Collections in Next Best Action Designer

The Taxonomy tab of the Next-Best-Action Designer allows you to define the business structure of your organization. Within that structure, Issues define the purpose behind the actions or reminders that you can offer to the customers. Within a business issue, Groups organize customer actions into categories.

The following figure highlights the Collections Issue and the associated Groups on the Taxonomy tab of the Next-Best-Action Designer:

The frequency and channels through which you can contact customers in collections are highly regulated. You use the Constraints tab of the Next-Best-Action Designer to specify outbound limits, to ensure that you remain compliant with regulations on limits. Additionally, you can use the Contact policy library to define suppression rules that automatically put an action on hold after you reach a specified number of outcomes. In this way, you prevent the customer from being over-exposed to the same collections reminder. The library also helps with re-use of contact policies that have a history of producing desirable outcomes throughout the organization.

The following figure highlights an outbound limit of one email sent every 7 days, defined on the Constraints tab of the Next-Best-Action Designer:

In Pega Collections, engagement policies are used to identify customers based on their level of default. For each business group you can configure a specific set of reminders to engage with the subset of customers in the most effective way. You also use Engagement polices to calculate the repayment plan options that are best suited to a given customer. This self-service option empowers customers to set up a pre-approved plan that meets their individual needs.

The following figure highlights the reminders configured for the Days Past Due 30 Collections group:

Use the Arbitration tab of the Next-Best-Action Designer to configure how customer actions and reminders are prioritized. On the tab, Propensity represents the action's likelihood of getting a positive response from the customer. Use this AI-calculated value to choose the right channel, action, and treatment to always deliver the most optimal message to the customer. You then use Context weighting to assign a value to real-time contextual data.

Business Value enables you to assign a financial value to an action and prioritize high-value actions over low-value ones. For example, promoting an unlimited data plan might be more profitable for the company than a limited data plan. Action values are typically normalized across Issues and Groups.

The following figure shows the arbitration tab of the Next-Best-Action Designer:

Collections customers are five times more likely to engage through digital channels as opposed to letters or phone calls. In Pega Collections, CDH determines the right channel and proposes the most optimal customer resolution.

As you can see in the following figure, Call center is just one of the available channels that taps in to CDH to find the next best action to take with relation to a given customer: