From Statement of Values to Smart Asset Registry: Preparing FEMA PA Applicants for Cost-Estimate-Driven Disaster Funding

 

 

Page 2 — What a Traditional Statement of Values Does Well

The traditional SOV is still essential. It should not be discarded. It should be upgraded.

The SOV typically provides five core functions.

First, it identifies locations. Each site should have a unique location number, physical address, city, state, ZIP code, county, and latitude / longitude. The attached document emphasizes that accurate geocoding is critical for catastrophe modeling, especially for wind, flood, earthquake, and high-hazard areas.

Second, it states total insurable values. These include building value, business personal property, inventory / stock, and business interruption or extra expense values. These values support insurance-to-value analysis, capacity placement, deductibles, sublimits, and catastrophe modeling.

Third, it provides primary COPE data. COPE means Construction, Occupancy, Protection, and Exposure. These are the underwriting basics: construction class, occupancy description, year built, square footage, number of stories, and basic fire protection.

Fourth, it provides protection and engineering information. For public-sector portfolios, this may include sprinkler type, water supply, public protection class, monitored alarms, generator protection, backup power, and essential service continuity features.

Fifth, it may include secondary COPE fields, which are increasingly important for catastrophe modeling. These include roof geometry and material, year of major roof / HVAC / electrical / plumbing updates, opening protection, basement / pit details, and flood vulnerability indicators. The attached document notes that absent secondary COPE data, catastrophe models may default to conservative or worst-case assumptions.

For insurance underwriting, these data points are useful. For FEMA Public Assistance, they are only the beginning.

A FEMA-ready Smart Asset Registry must extend the SOV in at least six ways:

1. It must document pre-disaster condition.

2. It must support facility eligibility and legal responsibility.

3. It must classify assets by FEMA PA category and facility type.

4. It must support rapid damage-to-cost conversion.

5. It must identify codes, standards, mitigation, and resilience gaps.

6. It must connect physical asset data to insurance, parametric triggers, and recovery funding sources.

• insurance claim validation;

• FEMA damage inventory;

• preliminary damage assessment;

• cost estimating;

• mitigation scoping;

• parametric payout calculations;

• capital planning;

• bond disclosure;

• grant closeout;

• and audit defense.

  The attached document captures this shift well: the “old way” says Building A is worth $10 million; the “new way” says Building A is worth $10 million, is made of reinforced concrete, and has expensive electrical equipment in the basement.

  That additional “DNA” is the difference between a passive insurance list and an active

  recovery tool.

  

  Page 4 — The HR4669 Connection: Why Initial Cost Estimates Change the Data Requirement

  The proposed HR4669 §409 model is the reason this matters now.

  The bill excerpt proposes that grant amounts would be determined based on the estimated cost to repair, restore, reconstruct, or replace a damaged public or private nonprofit facility to applicable building codes. The estimate must be developed by an appropriately licensed professional and include mitigation measures, labor, management costs, materials, other associated costs, and the cost of developing the estimate.

  The same bill excerpt proposes a 90-day review period after submission of the estimate, a 30-day deadline for making funds available after approval, a one-time adjustment within two years for market changes, and finality protections absent criminal fraud.

  That structure radically increases the value of pre-disaster asset data.

  If the applicant has poor data, the estimate process becomes slow and reactive. Engineers must locate drawings, confirm dimensions, investigate construction type, determine roof age, identify MEP location, obtain photos, determine code triggers, and reconstruct pre-disaster condition after the event.

  If the applicant has a Smart Asset Registry, much of that work is already structured. The registry becomes the pre-disaster baseline for:

• total square footage;

• replacement cost new;

• construction class;

• facility function;

• occupancy;

• major systems;

• roof type and age;

• MEP location;

• flood elevation relationship;

• code compliance gaps;

• mitigation opportunities;

• prior condition;

• insurance status;

• and local unit-cost assumptions.

FEMA already recognizes cost estimating as part of PA administration. FEMA’s Cost Estimating Format is described by FEMA as a uniform methodology for determining costs of eligible permanent work for large construction projects, and FEMA’s PA training materials describe the CEF as designed to support consistency in documentation. (FEMA)

The proposed HR4669 model would make this even more important because the cost estimate itself becomes the gateway to upfront funding.

 

Page 5 — Smart Asset Registry Data Model: The Core Data Fields

A FEMA-ready Smart Asset Registry should be designed as a “flat file” at the base level, meaning one row per location or one row per asset component, with no merged cells, consistent units, and clean alpha-numeric headers. The attached document recommends this same flat-file discipline for large SOV submissions.

The following data model can be used for GOVSTAR guidance.

1. Identity and Geospatial Fields

   Every asset should include:

   • Asset ID

   • Location ID

   • Facility name

   • Facility type

   • Department / agency owner

   • Legal owner

   • Operator

   • Street address

   • City

   • County

   • State

   • ZIP code

   • Latitude

   • Longitude

   • Parcel ID

   • FEMA region

   • Disaster declaration county / jurisdiction

   • Critical facility flag

   • Essential governmental service flag

     Why it matters: geospatial precision connects the asset to FEMA designated areas, flood maps, wind grids, seismic zones, wildfire hazard zones, surge footprints, rainfall grids, and parametric insurance triggers.

