DATA PROTECTION NOTICE
Version : April 2025
Download the PDF file SummaryVersion : April 2025
Download the PDF file SummaryWe carry out various types of profiling, the characteristics of which are described below. Some or all of this profiling may be carried out in a fully automated manner, in accordance with article 2.7.
1. Modelling and implementation of scoring rules for marketing purposes
The modelling of scoring rules for marketing purposes enables FLOA to find out its customers' and prospects' appetite for a product or service and their preferences, in particular as regards the communication channel used. FLOA can thus adapt its offer (product or service proposed and characteristics of the offer) and the frequency of contact.
The data taken into account for the determination of score models may be all the data concerning You, whether collected directly or indirectly.
We select certain fields that are useful for modelling scoring rules for marketing purposes, which can be correlated with one or more others and then associated with a weighting.
Score rules modelled in this way can be used to :
FLOA may thus adapt its offers (products or services proposed and characteristics of the offers), the rhythm and the channel of communication in order to respect the choices of its customers and prospects, provide them with quality information and services, adapted to their needs, and improve their satisfaction.
This purpose may have the effect of excluding certain persons from marketing campaigns and/or certain communication channels.
2. Modelling and implementing scoring rules for granting and collection purposes
The modelling of scoring rules for granting and collection purposes enables FLOA to control credit risk (in the case of prospects) and non-payment risk (in the case of customers).
The data taken into account for the determination of score models may be all data concerning You, whether collected directly or indirectly.
We select certain fields that are useful for modelling scoring rules for granting and collection purposes, which can then be correlated with one or more others and associated with a weighting.
Score rules modelled in this way can be used to calculate the credit risk (in the case of prospects) and non-payment risk (in the case of customers), enabling the person concerned to :
This purpose may have the effect of excluding certain people from taking out a loan (refusal to grant), leading to a change in the maximum loan amount or generating the proposal of a product more suited to the borrowing capacity of the person concerned.
3. Modelling and implementing scoring rules to combat fraud
Modelling score rules to combat fraud enables FLOA to identify signals that may help detect fraud, such as the technical and behavioural environments conducive to the action of a potential fraudster.
The data taken into account for the determination of score models can be any data concerning You, whether collected directly or indirectly.
We select certain fields that are useful for modelling score rules to combat fraud, which can then be correlated with one or more others and associated with a weighting.
The implementation of score rules modelled in this way enables FLOA to :
This may result in the exclusion of certain individuals from taking out a loan (refusal to grant), the termination of current contractual relations or the initiation of amicable or legal proceedings.