Merrill Lynch improves liquidity risk management for revolving credit lines

Tom Duffy, Manos Hatzakis, Wenyue Hsu, Russ Labe, Bonnie Liao, Xiangdong Luo, Je Oh, Adeesh Setya, Lihua Yang

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

Merrill Lynch Bank USA has a multibillion dollar portfolio of revolving credit-line commitments with over 100 institutions. These credit lines give corporations access to a specified amount of cash for short-term funding needs. A key risk associated with credit lines is liquidity risk, or the risk that the bank will need to provide significant assets to the borrowers on short notice. We developed a Monte Carlo simulation to analyze liquidity risk of a revolving credit portfolio. The model incorporates a mix of OR/MS techniques, including a Markov transition process, expert-system rules, and correlated random variables to capture the impact of industry correlations among the borrowers. Results from the model enabled the bank to free up about $4 billion of liquidity. Over the 21 months since the bank implemented the model, the portfolio has expanded by 60 percent to over $13 billion. The model has become part of the bank's tool kit for managing liquidity risk and continues to be used every month.

Original languageEnglish
Pages (from-to)353-369
Number of pages17
JournalInterfaces
Volume35
Issue number5
DOIs
StatePublished - Sep 2005

Keywords

  • Financial institutions: banks
  • Probability: Markov processes

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