2. FEMA PA Eligibility Fields

   Every asset should include:

   • FEMA PA category

   • Facility eligibility basis

   • Applicant legal responsibility

   • Public facility / PNP / critical service classification

   • Essential service designation

   • Pre-disaster use

   • Current use

   • Ownership documentation link

   • Maintenance responsibility

   • Insurance requirement status

   • Pre-disaster condition evidence link

     Why it matters: current PA eligibility requires the work to be disaster-related, in the designated area, and the legal responsibility of an eligible applicant. (eCFR) The registry should be built to help prove those elements quickly.

3. Value and Cost Fields

   Every asset should include:

   • Building value

   • Contents / equipment value

   • Business interruption or service interruption value

   • Replacement cost new

   • Replacement cost per square foot

   • Date of valuation

   • Escalation index

   • Local cost adjustment factor

   • Demolition cost factor

   • Debris removal factor

   • Soft cost factor

   • Design / engineering factor

   • Permitting factor

   • Construction contingency

   • Management cost factor

     Why it matters: proposed §409 estimates must include associated expenses such as labor, management costs, materials, and other costs to repair, restore, reconstruct, or replace the impacted facility.

4. COPE and Engineering Fields

   Every asset should include:

   • ISO construction class

   • Structural system

   • Occupancy description

   • Year built

   • Major renovation year

   • Square footage

   • Number of stories

   • Basement / below-grade area

   • Roof geometry

   • Roof material

   • Roof age

   • Roof rating

   • Opening protection

   • Sprinkler status

   • Alarm type

   • Public protection class

   • Utility service dependencies

   • Emergency power availability

     Why it matters: COPE data supports insurance underwriting, catastrophe modeling, damage estimation, and rapid recovery prioritization. The attached document identifies primary and secondary COPE fields as central to underwriting and CAT modeling.

5. Flood and Elevation Fields

   Every flood-exposed asset should include:

   • Flood zone

   • Special Flood Hazard Area flag

   • Base flood elevation

   • First floor elevation

   • Lowest adjacent grade

   • Lowest floor elevation

   • MEP elevation

   • Basement flag

   • Critical equipment location

   • Floodproofing status

   • Prior flood loss history

   • Drainage dependency

   • Pumping dependency

   • Flood depth damage function

     Why it matters: flood loss is often driven less by the building’s total replacement value and more by where the “guts” are located — electrical, mechanical, pumps, generators, boilers, IT, switchgear, fuel systems, and elevator controls. The attached document correctly identifies MEP elevation status as a major driver of percent-of-value damage in flood events.

6. Wind, Hail, and Envelope Fields

   Wind-exposed assets should include:

   • Wind design speed

   • Wind-borne debris region flag

   • Roof-to-wall connection type

   • Roof cover type

   • Roof deck attachment

   • Roof age

   • Roof uplift rating

   • Impact-resistant glazing

   • Shutter / opening protection

   • Exterior wall system

   • Rooftop equipment anchorage

   • Envelope integrity rating

   • Hail rating

   • Wind fragility curve assignment

     Why it matters: wind damage frequently begins with the building envelope. Once the roof, openings, or rooftop units fail, water intrusion and interior damage can rapidly multiply losses.

7. Seismic Fields

   Earthquake-exposed assets should include:

   • Seismic design category

   • Structural system

   • Soft-story flag

   • Unreinforced masonry flag

   • Retrofit status

   • Year of seismic upgrade

   • Peak ground acceleration trigger zone

   • Critical equipment anchorage

   • Nonstructural component vulnerability

   • Seismic fragility curve assignment

     Why it matters: a parametric earthquake trigger cannot be meaningfully translated into recovery funding without knowing which assets are reinforced concrete, unreinforced masonry, steel frame, or nonductile concrete.

8. Wildfire Fields

   Wildfire-exposed assets should include:

   • Wildland-urban interface flag

   • Defensible space status

   • Roof combustibility

   • Exterior wall combustibility

   • Ember exposure rating

   • Vent protection

   • Fire suppression access

   • Water supply reliability

   • Fuel load around asset

   • Wildfire fragility curve assignment

     Why it matters: a wildfire parametric trigger based only on perimeter proximity may overpay or underpay unless the registry contains defensible space, materials, suppression, and ember vulnerability data.

      

     

     Page 6 — ISO Construction Class as a Recovery Estimating Tool

     The attached document proposes using ISO construction class as a bridge between insurance underwriting and FEMA rapid cost estimating. That is the right concept, with one caution: ISO class is a useful starting proxy, but it should not be the only engineering variable.

     The document’s ISO framework groups buildings from Class 1 frame construction to Class 6 fire resistive construction and associates each with structural resilience, replacement cost ranges, and typical damage sensitivity.

     A Smart Asset Registry can use ISO class in three ways.

     First, ISO class supports rapid triage.

