Systems and methods for property damage restoration predictions based upon processed digital images

A non-transitory computer-readable medium, comprising instructions that, when executed by a data processing apparatus, cause the data processing apparatus to perform the steps of:

• receiving, from a client device, a property damage restoration estimate request comprising a first set of one or more digital image files and device metadata, wherein a digital image file of the first set of one or more digital image files comprises a facial image and a plurality of pixels of a first digital image of one or more of a physical piece of property;
• retrieving, from a repository and based at least in part on the device metadata, policy data associated with a user of the client device, the policy data comprising user identification properties including a policy holder facial image file and policy properties;
• comparing the facial image to the retrieved policy holder facial image file;
• determining a likelihood that at least one of the first set of one or more digital image files was fraudulently altered by generating a first predictive value, wherein generating the first predictive value comprises:
• extracting each pixel of a plurality of pixels of each digital image file of the one or more digital files;
• generating, for each digital image file, a multi-dimensional matrix comprising the plurality of pixels;
• identifying, by evaluating each pixel based at least in part on a first machine learning model, any of the plurality of pixels or any groupings of pixels of the digital image file that have been manually or programmatically altered;
• and
• generating the first predictive value based on the comparison and the identifying of any of the plurality of pixels or any groupings of the digital image file that have been manually or programmatically altered;
• determining that the first predictive value does not exceed a fraud threshold;
• generating, based at least in part on the first set of one or more digital image files and the retrieved policy data, a property damage restoration estimate;
• and
• transmitting a property damage restoration estimate response comprising the property damage restoration estimate to the client device.

A computer-implemented method, comprising:

• receiving, from a client device and by at least one processor, a property damage restoration estimate request comprising a first set of one or more digital image files and device metadata, wherein a digital image file of the first set of one or more digital image files comprises a facial image and a plurality of pixels of a first digital image of one or more of a physical piece of property;
• retrieving, from a repository and by the at least one processor, based at least in part on the device metadata, policy data associated with a user of the client device, the policy data comprising user identification properties including a policy holder facial image file and policy properties;
• comparing, by the at least one processor, the facial image to the retrieved policy holder facial image file;
• determining, by the at least one processor, a likelihood that at least one of the first set of one or more digital image files was fraudulently altered by generating, by the at least one processor, a first predictive value, wherein generating the first predictive value comprises:
• extracting each pixel of a plurality of pixels of each digital image file of the one or more digital files;
• generating, for each digital image file, a multi-dimensional matrix comprising the plurality of pixels;
• identifying, by evaluating each pixel based at least in part on a first machine learning model, any of the plurality of pixels or any groupings of pixels of the digital image file that have been manually or programmatically altered;
• and
• generating, by the at least one processor, the first predictive value based on the comparison and the identifying of any of the plurality of pixels or any groupings of the digital image file that have been manually or programmatically altered;
• determining, by the at least one processor, that the first predictive value does not exceed a fraud threshold;
• generating, by the at least one processor and based at least in part on the first set of one or more digital image files and the retrieved policy data, a property damage restoration estimate;
• and
• transmitting, by the at least one processor, a property damage restoration estimate response comprising the property damage restoration estimate to the client device.