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Increase profitability and efficiency whilst ensuring regulatory compliance is maintained in a fast moving environment.
SAS has a proven methodology to help establish a risk-aware culture, optimise capital and liquidity, and efficiently meet regulatory demands. The solution portfolio includes:
Asset & liability management – improve regulatory compliance and instill powerful balance sheet management capabilities
Credit risk management - Deploy a broad range of scalable credit models to continuously manage your loan portfolios
Enterprise stress testing - Simulate stress testing over multiple scenarios. Produce results faster with a richer analysis to inform business decision making
Expected credit loss - Execute the entire ECL process in a substantially reduced time frame using a controlled, high-performance environment
Risk governance - Proactively govern risk management processes to achieve business and regulatory goals
Insurance risk management - Adopt a single, integrated framework for IFRS 17 and Solvency II compliance – and beyond
Regulation continually broadening and deepening – the magnitude and speed of regulation in the financial services sector driven by the public sentiment which is becoming increasingly less tolerant of banking failures and use of public money to salvage them
Customer expectations are rising in line with advancing technology – Innovation in technology has resulted in a new set of competitors. These organisations do not want to be banks, they want to take over the direct customer relationship and most lucrative part of the financial institution’s sales value chain.
Technology & advanced analytics are evolving – advances in Big data and Machine learning are enabling new risk-management techniques to be introduced at lower cost.
New risks are emerging – new and unfamiliar risks are becoming common; for example model risk, cybersecurity risk and contagion risk.
Pressure on cost savings – The banking and financial services sector has suffered from a slow and constant margin decline. As the downward pressure on margins continues the emergence of low-cost business models used by digital attackers
Automation of complex risk management processes – Build an automated governance and workflow solution. Increasing efficiency & transparency whilst reducing model risk
Powerful & scalable analytics capabilities – Quickly develop and implement models with the ability to analyse large credit portfolios drilling down to individual loan assessments when required
Customizable, adoptable data & reporting –Integrate and stage high quality data to provide all the transparency needed to answer both current and future reporting requirements on-demand. The flexible data models address both industry standard and open-source software requirements
Powerful modeling environment –Develop a range of credit risk solution models using SAS code, Python, R & incorporate AI machine learning models into your solutions.