Financial distress in Brazilian banks: an early warning model

Rosa, Paulo Sérgio; Gartner, Ivan Ricardo

doi:10.1590/1808-057x201803910

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Revista Contabilidade & Finanças

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Original Article • Rev. contab. finanç. 29 (77) • May-Aug 2018 • https://doi.org/10.1590/1808-057x201803910 copy

Financial distress in Brazilian banks: an early warning model^* * Paper presented at the XL Meeting of the National Association for Post Graduate Studies and Research in Business Administration, Costa do Sauipe, BA, Brazil, September 2016 ,^ The views expressed in this study are exclusively those of the authors, and do not necessarily express the position of the Central Bank of Brazil or its members.

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

This study aims to propose an early warning model for predicting financial distress events in Brazilian banking institutions. Initially, a set of economic-financial indicators is evaluated, suggested by the risk management literature for identifying situations of bank insolvency and exclusively taking public information into account. For this, multivariate logistic regressions are performed, using as independent variables financial indicators involving capital adequacy, asset quality, management quality, earnings, and liquidity. The empirical analysis was based on a sample of 142 financial institutions, including privately and publicly held and state-owned companies, using monthly data from 2006 to 2014, which resulted in panel data with 12,136 observations. In the sample window there were nine cases of Brazilian Central Bank intervention or mergers and acquisitions motivated by financial distress. The results were evaluated based on the estimation of the in-sample parameters, out-of-sample tests, and the early warning model signs for a 12-month forecast horizon. These obtained true positive rates of 81%, 94%, and 89%, respectively. We conclude that typical balance-sheet indicators are relevant for the early warning signs of financial distress in Brazilian banks, which contributes to the literature on financial intermediary credit risk, especially from the perspective of bank supervisory agencies acting towards financial stability.

Keywords:
financial institutions; risk management; financial distress; insolvency; early warning model

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Category	Attribute	FI (n)	Assets (R$ bn)	Market share (%)
Type	Conglomerate^a	62	4,820.18	93
Type	Bank	80	373.80	7
Size^b	Large	9	4,340.81	83.5
	Medium	16	484.13	9.3
	Small	53	330.35	6.4
	Micro	64	38.70	0.8
Control	State-owned	9	1,399.75	27
	Brazilian	77	2,592.93	50
	Foreign	56	1,201.30	23
Portfolio	Commercial, multiple with commercial portfolio	114	5,072.87	98
Portfolio	Multiple without commercial portfolio, investment bank	28	121.11	2
Share capital	Open	22	3,982.06	77
Share capital	Closed	120	1,211.92	23

Financial institution	Size	Ramifications	Reference date
Unibanco	Large	Merger with Itaú	10/2008
Panamericano	Medium	Acquisition by BTG Pactual	11/2010
Matone	Micro	Acquisition by JBS	1/2011
Morada	Micro	Act n. 1,185/2011 - Intervention Act n. 1,205/2011 - Receivership	4/2011
Schahin	Small	Acquisition by BMG	4/2011
Prosper	Micro	Act n. 1,235/2012 - Receivership	4/2012
Cruzeiro	Small	Act n. 1,217/2012 - Temporary special administration regime Act n. 1.230/2012 - Receivership	4/2012
BVA	Micro	Act n. 1.238/2012 - Intervention Act n. 1.251/2013 - Receivership	10/2012
Rural	Small	Act n. 1.256/2013 - Receivership	7/2013

Indicator	Category	Description (Cosif accounts)
CAP	Capital	(61000001: net equity) /
		(13000004: securities and derivative financial instruments +
		14000003: interbank accounts +
		15000002: interbranch accounts +
		16000001: credit operations +
		17000000: commercial lease operations +
		18000009: other credits +
		19000008: other values and goods)
PROV	Asset quality	(16900008: provisions for credit operations) /
PROV	Asset quality	(31000000: portfolio total)
EXP	Management quality	(81100008: funding expenses) /
EXP	Management quality	(40000008: current and long-term liabilities)
ROA	Earnings	(71000008: operating revenues -
		81000005: operating expenses) /
		(10000007: current and long-term assets +
		20000004: permanent)
LIQ^a	Liquidity	(11000006: available cash +
		12000005: short-term interbank investments +
		13100007: free securities financial segment index) /
		(41000007: deposits +
		42000006: repo operations)
PART_SIS	Market share	10000007: current and long-term assets +
PART_SIS	Market share	20000004: permanent
PERC_CRED	% credit portfolio	16000001: credit operations
PERC_SEC	% securities portfolio	13000004: securities and derivative financial instruments
IBOV6M	IBOVESPA	6-month cumulative return
IFNC6M	Securities financial segment index	6-month cumulative return
GROWTH_GDP	GDP	Annual variation
UNEMP	Rate of unemployment	Monthly rate

Variables^a	CAMELS	$\bar{x}$	s	Max.	Min.	Median	Asymmetry^b	Kurtosis^b
CAP^c	C	35.54	49.18	319.75	-30.67	20.28	3.79	19.18
PROV	A	5.39	7.35	40.30	0.01	3.64	4.99	39.44
EXP	M	1.83	1.98	6.50	0.01	1.46	14.92	525.20
ROA	E	0.09	1.23	2.27	-2.58	0.13	-10.35	609.10
LIQ^c	L	8.59	51.67	464.68	0.01	0.56	8.04	68.56
PART_SIS	-	0.78	3.29	24.25	0.0001	0.05	5.65	35.42
PERC_CRED	-	41.58	26.89	92.43	0.05	37.83	0.23	1.94
PERC_SEC	-	22.10	19.13	95.58	0.00	18.16	1.23	4.45
IBOV6M	-	5.30	20.59	56.84	-51.68	0.81	0.04	3.14
IFNC6M	-	9.87	21.63	88.25	-34.56	7.17	0.94	4.78
GROWTH_GDP	-	3.17	2.75	7.53	-0.33	2.73	0.17	1.81
UNEMP	-	7.21	1.78	10.70	4.60	7.10	0.33	1.91

