Debt Collection Strategy For Retail Fianance

Strategy is a plan; Strategy is a pattern in actions over time; Strategy is a position; and Strategy is perspective, that is, vision and direction.

Strategy bridges the gap between policy and tactics.

Effective collection Strategy should have a comprehensive approach which encompasses:

Automating work flows: Automation of work flows through dedicated collection system would help classify, allocate, prioritize, and assign accounts and maintain flexibility to respond to changing circumstances. This is estimated to reduce delinquency by 1-2%.

Monitoring Resource Performance: Measurement of efficiency and effectiveness of collectors, supervisors, business unit is very important. Dash board approach is good; system should provide on-line performance to all stakeholders, continuously and consistently. System based and systematic monitoring for course correction is estimated to reduce delinquency by 1% and reduce collection costs by 4-5%.

Improving performance of Debt Collection Agency (DCA): It is important to get better results and accountability from DCA handing delinquent and recovery cases. Letting DCAs to use collection system on web and seeking accurate and daily contact and collection details help improve recovery and achieve high liquidation rate. Alternatively, it helps shifting of the cases to more effective agencies.

Reporting to Credit Bureau: Lenders will have to supply accurate delinquency data on each default customer to Credit Bureau. This brings discipline in few customers and results in payment in full ; and ensures future payments on time.

Capturing contact details digitally:  It appears very easy; but it is the most difficult activity in the Debt Life cycle. There are a lot of constraints and resistance to get contact details recorded systematically and daily. Some field collectors have retained most information on delinquent customers in their diaries and the notes go with them when they leave. Currently, contact history is very important to grade delinquent accounts systematically for different actioning.

Let us discuss tactics for each of the following category.

I High Delinquent – High Risk ( DPD > 89 & Delinquency rate > 66% )	II Low Delinquent – High Risk ( DPD < 90 & Delinquency rate > 66% )
III High Delinquent – Low Risk ( DPD > 89 & Delinquency rate < 67%)	IV Low Delinquent – Low Risk ( DPD < 90 & Delinquency rate < 67% )

Strategy for Quadrant IV – LDLR

These accounts may be allotted to desk collection; desk collection is responsible for tele-calling and written communication.

Soft collection letter may be sent after each cheque bounce or a missed payment.  Each letter must positively bring focus on possible loss of credit rating with credit bureau, pointing out the benefit of saving penalty, late payment charges/ fees, etc. apart.   80% of default accounts with DPD less than 31 will be cured with a simple letter. This includes self cure. (We will discuss the content and tone of different collection letters in future blogs).

Calling may be scheduled for accounts with DPD exceeding 30. A tele-caller can effectively and must call 50-60 accounts a day including ‘pop-up’ and ‘Promise-To-Pay’ cases. They may cure a minimum 70% of allotted cases; accordingly resources may be planned and provided for. The resources must be well trained to be effective to collect, but still relate. Being low delinquent, relationship with these customers are important and may be handled in a way relationship is not affected at all.

Strategy for Quadrant II – LDHR

These accounts will have to be allocated to field collection. These accounts should not be allotted to DCAs for collection, as highly reliable details on these customers are required for quick ‘grading’.  Collectors must meet these customers and record accurate contact details focusing on “Ability and/or Intention to pay”.

Collection tactic for each of the following metric is as follows:

High Ability – High Intention	Low Ability – High Intention
High Ability – Low Intention	Low Ability – Low Intention

High Ability – High Intentio               :           collect money

Low Ability – High Intention             :           seek and get surrender of the asset

High Ability – Low Intention             :           repossess the asset

Low Ability – Low Intention             :           charge off and/or sell the account

Strategy for Quadrant III – HDLR

These accounts may be considered for allocation to Debt Collection Agency (who is a good DCA?). Alternatively, it may be allocated to field collectors. Most likely, many accounts here will be high on intention and low on ability. Economics of these customers may have started deteriorating in the recent past. Collection should be possible and seeking the surrender of asset may be considered as next option. The interface with this customer will have to still be customer centric and communication both ways need to be managed better.

