Data management in traditional collections processes is time consuming. Teams need to procure information from different sources (specific departments, third parties, storage locations) and then perform manual analysis to inform their engagement with each customer. Even though utilizing this data is vital in determining treatment paths that lead to resolving debt, this manual process quickly becomes arduous and unscalable as business grows.
Data-driven processes eliminate the need for all of the manual intervention happening during a traditional process. Instead, data-driven processes inform decisions via a thorough and reliable foundation of customer information, utilizing AI-powered tools to bring layers of efficiency. Not only do they save you and your team time and money, but they also provide visibility of better treatment paths for individual accounts, customer vulnerability and enable multiple self-service opportunities.
What are the features of a data-driven collections operation?
Analytical models and machine learning
Data-driven processes are built on a strong foundation of customer analytics. Key characteristics such as outstanding balance, account lifetime and number of missed payments are compared to historical data to determine the likelihood that each individual customer is likely to resolve their debt. From this risk profile, a configurable collections platform that utilizes machine learning (ML) can segment customers based on their likelihood to pay, and determine suitable treatment paths based on your own workflows. This data-driven process brings a range of efficiencies to account management, while also improving the likelihood of individual customers gaining financial health.
Centralized data as a Single Source of Truth
From the beginning to the end of a customer journey, there is a wide range of important data that determines engagement methods and identifies an appropriate treatment path. You need to know what contact channels they have consented to, what payment offers they have received, and their full account history. By utilizing centralized data-driven processes, you will have a Single Source of Truth (SSoT) with easy access to all the necessary account information. Additionally, a configurable platform with access to this SSoT can automatically record each customer interaction and call-back to them when needed, optimizing data management and minimizing operational risk.
Automation and self-service
A significant number of accounts in collections, and especially those that have recently entered for the first time, can resolve their debt with a simple payment offer or plan. These are customers that have a low risk profile, and an SMS or email with an offer appropriate to their situation is often enough to reach a resolution. Data-driven processes provide automation opportunities for these accounts through both ML and centralized data. You can upload pre-determined workflows that are then interpreted by a configurable collections platform to automatically contact customers with applicable payment offers. Additional features such as chat-bots can also be utilized to further provide self-service opportunities to customers that do not need a phone call. Not only does this save time for you and your team, but it provides you with greater capacity to focus on customers that need human guidance to reach financial health; an improved customer experience for everyone.
Debt Manager - a data-driven collections platform that benefits customers and businesses
It is clear that a configurable debt collections platform lies at the heart of a data-driven collection operation. In order to utilize machine learning, SSoT and automation, you need a holistic system that ties everything together. C&R Software’s industry leading Debt Manager achieves just that, proven by the success of our client Williams & Fudge.
Williams & Fudge are an industry leading collections agency specializing in higher education, with a wide customer base that spans multiple states and industries. Because of this, they needed a configurable platform to comply with inter-state standards without risking customer treatment as a result.
After using Debt Manager as their collections platform, Williams & Fudge utilized data-driven processes to automate compliance factors, effectively value customer claims and ensure a humanized approach at each stage of the customer journey.
To find out how Debt Manager can bring configurability, efficiency and optimization to your collection operation with data-driven processes, contact a member of our team today.
