Detection of significant changes

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Imagine, for example, that a customer has a stable payment pattern for some months and, in others, a reduction in financial transactions.

With this information, the bank can offer credit alternatives that are compatible with this behavior, making the financial relationship healthier and minimizing the risk of default.


Additionally, time series are useful in quickly detecting significant netherlands mobile database in financial behavior . That is, sudden changes in income or unexpected increases in expenses can be quickly identified through continuous data analysis.

This capability allows financial institutions to respond proactively, reducing the risk of default or identifying opportunities to expand the supply of credit.

For example, if a regular customer begins to show a sharp drop in income over a specific period, the creditor may choose to review the terms of the credit or offer alternative solutions before the situation worsens.