Jun
14
2013

Collections Scoring Models for Autofinance portfolio

Auto finance is one of the important retail products offered by most of the banks and more importantly by the automobile manufacturers also having a dedicated business unit for Financial Services.

Autofinance has two business segments:

  1. Financing
  2. Leasing

The customers can also be segmented as:

  1. Private Individuals
  2. Business

Other segmentations include the Old/ New vehicle.

The collections process of Auto finance portfolio is therefore not as simple compared to the other retail banking products like Personal Loans, Credit cards etc. The simple reason being that the value of the car depreciates with every passing day. This calls for higher efficiency of the collections system and processes using sophisticated models for scoring and segmentation. Furthermore, the collections process of autofinance does not end with the cancellation of the contract, but continues with further additional activities of repossession of the vehicle, selling it, adjusting the balance and litigation and recovery for the balance outstanding.

The higher volumes of cases in collections with a mix of above segments can pose extremely challenging situations for effective and optimal management of collections resources. This demands a robust scoring and segmentation model to cater to the growing needs of the collections portfolio. The risk groups for the portfolio should be categorised as High, Medium, Low and Premium.

Drivers to prioritize operational level collections.

Another very important driver in prioritizing is the segmentation on the Old / New vehicles. This variable should be used at operational level in prioritizing the actions or queue the accounts in the operational workflow system.  As we know that new cars have higher value, those accounts have to be worked before the old cars. These segmentations can be built at different levels, firstly at the scorecard level and secondly at the operational level to set up the workflows and prioritize actions.

Difference between Financing and Leasing customers

Financing and Leasing business have to be segmented differently based on the definition of the business contracts. In financing the customer will own the vehicle after the successful repayment of the loan amount. Whereas in leasing the ownership of the vehicle is retained by the leasing company and only the monthly instalment is paid for the period the vehicle is used.

The second level of segmentation is the customer type i.e. Private individuals and Business. The private individuals have largely single contracts, whereas the business customers can have multiple contracts and that makes collections on the overdue contracts even more complicated.

Therefore while designing the scorecard models; these basic segmentations have to be considered. Overlooking these can lead to lesser effective scorecards leading to ineffective risk segmentation strategies.

Stages in Collections

The various stages in Collections for Auto finance portfolio are:

Early Collections, Mid Stage Collections, Repossession, Litigation, Late stage Collections and Recoveries.

The number of scorecards in every stage can vary depending on the business requirements. The best practices recommend that the number of score cards should not be too less or too many but optimal to cover the entire portfolio for effective risk segmentation for the above mentioned phases.

Most businesses are not certain if they would go for a static scoring model or a dynamic scoring model. This largely depends on the Work flow system being used for collections treatments. The static model has a collections score for the accounts at the time when the account enters Collections i.e. 1 Dpd and follows a standard treatment paths as defined till the time it is cancelled. This model has a disadvantage that if the accounts are good and have been in collections with no payments for over 2months, the collectors are unable to take a decision on how to treat these customers. Therefore, the static scoring model has a limitation only till the initial buckets and for the midstage collections, the accounts have to be re-scored to reassess the risk on them for better segmentation and treatment. That means the accounts after getting scored in early collections will be need another scorecard for the mid stage collections to update the risk segments and then treat the accounts accordingly.

In other case, if the operational workflow system is capable of re-routing the cases based on the dynamic movements in buckets a dynamic model will be the most appropriate Best Practice

The good bad definition changes with every phase and for every scorecard in that phase. The good bad definition must be in line with the business flow e.g. the Good Bad definition for the Early collections will differ for accounts < 90 Dpd and those >= 90 Dpd for the midstage collections till cancellation. Similarly, based on the different variables for Financing and Leasing and for Private and Business customers, there will be a need of separate scorecards. This calls for altogether 4 scorecards each for Financing and Leasing as:

Financing

< 90 Dpd Scorecards:

  1. Private Individuals
  2. Business / Companies

>= 90 Dpd Scorecards:

  1. Private Individuals
  2. Business/ Companies

Similarly, the Leasing Portfolio can have 4 scorecards to covering both the business segments.

As the accounts grow from Midstage, they are ultimately cancelled and reach the Repossession stage. It is a phase, where the critical decisions to repossess the vehicle are taken. Delay in the decision can lead to further depreciation of the vehicle with every passing day. Therefore Cost Benefits analysis plays a significant role in the scorecards at this stage to assess, if the accounts need to be prioritized for an internal or external treatment. The repossession of the cars has to be prioritized based on Balance at Risk for new high value cars followed by old cars. Therefore the one segmentation level can be reduced by consolidating the portfolios to have two scorecard one each for Financing and Leasing. E.g. Financing (Private and Business) and Leasing (Private and Business) can be two scorecards covering the portfolio for repossession.

Legal collections come into play after the repossessed vehicle is priced and sold to recover the outstanding balance. The amount received after selling the vehicle is adjusted with the outstanding balance. Any positive balance left after the adjustment is due for recovery. The scorecard at this stage should be able to predict the success of a legal process. Litigation is a slow and costly process therefore it needs good analytical base especially to set up a minimum threshold for the outstanding balance to qualify for the litigation process. All other accounts with lower chances of success through litigation are written off and should be allocated to the Late stage recovery either In-house or to external DCAs (Debt Collection agencies). This stage can follow the same model as for repossession.

Recovery process is the last phase of the collections process. This can be either done In-house or externally by allocating the cases to the DCAs. The scorecards can here add value by predicting based on cost benefits analysis, if the accounts need further resources to be invested or in order to save the costs the accounts can be offered final settlements. Recovery can also have the scoring model same as legal collections as the decision is largely based on the cost benefits analysis.


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