Early Warning Signals Analysis and Debt Restructuring

This highly interactive online programme firstly provides an insight into the classic Early Warning Signals (EWS) that companies face as they get into financial difficulty. The emphasis will be to move on from examining only financial EWS which are time lagging and to focus on defects and mistakes that the company is making in volatile and stressed economic circumstances that will ultimately lead to failure. These behavioural EWS being more time leading, provide the corporate lender with more time to react to a worsening problem loan.  

 

The second half of the course will focus on methods of turning problem loans around through early problem loan workout. The aim is to provide work shop style applied examples covering methods of corporate work out that will allow the bank to recover its lending exposure from the continued operation of the client company, rather than putting the company into corporate recovery or liquidation. The recovery methods would be developed within the recovery and bankruptcy laws generally applicable to the African market and also will include examples of international best practice for problem loan workout.  

 

In the wake of the global financial crisis the international banking regulators in Basel have increasingly emphasised the need for corporate bankers to focus principally on the future cash flows generated by their corporate clients, as their principal source of debt repayment. In our current, extremely difficult economic global situation, sufficient liquidity and effective cash flow generation will essential to preserve the survival of the corporate client.  

  This greater move toward a reliance on future cash flows and away from the securitisation of loans by the fixed assets of the client to protect the bank’s exposure, has meant that bankers need to develop a detailed knowledge of the future cash flow forecasting and cash flow sensitivities as a central part of their credit risk analysis and debt structuring.  

 The case study companies that we will analysis during our online workshop sessions will comprise a broad range of different distressed companies operating across Africa. We will use fully interactive case studies and financial models to forecast future cash flows of the company and therefore will use these case studies as part of the debt structuring workshops.  

 Core areas of the course will include the following: 

  • Understanding the core areas that bankers need to analyse in identifying Early Warning signals in assessing and monitoring the credit risks of a corporate client; 
  • Identifying reasons why businesses typically face problems and mitigating potential risks through credit structuring; 
  • Using the company accounts and financial statements as a means for assessing the credit risk of a corporate client; 
  • Quantitative analysis of the corporate company through the use of company accounts; 
  • Reviewing models that can assist the banker in identifying major external risks that can impact the client company 
  • Qualitative analysis of a corporate client as part of the credit analysis process; 
  • Awareness of the commercial position of the various stakeholders in a business facing potential problems; 
  • Understanding which trigger events can call for different courses of problem loan solution 
  • Review of potential options available to the corporate banker when the client defaults; 
  • Fundamental principles in dealing with problem loans; 
  • An analysis of potential solutions to issues arising from problem loan clients; 
  • Application of the IFC problem loan matrix to understand potential solutions to problem loans 
  • International solutions to managing problem loans; 
  • Managing other bilateral lenders in dealing with problem loans; 
  • The application of the Standstill Agreement 
  • The use and effectiveness application of the Independent Business Report 
  • Key commercial issues to be included in the loan documentation for a corporate client that can act as EWS and risk mitigants. 

 

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