It is essential to carry out debt collection so that an organization can attain financial robustness. Furthermore, the process should be done in such a way that it does not shift focus from the customer. More importantly, collection of debts helps retain customers. For instance, the Urban Institute and Encore Capital Group conducted a research that found that 35 percent of Americans usually have debt that is being collected (this is a large percentage). It is for this reason that more technologies have been developed to implement debt collection.
This process was done manually in the past but currently technological advancement has automated the process or rather made it similar to a self-service portal. It is important to note that payment follow up, skip tracing and phone calls are among the most popular processes which have been automated.
Decision automation has been implemented in the debt collection process; it entails teaching the machines to act, plan and think like agents that handle debt collection. Significantly, data science is normally applied so that models based on debt collection history can be built. The models are later used to teach machines how to close pending collections, follow up and interact with debtors. Some of the channels that are used include SMS, chat, and email. This is because they are private and offer absolute discretion.
Mobile phones assist in reaching debtors irrespective of the time or place. It is considered as the most effective ways of communication especially when it comes to field collections. Discretion is also observed when mobile phones are used in debt collection. This trend has proven to be effective according to a FICO report which reveals that B2C communications maximize on retaining interactions amongst debtors or consumers. The trend shows a positive sign which means it will be easier to monitor debts and carry out debt collections through this technology.
Payment apps have also been introduced and have been implemented through the mobile phones. Debt collection mobile applications such as Debt Collector and IOU are popular and effectively prevent fraud cases. The debt collection apps offer transparency which is important when it comes to debt collection.
Big Data Analytics
This assists in accessing data and personalizes debt collection. This form of technology has helped personalize the follow up actions. Bid Data Analytics attain more pertinent information about the debtor. This includes simple information such as demographic data or the behavioral aspects such as time of day that the debtor could respond to the call. Such information assists in the finding an approach the debt collection process can adopt.
Big data makes it possible to segregate and attain data with increased focus on a single debtor. Such an advantage can open up new possibilities like speech analytics with regards to debt collection related calls. Speech analytics increase the percentage of personal calls and save money on operational efficiency and training.
Tera Collect from NLS Banking Solutions is designed to create, follow, report and close pending debt collections through the consolidated Debt Collector. The module provides a comprehensive overview of debt management process thereby saving valuable time and reducing operational risk by offering relevant information in one central system.
From this centralized position, the user can easily manage a broad range of debt management activities. The solution further provides a broad range of tools and features and easily integrates with existing systems due to its service oriented foundation