Annex I
Information on merchant risk analysis
| Data categories used or to be used in the development of these models | Data provided directly by the client (merchant), as well as data obtained from external sources, such as public records (for example, Commercial Registry, Tax Agency) and other information sources, including social media or internet searches. This data includes, among others, business description, legal address, credit history, commercial references, and any other information relevant to the analysis. |
| Why these categories are considered relevant | The type of data used allows for a complete and accurate assessment of the risks associated with the client. This data is fundamental to determine the financial and reputational profile of the business, which in turn helps to develop a scoring-based valuation model. This analysis aims to ensure the financial viability of the commercial relationship and prevent possible economic or reputational damage to MONEI. |
| How the models are developed | The models are developed by evaluating the merchant category through scoring systems that assign a numerical rating, generally on a scale of 0 to 100. These models may include automated analysis processes. |
| Why this model is relevant for automated decision-making | The relevance of this model lies in its ability to provide an objective, uniform, and efficient assessment of the risks associated with each client. The internal scoring models allow for reliable, fast, and data-based rating, minimizing subjectivity and optimizing the decision-making process. |
| Expected consequences of this processing | The processing of this data and the development of scoring models allow MONEI to evaluate the client's financial capacity and suitability. As a result of the analysis, an assessment is generated which, after review by the delegated body, leads to one of the following decisions:
This process ensures that decisions are based on rigorous and fair analysis, aligning with MONEI's objectives and current regulations. |
