In addition, the COVID-19 pandemic tested the financial resilience of businesses and individuals across the region. Supply chain disruptions impacted operations and businesses were concerned about how to reduce bad debt after closing their books. The slowdown of economic activity has caused many to struggle or fail in meeting financial obligations, adding to the collections and recovery challenges of banks, fintech companies, and other lending institutions.
Fortunately, with data insights, advanced analytics, and modelling, lenders are able to identify patterns and trends to optimise their collections process, significantly improve their recovery rates, and provide a better customer experience throughout the collections journey.
Experian’s Advanced Analytics and Modelling capabilities help banks and lenders to make data-driven decisions and harness artificial intelligence (AI) and machine learning approaches. For instance, Experian’s Collections Analytics, helps our clients to determine the right collections strategy to reduce cost and enhance the customer experience.
Benefits of collections and recovery scorecards
In a case study where Experian developed an early stage collections model, the recovery rate (in percentage) for the company increased in the two-digit level, while improving customer retention and customer service. In another instance, Experian helped in scorecard development and implementation, leading to a reduction in non-performing loans (NPL) and “final” payment request letters sent.
This shows that incorporating collections and recovery scorecards into your strategy can benefit the business in more ways than one.
Utilising collections scorecards can help you identify clients who miss a payment for reasons unrelated to financial troubles, such as they were on holiday, as opposed to habitual defaulters. Proper segmentation of customers based on their collection scores can help companies better tailor their approach and ensure a good customer experience throughout the collections journey.
By determining actions based on customers’ risk profiles and behaviour, the company can balance their limited resources in favour of those who may need more contact or support to get their accounts up to date. Customers also feel that they are being treated fairly, especially those who require less interaction and have a good payment record.
Recovery scorecards, on the other hand, apply to the last stage of collections or loans that have gone 90 days past due. It allows companies to weigh the cost of recovery while optimising their resources in the process.
Scorecards enable lenders to take a proactive approach to collections and recovery. Through models, lenders can predict a customer’s propensity to pay, as well as the future likelihood that they will experience financial difficulties. By using platform-agnostic solutions like Experian’s analytics services, our client’s in-house collections teams can level up their skills and companies can ensure business continuity and knowledge retention and transfer.
Leveraging the power of advanced analytics
Leveraging advanced analytics and machine learning, can help businesses to automate repetitive tasks, thereby freeing up collections agents to focus on more complex cases. Machine learning can be used in model development to identify potential defaulters and predict credit risk. This can help businesses save time and money, while also improving their collections rate.
In addition, using analytics can uncover valuable insights about customer behaviour, allowing businesses to better target their collections efforts–for example, to determine the best timing and channels for collection.
Debt collection is a complex and often time-consuming process, but many businesses are now leveraging the power of data and advanced analytics to improve their collections process. It’s no wonder that it is quickly becoming an indispensable tool in the collections and recovery segment. Click to learn how Experian’s Advanced Analytics and Modelling capabilities Collections Analytics can transform your collections and recovery processes now.