Bankgesellschaft Berlin Case Study – Credit Risk and Operational Risk

This article briefly discusses the losses incurred by Bankgesellschaft Berlin in 2001 which was one of Germany’s top 10 banks.

The Case

In the mid-1990s some of the key subsidiaries of the bank started making massive loans to property developers. It also set-up property-backed funds that offered generous guarantees to retail investors.

In 1999, the Berlin’s property and rental bubble burst which led to massive losses and liabilities in their property-linked portfolios.

In July 2001, BgB reported a massive loss of E1.65 billion for the year 2000. Early in summer 2001, the Berlin senate was informed that Bankgesellschaft Berlin needed an emergency transfusion of E2 billion in new capital. In September 2001, Berlin pumped E1.75 billion of new capital into the bank to secure its future.

Risk in property-based Funds

  • The funds offered financial guarantees to investors against the risk inherent in the investment as a part of the deal.
  • BgB became a leading player in European real estate investment fund market, and grabbed more market share by taking real estate risks that were not appropriately measured/managed.
  • BgB property-related risk was very high because it also had extended huge loans to property developers.

Key risks

There were two key risks:

  • Credit Risk: This arose from loans to property developers.
  • Operational Risk: This arose from management’s actions and decisions.

Lessons learned

  • Extending investment guarantees to attract investors and build volume was a dangerous strategy, and the banks should assess the downside risk before extending any such schemes.
  • It is important for banks to follow sound risk management principles, have stricter loan appraisal procedures, and appropriate tracking of credit risk concentrations.
  • The board must be kept aware of the risks underlying business activities.
  • Bank risk management and politicians don’t go well together.

Full case study is available at PRMIA website.

Learn the skills required to excel in data science and data analytics covering R, Python, machine learning, and AI.

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Saylient AI Logo

Take the Next Step in Your Data Career

Join our membership for lifetime unlimited access to all our data analytics and data science learning content and resources.