Commercial Vehicles. Contents Commercial Vehicles – An Overview Objective of the Analysis ...
-
Upload
byron-crawford -
Category
Documents
-
view
222 -
download
0
Transcript of Commercial Vehicles. Contents Commercial Vehicles – An Overview Objective of the Analysis ...
Commercial Vehicles
Contents
Commercial Vehicles – An Overview
Objective of the Analysis
Preliminary Analysis of CV Pools – All Originators
Preliminary Analysis of CV Pools – Only AU Financiers Ltd.
Detailed Analysis of CV Pools – All Originators
Market Outlook
Conclusion
Commercial Vehicles – An Overview
Commercial Vehicles
What is a Commercial Vehicle (CV)?
A Commercial vehicle is a type of motor vehicle that may be used for transporting goods or passenger.
Importance on CV Industry in India
Trucks can access remote and hilly areas where rail lines cannot be constructed.
The CV industry enables quick, easy departure of goods and accepts smaller loads than railways.
The industry has captured short-haul goods transport and a major chunk of long-haul goods transport where quick delivery from railways is essential.
Major Classification of CV Industry
Light Commercial Vehicle (LCV) – Goods & Carriage Vehicle with light capacity with Minimum Permissible Capacity (MPC) of 7 – 11 tons
Medium Commercial Vehicle (MCV) – Single Axle Vehicle used mainly for the carriage of perishable goods with MPC of 16 tons of Mass
Heavy Commercial Vehicle (HCV) – Dingle Axle Vehicle used mainly for the carriage of non-perishable goods with MPC of 17 to 25 tons of Mass
Major CV Financiers in India
Cholamandalam Finance, Sundaram Finance, AU Finance, Shriram Transport Finance, Magma, L&T, M&M, Religare, Tata Motors, Reliance
Objective of the Analysis
Objectives
Identify the factors which significantly affect the pool performance (delinquencies)
Illustrate the way in which these factors affect the delinquencies
Preliminary Analysis of CV Pools – All Originators
Data Used – An Overview
Securitized CV pool details from the Pool Performance reports (Sep’12) of Rating Agencies (CARE, ICRA and CRISIL)
Total number of Transactions (Data Points) - 190
Period of Transactions - 2008-2012
Number of Originators - 16
Major Originators used for Analysis
Shriram - 58 Transactions
Magma - 34 Transactions
AU - 21 Transactions
Tata Motors - 18 Transactions
Sundaram - 13 Transactions
Religare - 12 Transactions
Reliance Cap - 9 Transactions
Collection Details & Methodology Used
Parameters Collected for Analysis:
Transaction Details : Transaction month, Transaction Name, Originator, Transaction Structure, Type of Transaction, Rating Assigned for Seniors and Junior
Initial Pool Details : Pool Principal, Pool Composition, Credit Enhancement (% of Initial POS), EIS (% of Initial POS)
Pool Performance Details : Cumulative Collection Efficiency (CCE)
Methodology Used:
Collection of data from the Pool Performance (Sep’ 12) reports of Rating Agencies
Identification of factors, which are to be used for the analysis of transactions
Regression Analysis of these factors with respect Sep’12 CCE and Scatter plots to capture trends
Observe the significance level of factors which affects CCE
Findings from Preliminary Analysis of CV Pools (All Originators)
Pools having greater NCV Exposure (>40%) tend to
have better collection efficiency and lower credit
Enhancement (Figure 1)
Cumulative Collection Efficiencies of transactions are
continuously declining with respect to the year of
transactions during 2008-2012 (Figure 2)
Au pools seems to have the lowest CCE when
compared to its competitors in CV Industry (Figure 3)
Figure 2
2008 2009 2010 2011 20120
10
20
30
40
50
60
93%
94%
95%
96%
97%
98%
99%
100%
2
28
52 52
28
CCE by year of securitization
Total Transaction Collection EfficiencyYear
0
10
20
30
40
50
60
70
88%
90%
92%
94%
96%
98%
100%Originators and CV Analysis
No. of securities WCE
Figure 3
Figure 1
Preliminary Analysis of CV Pools – AU only
Data & Methodology Used
Data Used:
Securitized CV pool details from the Pool Performance reports (Sep’12) of Rating Agencies (CARE, ICRA and CRISIL)
Total number of Transactions (Data Points) - 21
Period of Transactions - 2010-2012
Parameters Collected for Analysis:
Transaction Details : Transaction month, Transaction Name, Originator, Transaction Structure, Type of Transaction, Rating Assigned for Seniors and Junior
Initial Pool Details : Pool Principal, Pool Composition, Credit Enhancement (% of Initial POS), EIS (% of Initial POS), Weighted Average Seasoning (Months), Tenure (Years)
Pool Performance Details : Cumulative Collection Efficiency (CCE)
Methodology Used:
Collection of data from the Pool Performance reports of Rating Agencies & Identification of factors, which are to be used
for the analysis of transactions
Single & Multiple Regression of these factors with CCE, Scatter plots for trend capture
Observe the significance level of factors affecting the delinquencies
Findings from Preliminary Analysis of CV Pools (AU Only)
Average CCE is better for the pools with Short Tenure
(<3 years) and High WAS (> 3months)
Average CCE is the lowest (around 92%) when the
pool mix is CV,AUTO and Tractors when compared to
other mixes
Average CCE, with respect to CV and Auto mix, is
ranging around 94%.
