Artificial Intelligence: a key tool for recovering debt

New technological tools can help optimise portfolio management and debt recovery
GDS Modellica’s technological and analytical solutions enable companies to automate decisions, increase customer loyalty and predict risk behaviours
An increasing number of financial companies and organisations are turning to innovations like automation, predictive technology, advanced analytics and artificial intelligence (AI) to recover unpaid debt or more effectively manage collections processes. In an increasingly competitive global market, smart, targeted collection strategies are key for maintaining customer loyalty, reducing risk behaviours, recovering collection portfolios and reducing late payments or defaults.
According to GDS Modellica, every customer is unique, and every interaction is an opportunity to build a stronger relationship with them. Customers are sensitive to how, when and why they are contacted, and whilst call centres are an effective method, they’re also the most expensive. As a result, many companies are looking to alternative communication methods, and automation via mobile and digital channels is one such option for reaching consumers and providing them with viable solutions.
With the arrival of AI, the humanisation of interfaces and communications have become key for debt recovery processes. GDS Modellica has developed various technologies which get the most out of advanced analytical technologies like AI or Machine Learning through a PMML format or other R or Python-based models. AI is capable of analysing big data, identifying patterns and trends and automatically formulating predictions, all with speed and precision. As a result, AI can enable smarter day-to-day communications with the customer by using predictive analysis and other techniques in applications that are used every day
The data that companies possess is key. If properly developed and analysed using algorithms, this information can allow businesses to establish behaviour patterns which can be highly valuable for automated decision-making and resolving everyday business problems. Using the available data, it is possible to prioritise and apply different collection strategies based on timescales and the amount owed. Predictive models can be used to complement other technologies like chatbots and virtual assistants to automate and accelerate collection processes, adapting solutions to each individual and thereby increasing the likelihood of recovering the debt.
GDS Modellica offers the Modellica Collection Suite to help companies increase their revenue by using data analysis to automate and streamline their collections processes. It allows companies to precisely segment debtor accounts and get a comprehensive view of customer information. Then, it makes it possible to strategically manage interventions in order to increase debt recovery, guide collection activity, automate decisions and increase customer loyalty with higher-quality interactions. Companies that adopt these solutions immediately see the benets, with more effective management of all processes, leading to a lower rate of late payments and providing a clear advantage over the competition.
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