Abstract: Systems and methods are provided for providing targeted messaging to a user of a user device without requiring transmittal of personal information from the user device. The user device employs one or more machine learning models to obtain analytic data that reflects the demographics of the user from personal information. This analytic data is then provided to a central server without transmission of the personal information. The central server uses the analytic data to obtain messaging from one or more third party providers that is targeted to the user of the user device, which is provided to the user device for display to the user. Other embodiments may be described and/or claimed.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: A method of income validation and evaluation for income risk assessment is disclosed in one embodiment. The method includes receiving a borrower loan request including a plurality of borrower data selected from the group consisting of: an employment type code, a borrower date-of-birth, a borrower zip code and a stated monthly income.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.