Strategy for Quadrant I – HDHR

These accounts are very Low on intentions. These must be allocated to the most experienced field collectors or collection supervisors. Best way to realize any collection from these accounts is by repossession and sale of asset. It is advised not to repossess assets which are in non-saleable condition.

Losses can be only minimized if the sale of repossessed asset is done urgently and through robust process. Many a time, the process is subject to judicial review, when suit is filed for recovery. So, it is advisable to keep the record of the process and documents in customer files without fail.

In many cases, there would be difficulty in repossessing the assets. In such cases where the ability is high, legal proceedings must start immediately without wasting any time.                                                                    

Be Tech Savvy In Finance Business

It is highly impossible to have a good control on any part of finance business without being a tech savvy company.

There are enough gadgets including mobiles and high speed connectivity to have every information and capture any activity very accurately on site and off site.

Top guy need not be a computer wizard or software engineer to run a finance company; he still necessarily needs to be an economist, marketer and financial wizard.

He must be open to the change and he may have to be interested to know what computers and new gadgets can do to mitigate risk and help him have a full operational control.

Whatever computer is capable, must be done through only computers. This drastically saves cost and helps control the business better. Of course, he must choose right software vendor, to really get better return on huge financial outlay upfront.

There was a company who had invested a huge money in collection module of a financial software – Finness. It was not implemented till the author joined the company as collection head.


With implementation, the following were achieved quickly:

• Centralized control on delinquency; accurate delinquency ratio and rates
• Automated work flow; segmentation was done through queing system
• Tele-calling could be started for Low risk - Low deliquent accounts
• Dunning; collection letters were sent out on time, through collection system
• Customer disputes are known
• Mitigated the risk of cash handling and misapplication
• Daily allocation and assignment of cases to field collectors
• Access to collection system, through inter and intra net
• Accounts of customers at the press of the button; foreclosure data available
• Efficiency and effectiveness could be measured, thanks to analytics.
• Customer Contact / interaction details and feedback were recorded.
• Promises To Pay were to made to pop up on PTP dates, for close follow up.

The company had moved to a position of having the lowest delinquency ratio of 6% on their car portfolio from around 12% ( In fact, the company had no accurate delinquency ratio as it depended on field delinquency data till implemenation of dedicated collection sysytem ) and more importantly, it was useful to maintain accurate customer accounts.

I am sure more advanced versions of many software are available currently to track default accounts from delinquency to collection to losses to legal proceedings to recovery.

Have one, because charge-offs need to be minimised.

Use Collection Analytics

Analytics

Analytics provides organizations with better visibility into the factors that drive revenues, costs, and shareholder value. Today’s business challenges demand timely financial information that enables executives, managers, and front-line employees to make better decisions, take action, and correct problems before they affect the company’s financial performance.

Analytics provide insight to the people who can impact business performance.

Collections + Analytics = Improved Recovery.

Collection Analytic is nothing but an intelligent analysis, using combination of mathematical and statistical tools, to arrive at a “behavioral scoring”, depicting accurate picture of the customer’s propensity and ability to pay, which is used to segment defaulters, prioritize collections activities to maximize recoveries and reduce collections costs.

Effective collection analytics empower the collection staff to focus on the right debtors, maximizing the payments collected by a combination of segmentation, scorecards, and strategies to help manage delinquent accounts better.

Collections Analytics segments and identifies accounts representing those that self-cure, those that cure with engagement, and those that will improve, remain stable, or grow more delinquent. Using Collections Analytics you can assign treatments and protocols to each of your segments depending on the account’s recovery score, outstanding balance, and balance age. This ensures collection teams are distinguishing well-intended, “accidental” debtors from those under economic hardship or potential cases of actual fraud. Strategies can be interfaces with client interaction further enhancing productivity by leveraging and optimizing investments in existing systems and providing a seamless integration to tools already being used to help collection teams.

Why collection analytic?

Because it increases amount of collection and more importantly reduces the losses by 1-2%. This translates into almost the existing profit of many well-run companies; will company not like to double its profit?

