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Solutions for Finance

Mobile Scoring

We convert mobile data into scores and analytics, enhancing financial industry processes and decision-making.

Companies that trust us

Data-Powered Decisions

Risk Score

Our score enhances the risk assessment associated with the origination of credit financial services.

Other Scores

For the evaluation of users throughout the credit products and services lifecycle.

Data Model Enrichment

Our data strengthen existing predictive models and improve performance in segments with little or no traditional information.

What Data do we use?

We have access to data from more than 104 million mobile users in Mexico, reaching more than 77% of the prepaid base (users from 2 of the most important mobile operators in Mexico).
Useful for interpreting the payment scheme and discipline of a mobile number.
Useful to identify the type of contracted services, plans and their usage.
Useful in designing a profile and the level of sophistication of the users.
Useful to know the behavior and mobile use of users.
Useful to know the technological social connection of users.

Risk Score

Improved predictive power, tailored performance metrics, enhanced monitoring, and better long-term cost/benefit. Custom risk scores enhance financial services evaluation.
Classifies banked and unbanked users or those with little traditional credit information. (No-hits and thin-files).
Allows for updating and monitoring the status of the portfolio and identifying trends to increase and keep it healthy.

Other Scores

Customized solutions to improve different use cases in the credit lifecycle.
General purpose score that offers a pre-trained method of mobile number evaluation. It allows enrichment of onboarding processes.
Score that improves the contact rate, optimizing operating costs and identifying the best contact channels.
Classification and evaluation of suspicious payment transactions in real time.
Personalized score that predicts specific behaviors associated with abuse and fraud.

Data Model Enrichment

Enhancing models with new variables improves performance where data is scarce. Validating identity and risk at origination, detecting risk-related behavioral changes, and identifying up-selling opportunities.

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