In this fitful scenario, technology and the development of solutions through applied software have their reason for being to improve the
global process, thus reducing the default rate and increasing the debt collected. This
better-integrated management of human resources and the costs associated with debt collection procedures was possible thanks to new data processing and automation tools that facilitate, among other things, the analysis and segmentation of customer data, as well as the identification and classification of debtors according to their probability of paying. Good segmentation dramatically facilitates management and intelligent decision-making.
In the case of the debt collection process, it helps to:
- Perform better analysis of both debtors and risks
- Make better decisions
- Mitigate risks
- Ensure a better return on investment in debt collection regarding time and cost.
To boost their profitability and growth, entities and firms must automate and optimise their operational decisions in order to leverage customer business value by responding effectively to markets and increasing business risks.
The Decision Management Architecture platform developed by
GDS Modellica provides a comprehensive rapid decision development environment for customers to customise, evaluate, implement and scale decision-making technology in a truly effective manner. Its extensive evaluation and segmentation capabilities enable companies to manage and automate operational decisions with high performance across processes, systems and channels, whether on-premise or in the cloud.
Antonio García Rouco, CEO of
GDS Modellica, describes our decision-making process as follows: It performs
calculations and executes formulas and models according to the variables determined to make safe decisions. Moreover, it applies to multiple products. The bank itself draws its own risk strategy and implements the decision-making process through tools and internal architecture.” In this sense, says García Rouco: “Organisations are adopting
decision management technology
because they need a higher return on investment in infrastructure, due to the increased complexity of business decisions, competitive pressure for more sophisticated decisions and ever-shrinking gaps in competitive advantage. Companies must improve the value created through each decision by deploying analytics solutions that better manage the trade-offs between accuracy, consistency, agility, speed and cost of decision making“.