*CI in Figure 1 & 2 represent Confidence Interval
Figure 2 Figure 1
Detailed Analysis of CV Pools – All Originators
Data Used – An Overview
Securitized CV pool details from the Pool Performance reports (from Jun’ 08 to Dec’12) of Rating Agencies (CARE, ICRA
and CRISIL)
Total number of Transactions (Data Points) - 194
Period of Transactions - 2008-2012
Number of Originators - 14
Quarterly data is collected for Cumulative Collection Efficiency and Quarterly Average Collection, starting from the first data
to the latest one available.
Major Originators used for Analysis
Shriram - 58 Transactions
Magma - 34 Transactions
AU - 21 Transactions
Tata Motors - 18 Transactions
Sundaram - 13 Transactions
Religare - 12 Transactions
Reliance Cap - 9 Transactions
Collection Details & Methodology Used
Parameters Collected for Analysis:
Transaction Details : Transaction month, Transaction Name, Originator, Transaction Structure, Type of Transaction, Rating Assigned for Seniors and Junior
Initial Pool Details : Pool Principal, Pool Composition, Credit Enhancement (% of Initial POS), EIS (% of Initial POS), Weighted Average Seasoning (Months), Average Loan to Value, Average
Loan Size
Pool Performance Details : Cumulative Collection Efficiency (CCE), Quarterly Average Collection, 90+ & 180+ Delinquency Loss
Methodology Used:
Collection of data from the Pool Performance reports of Rating Agencies & Identification of factors, which are to be used
for the analysis of transactions
Single & Multiple Regression of these factors with 90+ and 180+ delinquencies
Observe the significance level of factors affecting the delinquencies
Findings from Detailed Analysis of CV Pools (All Originators)
In the transactions, Originators have greater impact on
delinquencies than the other parameters (Figure 1)
None of the other pool parameters are found to have
significant impact on the pool performance in multiple
regression (Figure 1)
Individual regression results suggest that more % of
NCV (less % of UCV), high Weighted Average
Seasoning and high Loan Size have positive impact on
delinquencies (Figure 2)
Figure 1 – Multiple Regression with 180+ Delinquency
Figure 2 – Individual Regression with 180+ & 90+ Delinquency
Limitations & Future Works
Limitations
Data Collected for only those transactions that are done after June 2008.
Reporting format was not uniform across all the rating agencies.
Inferences are based on small sample size.
Future Works
Time Series analysis of Delinquencies and Cumulative Collection Efficiency of earlier transactions to date and also from the
perspective of an originators can be done
All the originators should be analysed according to the individual assets of the pools (type of underlying vehicles).
Analysis of relation between the closely related independent factors viz. Loan size and % of NCV so as to figure out that
which of the two factors actually impacts the performance
Comparing the rating rationales, for similar rated transaction with different credit enhancement or vice versa, more deeply to
understand the factors seen by rating agencies
Market Outlook
Recent Study by ICRA
Asset Quality of CV
UCV – 90+ DPD 6.8% and 180+ DPD 3.8%
NCV - 90+ DPD 6.2% and 180+ DPD 1.5%
Macro-Economic Indicators
Correlation between GDP vs. 90+ DPD = -83% (-91% with three months lag of 90+dpd)
Correlation between IIP vs. 90+ DPD = -91%
Portfolio Analysis
In FY13, Average Tenure is 43 months
TN & Maharashtra contributed around 35% of total disbursement
MHCV weaker performance than other asset classes
High Tenure Contract (3 Years) showed weaker performance
Contracts originated in Orissa and Goa is affected a lot because of Mining Issues
Contracts with higher interest rates performed weakly
Repossession Loss
37% in New LCV and 39% in New MHCV
Loss due to repossession in UCV is slightly lower than New CV’s (Probably because of Lower LTV)
Repossession Rates in FY13 is ranging around 30-50%
Resale Value is reduced by 10-20% due to demand decline and discount on new vehicles
Conclusion
Concluding Remarks
Originators play an important role compared to other parameters when it comes to the
performance of CV Pools.
Also, with fair degree of confidence, it can be said following parameters have an
impact in a pool’s performance
% of NCV Exposure
Weighted Average Seasoning
Tenure of the pool
Loan Size (May be correlated with other factors like % of NCV)
GDP and IIP are the major indicators of CV industry
LCV - Safer bet than MCVs and HCVs
Questions ??