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Collection intelligence, a reality closer to everyone
For a long time now, companies have been looking to improve the process of granting credit in order to reduce the default. Thus, this process, which used to boil down to a phone call to ask for business references, now involves the use of data in powerful statistical models that help companies define and calibrate the best credit approval policies.
However, no matter how well-structured a credit process is, default can always occur. Various situations can interfere with a person or organization's ability to pay their financial commitments, and this non-payment needs to be dealt with in order to avoid an impact on the company's cash flow. creditor. It is at this point that the Collections area shows its importance.
Within the financial structure, the Collections area, often also referred to as Recovery of Credit, This is why a lot of investment has been made in tools and means of activation. For this reason, a great deal has been invested in tools, drive means and analytics for billing. The latter is essential for any strategy to achieve better performance. To put it in context, here are some basic concepts what analytics are and their applications.
Collection analytics are statistical models which support and add intelligence to the recovery process, are built on advanced modeling techniques, machine learning, behavioral patterns or any other technique that allows you to identify customers who really have a chance of paying off their debts.
To do this, these models combine variables that make up credit bureaus' databases, such as positive, negative, cadastral and behavioral information, and generate, by means of a classification, metrics that help the creditor to better assess the recovery potential of a given debtor.
In this context, discharge probability solutions can be applied to debts, These include the amount that fits in the creditor's pocket and the time it takes to pay off, among others.
The use of analytics sheds light on the debtor portfolio, allowing the collection manager to create different actions according to different profiles. After all, considering that people and companies have different characteristics, why should recovery actions have to be the same?
The value of statistical tools for the collection process is unquestionable and I would like to highlight two important points that need to be on the manager's agenda.
Budget optimization: the financial health of companies depends on the quality and rigor of the management of the business area. charging. And the basic concept followed by the collection manager is: without having received, I have to avoid spending even more on recovery. But the point here is to invest correctly, in analytics. When there is clarity about the profiles most likely to pay, there is optimization of investments and, in the case of the least likely profiles, going for a denial may be the best way to negotiate, since they will see their credit restricted. In traditional processes without the use of analytics, all debtors are contacted in the same way, following the same collection guidelines, greatly reducing effectiveness and not getting the best out of the investment made in collection.
Relationship preservation: A lot is invested in winning over customers and their experience, so every effort to maintain this relationship is important. In many cases, default is a one-off event. The customer is in default and if this is not taken into account in the collection processes, there will be wear and tear and the possible loss of this customer. Winning customers is more expensive than keeping them and, even if they are in default, they can still be kept and the relationship preserved. In situations like this, a powerful ally for both debtors and creditors is the credit score (score). It's likely that the note signals a customer profile that is more inclined to settle and to take a more lenient approach to collection, or even to extend the payment deadline. The fact is that in the race between collecting and maintaining the relationship, the collections manager has the challenge of maintaining both.
Every day, the benefits generated by analytics are approaching collections teams with affordable solutions, products and services. And, given the reality of lean teams, collection analytics, developed so that they are easy to interpret and implement, become even more strategic.
Fortunately, companies of any size and segment can now have them available, benefiting from the use of intelligence to make their billing area much more effective and productive.
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By: Elias Sfeir President of ANBC & Member of the Climate Council of the City of São Paulo & Certified Advisor
