Standard indicators of physical exposure from floods capture only a portion of the probability distribution of potential flood events, in terms of return periods as well as populations and property at risk of inundation and in follow-on assessments are combined with data on economic activity at relatively coarse geographic scales to derive losses, with the potential for aggregation bias. We conduct a comprehensive flood risk assessment at the individual property level on the distribution of inundation exposure due to pluvial and fluvial floods on different return periods over a broad geographic domain from a validated 30 m resolution model, depth-damage functions and property-level information on building characteristics and market prices from Zillow’s ZTRAX database for a sample of over 1 million single family homes in Massachusetts. Of these, 236,897 (26,219) homes are at risk of pluvial (fluvial) flooding with $65 M ($21 M) in expected yearly losses which make up 2.4% (8.9%) of their overall structure value discounted yearly at 3% over the course of a typical mortgage. Overall expected damages are driven disproportionately by homes exposed to extreme (>= 100 cm) flood depths, associated mostly with fluvial floods, but a substantial portion of overall losses is contributed by the large number of high value properties surrounding Boston exposed to nuisance flooding (3-10 cm) in basements from rainfall. Partitioning homes by nuisance, moderate (10-100 cm) and extreme flood depths effectively draws out distinct hazard and asset distributions informing targeted risk reduction strategies, as opposed to return period or event-based planning which dominates current government practice. We find that retrofits and buyouts based on the risk distribution can result in over 55% (30%) in cost effective loss reduction interventions on 16% (8%) of pluvial (fluvial) at-risk homes. In contrast, ex-post disaster buyouts for a historic extreme event aren’t cost effective and ex-post disaster retrofits are cost effective but implemented only after severe losses have been realized. Our representation of objective flood risk over a large spatial scale elucidates the complex relationships under the present distribution of hazard and vulnerability so that we may inform adaptation and development in the face of climate change.