Arindam Bandyopadhyay: Poor default history

Indian banks need to strengthen their recovery mechanism to gear up to meet Basel-II standards.

Loss-given-default (LGD) is an important determinant of credit risk, and is the degree of uncertainty about how much the bank will not be able to collect if a borrower defaults. Banks must measure this loss arising from counterparty default in order to graduate towards the proposed Basel-II minimum capital regulatory framework.

The historical LGD (or accounting LGD) equals 1-historical recovery rate (RR). The historical RR is the sum of the cash flow received from defaulted loans divided by total loan amount due at the time of default (EAD). Economic LGD is the economic loss in the case of default, which can be very different from the accounting one. "Economic" means all costs incurred with recoveries have to be included in the loss estimate, and that the discounting effects have to be integrated. 
 

DEFAULT HISTORY
	Loss-given-default (%)		Default-weighted Loss-given-default (%)
	Historical	Economic	Historical	Economic
Commercial: Loan >Rs 50 lakh                                       Period: 1998-2007
Bank 1 (Mid-sized)	62.6	78.0	63.2	78.9
Bank 2 (Small)	81.0	87.1	17.9	19.1
Bank 3 (Mid-sized)	84.9	90.5	82.4	87.7
Bank 4 (Small)	73.8	80.4	57.5	62.7
Bank 5 (Large)	64.7	81.7	129.3	163.4
Bank 6 (Large)	80.6	84.9	102.3	107.8
Bank 7 (Mid-sized)	66.5	76.5	43.9	50.5
Average	73.4	82.7	71.8	82.5
Retail                                                                                    Period: 1998-2007
Bank 1 (Mid-sized)	65.3	71.7	184.9	202.8
Bank 2 (Small)	60.0	64.9	13.2	14.3
Bank 3 (Mid-sized)	""	""	""	""
Bank 4 (Small)	""	""	""	""
Bank 5 (Large)	""	""	""	""
Bank 6 (Large)	68.9	96.8	127.4	179.2
Bank 7 (Mid-sized)	""	""	""	""
Average	64.7	77.8	66.4	80.9
1. Commercial loan exposures include defaulted corporates, commercial SMEs, NBFCs, and commercial real estate exposures. 2. Retail loan exposures include housing loans, auto loans and other consumer loan exposures, including student and personal loans, and defaulted credit card exposures. 3. A discount rate of 10.5% is used for calculating economic LGD.

Because loan recovery periods may extend over several years, it is necessary to discount post-default net cash flows to a common point in time (the most suitable being the event of default). The LGD on defaulted loan facilities is thus measured by the present value of cash losses with respect to the exposure amount (EAD) at the defaulted year. This can be estimated by calculating the present value of cash received post-default over the year's net discounted cost of recovery.

If we divide this net discounted recovery by the exposure amount at default time (EAD), we get the recovery rate. Say, the RR is 40 per cent in this example, then the loss given default rate (LGD) is 60 per cent, which is 1-RR.

At the moment, there is no study on LGD in India. So, the National Institute of Bank Management (NIBM) undertook a survey of the LGD of Indian banks to bridge this gap and assist them in improving their credit risk management practices in line with the Basel-II guidelines. The loss data on defaulted loans was collected from seven Indian public sector banks (PSBs). Among them, two are large, three medium-sized and two are smaller-sized banks in terms of total assets.

These banks have given us 691 commercial (with an exposure of more than Rs 50 lakh) and 490 retail NPA accounts, and their recovery experiences from 1998-2007. Commercial loan accounts comprise of defaulted corporates, commercial SMEs, NBFCs and commercial real estate exposures. The retail-defaulted accounts are defaulted housing loans, auto loans, other consumer loan exposures, including student and personal loans, and defaulted credit card exposures.

Based on this data, we have worked out the economic LGD, which is the discounted portion of defaulted loans the bank is not able to recover. The bank-wise LGD statistics across borrower categories are shown in the table. The LGD figures are higher for large commercial exposures than for smaller or retail loan segments (simple historical LGD for commercial loans is 73.43 per cent in comparison to an average of 64.74 per cent for retail loans). The default weighted average gives the severity of loss average which adjusts the loss number with the number of defaults.

In our survey, we have found that collateral liquidity and marketability have great influence on recovery. Loans with good collateral and market value have shown better recovery (lower LGD) than unsecured loans and loans with less liquid collateral. Moreover, the collection time also has an importance in recovery. A lesser delay in the collection process yields better recovery. International experience suggests that the collateral value falls faster than the health of the account.

The Indian experience in our survey suggests that LGD rates are higher (73.43 per cent for corporate and 64.74 per cent for retail) than those globally. Moody's 1970-2003 study of US bank loans shows an average LGD rate of 36.10 per cent, of which corporate LGD was 60.09 per cent. The high LGD rate is a sign of weakness in the recovery mechanism of Indian banks.

There is a positive correlation between the GNP growth and LGD rates. However, there is a lead-lag effect. When the growth is high, the recovery rate peaks (with a temporal gap of one-two years), and the LGD rate slows down. Whenever there is a dip in growth, it has an adverse impact on the recovery process and the LGD rates peak.

The high loss rate on defaulted bank loans thus warrant better and prompt recovery strategies to reduce credit risk losses. LGD is a time-dependent issue and the concept is not yet formalised in India. As the banking sector realises its relevance, LGD levels will improve. LGD figures in banks would also help them to negotiate the sale of their bad loans with other banks.

Because of illiquidity and rigidity in the legal system, banks hardly find any exit route for their defaulted loans. As banks become more capital conscious, collateralised debt obligations (a type of investment grade bond) and credit derivative products (like credit default swaps) will also emerge which will enable banks to trade their loans either directly or indirectly and will bring liquidity in the credit portfolio.

The dynamic character of bank loan management requires developing a facility-wise recovery rating (or LGD rating) besides having a borrower-specific obligor rating system. Banks need to rate collateral security documents pledged against the loan facility to manage LGD. This requires more realistic collateral valuations since collateral plays a significant role in secured lending.

A facility LGD rating model would not only benefit banks for Basel IRB compliance but also for loan recovery. It is worthwhile to mention that Basel-II IRB compliance requires a two-tier rating system (obligor rating and facility rating). LGD rating for standard accounts should seek to incorporate key factors affecting recovery prospects after default. This requires data archiving with great care and the tracking of exposure and collateral received throughout the life of a loan.

While working on the bank's loss data, we found some important factors contributing to the bank's net recovery rate. The interplays of these factors (policy factors as well as real factors) would help banks to predict the recovery prospects of what are still standard assets. For example, we have found that the shorter the collection process's length (that is, the number of years for recovery), the better is the chance of recovery, and hence, the LGD is lower.

The author is Assistant Professor, National Institute of Bank Management (NIBM), Pune. He can be reached at arindam@nibmindia.org