For an effective market-discipline in the credit sector it is necessary that investors increase their capability of early detecting banks with sub-optimal solvency levels and produce timely responses, in proportion to the relevant idiosyncratic risk. This article explores the possibility of applying structural models for credit risk to calculate banks’ solvency indicators capable of extracting more information from balance sheet data and with a high discriminatory power if compared to the most common measures such as capital ratios and Texas ratio.