Predictive models

Predictive models analyze past performance to assess how likely a customer is to exhibit a specific behavior in the future in order to improve collection effectiveness. Many types of models are available and uniformly, all of them deduce the analysis to a scoring. A good scoring model requires varied data accurately and on timely manner.

Data is at the heart of everything.  With expertise in the interpretation and use of credit bureau, clients’ customer data and customer contact history, Analytics turns this data into information, which enables organizations to predict how defaulters will behave in the debt collections process.

Do Indian companies require them? Yes, banks and big finance companies certainly require. But, are they ready? One is not sure.

Very few banks and lenders have applications data, credit bureau data, credit scores, and collateral details electronically. Some do not have a dedicated debt management system. Migration or pulling data from one to another system creates its own set of problems.

This apart, hardly any bank or lender has captured and recorded customer contact/ interaction history systematically and digitally. Without this crucial information, no predictive model implemented will churn out any meaningful results. It would take a few years more, provided companies realize the value and importance of recording customer contact/ interaction history.

Predictive models are of no use to Indian banks and lenders, in near term.

Descriptive models

This may be appropriate for India. Descriptive models quantify relationships in data in a way that is often used to classify default customers into groups. In other pages, we have classified and grouped them under four groups/ quadrants:

I           High Delinquent        -           High Risk

II         High Delinquent         -           Low Risk

III        Low Delinquent         -           High Risk

IV        Low Delinquent         -           Low Risk

Additionally, we may use six sigma concept to further identify high risk accounts within the groups based on payment pattern falling outside six sigma (standard deviation). This would help rank-order the cases within the groups or in the collection lists.

We will discuss the level of effort, type of effort, timing of effort and the right strategy for each the above groups in future blogs.

Classify To Bring Focus

Delinquencies need to be classified appropriately to bring the right focus. Different institutions use different type of delinquency/ collection reports. Each has its advantage and disadvantages.

Some foreign banks use collection reports based on ‘exposure given default’ – EGD. This gives a list in descending order of exposure. Here, the focus is on accounts with high exposure. Obviously, they do not want loss per account to be huge. Here, classification does not reflect neither level of delinquency or level of risk.

Some NBFCs use collection reports based on ‘past due amount’. This gives a list in descending order of default amount or past due amount. There is no clarity on delinquency and risk levels.

Most MNC lenders use collection reports based ‘days past due’ – DPD. This gives a list in descending order of number of days accounts in default. One can get ‘months past due’ by dividing DPD by 30. Months past due gives number of installments overdue.  Similarly, many credit card lenders use ‘buckets’ generally representing different months past due, say first bucket to mean account with past due from 1-30 days. This certainly indicates the level of delinquency and not fully the level of risk. Yes, default accounts with high DPD tend to be high risk; it gets increasingly difficult to collect with an increase in DPD.

Then, how do we measure risk, delinquency level and classify them broadly based on delinquency and risk, to bring the right focus by allocating and assigning resources to mitigate losses?

It is important to have accounts classified in the following matrix.

I High Delinquency - High Risk	III Low Delinquency - High Risk
II High Delinquency - Low Risk	IV Low Delinquency - Low Risk

Collection reports rak ordered by delinquency rate would help classify, based on risk.

Delinquency rate is, as defined elsewhere in my blogs, the rate of amount past due as compared to amount billed so far for the contract.

Top 20% of accounts on the list are certainly high risk accounts; balance can be classified as low risk accounts. These can be further classified based on DPD. Accounts with DPD higher than 90 may be classified as high delinquent and remaining low delinquent.

Now, we have 4 quadrants which constitute Debt Lifecycle as follows:

I        High delinquent – High risk

II       High delinquent – Low risk

III      Low delinquent -  High risk

IV      Low delinquent – Low risk

It is clear that the focus needs to be on high risk accounts and more on Quadrant I accounts which are High delinquent – High risk. Different quadrants require different levels of curing like calling, field visits, repossession, agency collection, legal actions, etc.

Try them; you will see results. Losses will come down.

Collection analytic will help further classify to bring razor sharp focus; I will write on collection analytics on different pages in near future.