standard, while advancing alignment and transparency.
Compliance with the complex new standard for insurance contracts will require an overhaul of the processes and the IT systems and this Survival Guide will help you successfully navigate the change.
This white paper explains why traditional master data management (MDM) systems do not scale to meet the needs of large, multinational financial companies. It further explores a new MDM reference architecture that applies machine learning algorithms to the problem.
As the Financial Action Task Force and the Asia-Pacific Group on Money Laundering approaches its fourth round for mutual evaluation of Japan’s anti-money laundering compliance regime, many institutions—particularly regional and community banks—have found grasping the fundamentals of the problem a…
The intent of this paper is to analyse how model risk management requirements change the banks’ view on their models, especially regarding the quantification of associated risks, and to introduce a new framework methodology.