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Useful Resources


Transforming strategic risk management to realize competitive advantage
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SAS – WHITE PAPER “6 Keys to Credit Risk Modeling for the Digital Age”

This SAS White Paper focuses on the emerging role of machine learning and alternative data in credit decision making. Technology advances such as high-performance, in-memory processing and machine learning have redefined the credit risk management. Lenders that capitalize on modern technology to re-engineer their credit risk scoring and decision systems can improve the quality of leads and make better recommendations, while reducing manual activities, maintenance costs and losses.

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SAS – Risk-Aware Finance and the Changing Nature of Credit

Shaken by the financial crisis and shaped by a wave of new rules and regulations, credit – and the risks it carries – is changing. New research by Chartis and SAS highlights how Financial Institutions looking to address the shifting nature of credit must align their finance and risk departments to accurately assess the dynamics of future risks and bolster their budgeting and forecasting capabilities.

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Risk Landscape Review – JUNE 2018

The European Risk Management Council launched its quarterly publication “Risk Landscape Review”. The first edition includes 11 articles dedicated to main topics discussed at the UK Leadership Meeting and written by our speakers. The Q2 2017 edition includes five articles covering macroeconomic, political and liquidity risks as well as cyber security and risk culture.

Q2 2018 RLR
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Risk Landscape Review – MARCH 2018

The European Risk Management Council has published the Q1 2018 Risk Landscape Review. This edition consists of four articles including a keynote speech “Adapting as Leaders to a Fractured World” of Dr Lee Howell, Managing Director, Head of Global Programming and Member of Managing Board of the World Economic Forum, delivered at 2018 European Leadership Meeting on 8 March 2018.

Q1 2018 RLR
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Oliver Wyman – NEXT GENERATION RISK MANAGEMENT

Many drivers are shaping the context of risk management today. Macroeconomic headwinds, global geopolitical uncertainty, and ever more frequent and damaging cyber events have been in the vanguard of challenges leading to heightened risk perceptions. At the same time, investment in risk management is under pressure. The changes in banking regulation, to address shortcomings highlighted by the Global Financial Crisis, have transitioned from the uncertainty of planning stages to implementation; these coupled with low productivity growth are pressuring returns.

OW Next Generation
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Oliver Wyman – RISK FUNCTIONS AT BANKS AND INSURERS MUST BECOME MORE AGILE

Large, long-established firms find it hard to change. That’s okay in a stable business environment when you’ve got time on your side, but when things start to change quickly in the external market, it puts your organization at risk. Hence, the current fixation with “agility.”

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Oliver Wyman – MANAGING NEXT GENERATION ARTIFICIAL INTELLIGENCE IN BANKING

Financial services executives view artificial intelligence (AI) with a powerful mix of excitement and concern. With new proofs of concept, innovation labs and investments in technology appearing every day, financial institutions are eagerly exploring AI to improve business decisions, customer experiences and risk management outcomes.

OW AI
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Oliver Wyman – THE CUSTOMER VALUE GAP: RE-CALCULATING ROUTE

While we are using the global mass market as an example throughout this report, the core messages and approaches apply across all of financial services (FS) – and other industries as well. Anywhere customers are served, customer value gaps can emerge and better solutions can be crafted to fill them. The affluent, small businesses, commercial and corporate clients are all affected by the same trends.

OW Value Gap
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Risk Landscape Review – June 2017

The European Risk Management Council published Q2 Risk Landscape Review. This edition includes five articles which cover macroeconomic, political and liquidity risks as well as cyber security and risk culture.

Q2 RLR
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