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Many lending institutions across the world are still burdened with a high level of actual or potential nonperforming loans or other credit exposures. In these situations, lenders need to maximize their recovery rates and optimize their long term returns, subject to prevailing insolvency laws, the leder’s own capital situation and sometimes to the wider interests of other stakeholders in the firm.
Specialist knowledge is required to analyse the cause of the borrower’s problems and to design and implement an optimal restructuring solution. This can involve both operational and capital restructurings, including debt for debt swaps, full or partial debt for equity swaps, discounted debt buybacks, equity cures, shareholder loans etc. In some cases, the best outcome may be full or partial asset liquidation. Cashflow forecasting is key to creating an optimal debt restructuring solution and the course covers distressed debt restructuring solutions in Excel. Case studies focus on a range of sectors including property, retail, infrastructure, house building, media and industrial.
- How to find early warning signs of distress in company accounts
- The main operational and financial restructuring options and how to assess which should be the most appropriate
- How to model different rescue and liquidation scenarios for distressed firms in Excel
The teaching methodology used on this course combines formal theoretical instruction with frequent reference to market data, use of exercises and case studies. Case studies are based on real situations and are designed to help delegates implement new valuation techniques and to learn from empirical experience. Delegates are expected to know how to use Excel at a basic level and should bring a personal computer with them. The course is intended to be practical and interactive, with delegates encouraged to ask questions. The techniques taught to delegates are intended to be of immediate practical use in the workplace.
Agenda (12-16 November 2018)
For further questions regarding the course or the application please contact Krisztina Perge on email@example.com or via phone on +36 30 175 6538.