Research Seminar ‘Non-accounting data improves bankruptcy forecasts: Evidence from Benford Act and litigation’

Dmitry Skugarevsky, PhD, associate professor and Sergey Bondarkov, junior researcher from the European University (St. Petersburg) will speak on the topic of their research ‘Non-accounting data improves bankruptcy predictions: Evidence from Benford's law and litigation’.

Annotation: Bankruptcy prediction models typically use as features financial ratios derived from accounting statements. We extend this feature set by novel variables measuring good standing of a firm: conformity of the first significant digits in its financial statements with Benford's law and incidence of bankruptcy-unrelated litigation. The former measure relies on the long known observation that deviations from Benford's law may signal data manipulation. The latter builds on the intuition that would-be bankrupts face litigation related to their contractual non-performance before filing for bankruptcy. In a novel data set covering the near-universe of 2 million Russian firms in 2012--2018 we find feature importance and predictive capability of litigation-based variables on par to most of the financial ratios traditionally used in bankruptcy prediction, both for larger firms and small and medium-sized enterprises (SMEs). In contrast, conformity of statements with Benford's law is revealed as a modest bankruptcy predictor and an unimportant feature. We estimate that lenders of larger firms employing gradient-boosted decision trees-based bankruptcy prediction models with litigation variables could have increased their Expected Maximum Profit (EMP) by USD845 mln worth of total liabilities in 2018 in Russia in comparison with traditional financial ratio-based models. This is not the case for SME lenders: their EMP gain is estimated at only USD14 mln. This suggests that the search for improved bankruptcy models for SMEs may have little to no practical significance in certain real-life contexts. 
Please, register here or contact vkotelnikova@hse.ru to join the seminar.