TY - JOUR
T1 - Merrill Lynch improves liquidity risk management for revolving credit lines
AU - Duffy, Tom
AU - Hatzakis, Manos
AU - Hsu, Wenyue
AU - Labe, Russ
AU - Liao, Bonnie
AU - Luo, Xiangdong
AU - Oh, Je
AU - Setya, Adeesh
AU - Yang, Lihua
PY - 2005/9
Y1 - 2005/9
N2 - 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.
AB - 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.
KW - Financial institutions: banks
KW - Probability: Markov processes
UR - http://www.scopus.com/inward/record.url?scp=27844476930&partnerID=8YFLogxK
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U2 - 10.1287/inte.1050.0157
DO - 10.1287/inte.1050.0157
M3 - Review article
AN - SCOPUS:27844476930
SN - 0092-2102
VL - 35
SP - 353
EP - 369
JO - Interfaces
JF - Interfaces
IS - 5
ER -