Since you have the Python tag, the following example is how you would accomplish this task using raster algebra in Python.  Here I am assuming you have a variety of rasters in one GDB with a unique ID for each pair.  The output is written to a separate folder in .tif format.

    import arcpy, os
    from arcpy.sa import *
    arcpy.CheckOutExtension ("Spatial")
    
    arcpy.env.workspace = r'C:\temp\temp.gdb'
    inws  = arcpy.env.workspace
    outws = r'C:\temp\out'
    
    # List all of the "forestmask" rasters
    rasters = arcpy.ListRasters("*forestmask*")
    
    # 1) Assuming there is a "loss" counterpart with a unique ID
    # 2) Loop through your raster list
    for r in rasters:
        # Extract prefix and suffix for naming purposes later
        prefix = r.split("_")[0] + "_"  # Get just the prefix
        suffix = "_" + r.split("_")[2] + "_" + r.split("_")[3] # Get just the suffix
    
        # Define the "forestmask" and "loss" paths
        forestmask = os.path.join(inws, r)
        loss       = os.path.join(inws, r.replace("forestmask", "loss")) # Replace "forestmask" with "loss"
    
        # Convert these to raster objects
        r1 = Raster(forestmask)
        r2 = Raster(loss)
    
        # perform the raster algebra
        mycalc = r1 * r2
    
        # Save to disk (write to .tif)
        mycalc.save(os.path.join(outws, prefix + "deforestation" + suffix + ".tif"))
    
    arcpy.CheckInExtension ("Spatial")