Risk Management Insights

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Enterprise Risk Management, Risk Management, ERM, Risk Management Software

The Experience of Having a Risk Management System

A REAL LIFE APPROACH

Risk management is a continuous journey. In our personal lives we instinctively make risk based decisions according to our own risk appetite. As we move from our teenage years to adulthood to middle age to our senior years, our internal risk management evolves and matures. The same applies with the organisations we work within. Their external and internal context evolves, their risk management matures and evolves to meet the challenges of the changing environment.

This week’s blog is an interview with Michael Blacker, Chief Risk Officer at Police Bank. In this interesting conversation, he shares his experiences and challenges with the evolution of risk management at Police Bank and explains how Protecht.ERM is being used to embed risk management throughout the organisation. We hope that you enjoy the interview.

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Enterprise Risk Management, Risk Analytics, Risk Management Software

10 Great Features of Protecht Enterprise Risk Management Software

Having an (ERM) has become a MUST

Enterprise Risk Management has become a must for all organisations, regardless of size, complexity and industry sector. Companies are asked by regulators, shareholders and other stakeholders to demonstrate that the organisation has risk-management policies and procedures implemented and embedded. No longer is it sufficient to show that an organisation understands its material risks, but needs to demonstrate how their approach to risk management is driving enhanced performance against objectives.

In a previous post, we mentioned that embedding enterprise risk management techniques into business decision-making processes, can and will drive improved business performance, not just risk mitigation.

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Risk Culture, Risk Management Software

Business Intelligence for Commercial Credit Risk Management

Good practice in credit risk management is to turn periodic core banking data (eg. portfolio balance vs arrears) into meaningful information for ongoing portfolio monitoring and loan loss analysis. The process of transforming raw data into meaningful information to support business decisions is denoted by the term ‘Business Intelligence’ (BI). This can provide banks and other commercial lenders with better visibility and management of credit risk across commercial credit portfolios.

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Risk Analytics, Risk Management Software

Moving from ALM Risk Data to ALM Business Intelligence

As Albert Einstein said “If you can't explain it simply, you don't understand it well enough”…

Interest rate risk measurement typically has a number of processes attached to it:

  • Reconciliation of balance sheet data;
  • Confirmation of rates used for Earnings at Risk (EAR) and volatility calculations;
  • Parameters and assumptions appropriately checked;
  • Key outputs checked for reasonableness; and
  • Attribution analysis to interpret movement in measures.

Much time is devoted to these processes to derive a set of point in time numbers - such as: Value at Risk (VaR), Present Value of a Basis Point (PVBP) or EAR at a particular run date. However, how much consideration and effort do you need to give to turning this point in time data into useful business intelligence? 

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