Mr. Wong Kang Hing
Chief Executive Officer & Director of Asia Credit Monitors (Holdings) Ltd.
Asia Credit Monitors: Debt collection made smarter and more effective with data analytics
When an individual gets too far behind and is unable to make payments on time, debt collection comes in as a tool that is employed at multiple levels of recovery to keep the credit flowing.
Though debt collection is a complex and diverse issue, it has nowadays increasingly become a game of efficient operations backed by solid analytics. Asia Credit Monitors, one of the pioneer credit management providers which perform account receivables management in Hong Kong and Asia, is also committed to deploying data analytics for approaching those debtors with a higher repayment propensity, increasing the success rate of debt collection from an operational perspective, and, in the long run, improving overall business efficiency.
SAS arms us with a more scientific approach, rather than relying primarily on the experience of people in order to determine payment behavior and the likelihood that money owed can be collected from debtors.
Mr. Wong Kang Hing
Prior to the deployment of SAS solutions, Asia Credit Monitors had encountered several key difficulties which were affecting its business performance. The biggest challenge was the scattered distribution of the data available and the inability to analyze this thoroughly. On top of this, it had difficulty in prioritizing the different cases of debt collection as this sort of ranking mainly relied on domain knowledge and past experience, often resulting in misallocation of resources.
After evaluation, Asia Credit Monitors implemented a project in close collaboration with SAS Hong Kong. By utilizing SAS’s tailor-made and packaged solutions for the company’s debt business to build a data model, it has successfully enhanced its operational efficiency.
Mr. Wong Kang Hing, Chief Executive Officer & Director of Asia Credit Monitors (Holdings) Ltd., says, “The implementation of this project took just three months and we are very pleased with the results. SAS has truly demonstrated its superior technology capabilities and its professional domain knowledge in incorporating analytics into our business. We have developed SAS models to support the entire debt collection lifecycle, which enables us to take a holistic view of debtors. For example, the descriptive and predictive modeling in SAS Enterprise Miner provides insights that drive better decision making, and SAS Visual Analytics also helps us explore all relevant data visually in a smart, quick and easy way.”
Mr. Wong is delighted with the outcome of the implementation of this project. “SAS is strong at data analytics and is a recognized market leader in advanced analytics and business intelligence. SAS arms us with a more scientific approach, rather than relying primarily on the experience of people in order to determine payment behavior and the likelihood that money owed can be collected from debtors. We believe that deploying SAS analytics solutions makes the process of debt collection smarter and more effective in this data-driven business world.”
- Unable to analyze the scattered distribution of data
- Difficult to prioritize the different cases of debt collection as it relies on people’s experience to determine the likelihood of successful collection, resulting in misallocation of resources
- SAS models support the entire debt collection lifecycle to give a holistic view of debtors
- Allow users to explore all relevant data visually in a smart, quick and easy way
- Deploy a more scientific approach to improve the process of debt collection