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The use of corporate ledger information in payment behavior prediction - Evidence from the Finnish construction industry
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School of Business |
Master's thesis
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en
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82
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ABSTRACT
This paper provides new insights into payment behavior prediction by using daily ledger data from
a case company. The results indicate that a model based on ledger information is more accurate
and efficient in future payment failure prediction than models traditionally based on financial
and background variables. More specifically, the results implicate that a company benefits the
most from credit risk rating services when its own ledger data are used as a part of the rating
scoring model. In addition, the results have three implications. First, ledger information can be
used in the future to create more accurate and up-to-date credit rating scores, which reduces the
dependency over publicly available information. Second, the length of the client firm-creditor
firm relationship seems to significantly reduce problems of informational asymmetry. Third,
problems of asymmetric information, such as adverse selection, lemon’s problem, moral hazard
and agency costs could be significantly reduced in the future using a shared information pool
deriving from corporate ledgers.