SCORE Blog

We’ve spoken about Big Data, AI and machine learning and its application in the collections and recovery process. While it sounds futuristic, it’s technology that’s right here, right now, and it simply must be incorporated into any debt collections strategy to ensure the best possible results. At SCORE, we believe that data modeling, risk-based pricing and analytics give our clients the edge, allowing them to maximize their accounts receivables management. It’s why Canada’s top banks and 80% of major collections agencies in Canada use SCORE models to manage accounts receivables. We’ve put together three of our top tips to help you strengthen and improve your debt recovery strategies to reduce costs, save time and maximize resources.  

 

With advanced modelling and analytics, improving collections efforts to maximize accounts receivables becomes that much easier. However, you need to be able to interpret the data.  SCORE’s advanced scoring and segmentation tools give you complete portfolio intelligence, enabling you to make informed decisions. Our ongoing portfolio management and consulting services allow you to improve debt recovery strategies too.

 

By taking into consideration a broader array of input data, the accuracy of predictions constantly improves. SCORE’s predictive analytics allocate a collection risk score to every customer, then use this score to prioritize collections and methods of engagement. These solutions can identify changes in customer’s payment behaviour that can lead to a higher collection risk such as when a client is struggling, or flags variations in payment schedules.

 

Selective scoring is another solution SCORE has designed for larger portfolios. It is a cost effective and easily integrated tool that can be customized according to the specific scoring model (30, 90, 180- or 360-days delinquent). The portfolio is divided into segments according to probability of recovery, and users can score the portion of a portfolio that is above, below or within a pre-set score range.

 

By ranking and segmenting accounts into low, medium and high risk, debt collection agencies can be targeted with accounts that they have been successful at collecting in the past. This allows improved results, recoveries, commission dollars, liquidation rates, yields per account and commission dollars for each segment, while netback also increases as a result.   

 

 

Collections efforts should be focused on customers that are the most likely to pay. By predicting which accounts are most likely to cure or collect, you can target the most profitable accounts first.  SCORE’s models allow statistical analysis of a company’s historical accounts receivables data, as well the analysis of external sources to determine collection risk – the probability that it will become past-due at some point in the future. Utilizing credit bureau data, SCORE’s models help organizations manage risk by predicting which accounts at various stages of delinquency will cure or demonstrate high probability of payment. Once these accounts are determined, we can recommend cost-effective collection strategies to reduce the number of contact attempts. An in-depth analysis can also identify the method of contact or message that would influence the client the most. By targeting the right people, in the right way and at the right time, recovery rates will increase.

 

Of course, for many organizations, outsourcing collections might be the best strategy. SCORE offers consultation to improve your collections and recoveries, helping you manage activities from charge-off portfolios through to the entire back-end process.