Variables	Normal FI		Financial distress FI		∆ Averages	U^a Test
Variables	$\bar{x}$	s	$\bar{x}$	s	∆ Averages	U^a Test
CAP^b,c	35.75	49.34	12.24	9.61	-23.51	-9.14***^d
PROV	5.36	7.33	8.39	8.30	3.03	6.49***
EXP	1.83	1.98	2.57	1.68	0.74	5.42***
ROA	0.10	1.20	-1.00	2.95	-1.10	-7.34***
LIQ^b,c	8.66	51.89	0.50	0.37	-8.16	-4.82***^d

Variable	MV Function	LR χ² (1)	McFadden R²	Coefficient	z^a	p	AUC Y12	AUC Y24
CAP	-558.75	108.01	0.09	-0.100	-7.95	0.000	0.76	0.74
PROV	-597.89	11.26	0.01	0.029	4.06	0.000	0.68	0.66
EXP	-607.34	5.48	0.01	0.051	3.04	0.002	0.65	0.64
ROA	-601.93	21.26	0.02	-0.149	-4.55	0.000	0.71	0.61
LIQ	-592.20	40.91	0.03	-0.791	-3.84	0.000	0.63	0.64

McFadden R²	AIC	BIC	Cox-Snell R²	Cragg-Uhler R²	Total accuracy (%)	TP (%)	FP (%)	FN (%)	KS^a	AUC
Model 1: Y12 = f (financial indicators, control variable)
0.155	1035.4	1101.2	0.017	0.162	67.07	82.24	33.08	17.76	1.32	0.84
Model 2: Y12 = f (financial indicators, market indices, control variable)
0.162	1031.3	1111.7	0.018	0.169	68.16	85.05	32.01	14.95	1.48	0.85
Model 3: Y12 = f (financial indicators, market indices, macroeconomics, control variable)
0.212	974.4	1069.4	0.023	0.222	74.00	89.72	26.16	10.28	2.16	0.89

Y12	ϐ	Standard error^a	\|z\|	Standard error	\|z\|	Standard error	\|z\|	exp(ϐ)
		(1)		(2)		(2)
Intercept	3.250	1.232	2.64***	0.931	3.49***	1.699	1.91*	25.78
CAP	-0.062	0.015	4.10***	0.013	4.71***	0.030	2.10**	0.94
PROV	0.058	0.018	3.26***	0.012	4.61***	0.026	2.27**	1.06
EXP	0.056	0.030	1.93**	0.017	3.26***	0.026	2.16**	1.05
ROA	-0.466	0.086	5.41***	0.076	6.13***	0.137	3.40***	0.63
LIQ	-0.984	0.204	4.82***	0.162	6.07***	0.373	2.63***	0.36
PART_SIS	-0.053	0.045	1.18	0.019	2.78***	0.067	0.79	0.95
PERC_CRED	-0.014	0.009	1.61*	0.005	3.06***	0.013	1.08	0.99
PERC_SEC	0.022	0.009	2.48***	0.007	3.01***	0.023	0.94	1.02
IBOV6M	0.059	0.020	2.89***	0.018	3.26***	0.009	6.89***	1.06
IFNC6M	-0.072	0.023	3.13***	0.021	3.49***	0.011	6.56***	0.93
GROWTH_GDP	0.213	0.062	3.42***	0.059	3.60***	0.079	2.69***	1.24
UNEMP	-1.031	0.158	6.53***	0.123	8.34***	0.277	3.72***	0.36
MV Function	-316.8
McFadden R²	0.24
LR χ2 (12)	198.9
Prob > χ²	0.000

		Reality
		Distress	Normal	Total
Classification	Distress	60	1,785^b	1,845
Classification	Normal	14^a	5,726	5,740
	Total	74	7,511	7,585

	Observations (n)	Total accuracy (%)	TP (%)	FP (%)	FN (%)	KS^a	AUC
Model 3 - Estimation	7,585	76.28	81.08	23.77	18.92	2.01	0.896
Model 3 - Validation	3,409	71.22	93.94	29.00	6.06	2.05	0.903

		Reality
		Distress	Normal	Total
Classification	Distress	8	90^b	98
Classification	Normal	1^a	187	188
	Total	9	277	286

	Observations (n)	Total accuracy (%)	TP (%)	FP (%)	FN (%)	KS^a	AUC
Model 3 - Estimation	7,585	76.28	81.08	23.77	18.92	2.01	0.896
Model 3 - Validation	3,409	71.22	93.94	29.00	6.06	2.05	0.903
Signs - Early warning	10,994	68.18	88.89	32.49	11.11	4.95	-

Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade, Departamento de Contabilidade e Atuária Av. Prof. Luciano Gualberto, 908 - prédio 3 - sala 118, 05508 - 010 São Paulo - SP - Brasil, Tel.: (55 11) 2648-6320, Tel.: (55 11) 2648-6321, Fax: (55 11) 3813-0120 - São Paulo - SP - Brazil
E-mail: recont@usp.br

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[1] Correspondence address:Paulo Sérgio Rosa Universidade de Brasília, Departamento de Administração Campus Universitário Darcy Ribeiro, Bloco A-2, 1º andar, Sala A1-54/7 - CEP: 70910-900 Asa Norte - Brasília - DF - Brasil Email: paulo.rosa@bcb.gov.br