credit risk management

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Published By: FICO EMEA     Published Date: May 31, 2019
: FICO commissioned an independent research study by TM Forum to look at how global telecommunication providers are using (and plan to use) machine learning and advanced analytics to improve the customer experience in credit risk and beyond. This in-depth report includes key insights from a global survey as well as executive interviews with leading communication service providers such as Telstra, Vodafone, Sky, Globe Telecom, and BT on their vision for leveraging artificial intelligence to stop fraud, better engage customers across channels, improve risk management, and drive collection results. Read this report to understand: o What CSPs see as the biggest drivers for deploying advanced analytics over the next two years o How and where BT, Globe Telecom, Vodafone UK, Sky and Telstra are using analytics, from marketing through origination o The opportunities and pitfalls around financing devices as opposed to or in addition to subsidising them o The scope for analytics to improve c
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csp, advanced analytics, telco, improve credit risk, reduce fraud loss
    
FICO EMEA
Published By: IBM     Published Date: Aug 22, 2014
The ongoing processes of managing collateral, loan covenants and monitoring borrowers' financial condition are key to ensuring that banks are in the best position to minimize loss.
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credit risk management, managing collateral, financial monitoring, risk analytics, asset management, finance
    
IBM
Published By: IBM     Published Date: Jun 25, 2013
The global credit crunch that began in 2007 threw the financial industry into turmoil and highlighted the need for financial firms to improve their risk management practices. Today, the credit crisis is far from over. Markets remain volatile, and financial firms face waves of regulatory requirements intended to safeguard the solvency of individual firms and the stability of economies worldwide. These reforms will dramatically affect firms burdening the profitability and growth of some, and the very survival of others.
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risk management, financial industry, profitability, smarter risk management practices
    
IBM
Published By: SAS     Published Date: Aug 04, 2016
Banks have been using credit scoring models for over five decades, so managing the life cycle of models is nothing new. Most have had some kind of process in place to ensure the models they develop are robust, validated and monitored from a performance perspective and that decision makers have confidence in them. In recent times, however - partly in response to the credit crisis in 2008 - the discipline of model risk management (MRM) has become more formalized and rigorous, driving the need for enterprise-level model information management systems. The regulatory scrutiny being applied to them is intensifying and spreading globally, with US and European regulators leading the charge. For example, whereas regulators were previously more interested in the numbers they were provided, now more regulators want to have a core understanding of the models banks used to generate these numbers.
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best practices, risk management, finance, security, info systems
    
SAS
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