     After a disaster, a Class 1 wood-frame facility exposed to surge, fire, or high wind may be more likely to require major repair or replacement than a Class 6 reinforced concrete facility exposed to the same hazard intensity. That does not mean every Class 1 building is a total loss or every Class 6 building is safe. It means ISO class provides an early vulnerability signal.

     Second, ISO class supports cost-per-square-foot assumptions.

     A reinforced concrete public safety building may have a very different replacement cost per square foot than a metal warehouse, wood-frame community building, or masonry school. The attached document suggests linking ISO class to unit cost per square foot and a resiliency factor for rapid cost estimating.

     Third, ISO class supports parametric vulnerability functions.

     Parametric insurance works best when the parties agree in advance how hazard intensity translates into expected loss. An ISO Class 2 building and an ISO Class 6 building should not necessarily receive the same payout for the same wind speed, flood depth, or ground acceleration. The registry can assign different fragility curves by asset class.

     A simple rapid cost-estimating structure may look like this:

     [

     BDE = (Total\ SF \times UC_{sf}) \times %Damage

     ]

     Where:

   • BDE = Base Damage Estimate

   • Total SF = total square footage

   • UCsf = unit cost per square foot

   • %Damage = observed or modeled damage percentage

     Then:

     [

     TRE = BDE \times (1 + \sum Soft\ Costs) \times RF

     ]

     Where:

   • TRE = Total Recovery Estimate

   • Soft Costs = architecture, engineering, permitting, project management,

     escalation, insurance, and other soft-cost factors

   • RF = resiliency or repair complexity factor

     The attached document uses this same basic Base Damage Estimate and Total Recovery

     Estimate logic for fast-track estimates.

     For FEMA readiness, this formula should not be presented as a substitute for a licensed professional estimate. It should be presented as a preliminary estimating engine that helps applicants organize data, triage losses, and accelerate professional review.

      

     

     Page 7 — How the Smart Asset Registry Supports FEMA Upfront Funding

     If a future FEMA PA model moves toward upfront funding based on initial estimates, the Smart Asset Registry becomes the applicant’s evidence engine.

     The proposed HR4669 §409 language says the cost estimate must be developed by an appropriately licensed professional, must include mitigation measures, labor costs, management costs, materials, and other repair / restoration / reconstruction / replacement costs, and must include the cost of developing the estimate.

     That means the registry should pre-stage the data needed by engineers, architects, cost

     estimators, grant managers, and finance officers.

     Pre-disaster registry data helps answer:

   • What was the facility before the disaster?

   • Who owned it?

   • Who had legal responsibility?

   • What was its use?

   • What was its pre-disaster condition?

   • What was its replacement cost?

   • What construction system was used?

   • What systems were in the basement?

   • What systems were elevated?

   • What codes and standards may be triggered?

   • What mitigation measures are appropriate?

   • What insurance applies?

   • What local cost data should be used?

   • What prior damage or deferred maintenance existed?

     Post-disaster registry data helps answer:

   • What hazard intensity reached the asset?

   • What components are likely damaged?

   • What is the estimated percent damage?

   • What is the initial base cost?

   • What soft costs apply?

   • What mitigation costs should be included?

   • What insurance proceeds or parametric payouts may duplicate or complement the funding?

   • What scope can be submitted for upfront grant funding?

This is especially important because current PA cost eligibility depends on more than damage. FEMA PA requires eligibility of the applicant, facility, work, and costs. FEMA’s CEF materials show that cost estimating is designed to support consistency in documentation and project development. (FEMA Emergency Management Institute)

A Smart Asset Registry does not guarantee FEMA eligibility. It makes the eligibility and estimate process faster, cleaner, and more defensible.

 

Page 8 — The Parametric Trigger Layer: Turning the Registry into a Liquidity Engine

Parametric insurance pays based on an agreed event index, not a traditional loss adjustment. The trigger might be wind speed, flood depth, rainfall total, storm surge height, earthquake shaking, heat index, wildfire footprint, or river gauge height.

The attached document explains the parametric-registry link as three components:

1. Index — a verifiable data point such as wind speed, peak ground acceleration, or

   gauge height.

2. Threshold — the intensity at which payout activates.

3. Payout Function — the pre-agreed percentage of TIV or other value measure paid when the trigger is met.

   A traditional SOV can support a crude parametric product because it provides TIV by location. But a Smart Asset Registry supports a better parametric product because it explains how different assets respond to the same hazard.

   For example:

   • A Class 1 wood-frame public works garage may suffer severe wind damage at a

     lower wind speed.

   • A Class 4 masonry non-combustible school may have lower structural damage but meaningful roof or envelope damage.

   • A Class 6 reinforced concrete hospital may have limited structural damage but

     catastrophic service interruption if basement electrical systems flood.

   • A wastewater pump station may experience low building damage but high functional loss if electrical controls are submerged.

     That is why parametric design should not be based only on TIV. It should be based on:

   • asset location;

   • hazard intensity;

   • asset construction;

   • occupancy / function;

   • criticality;

   • vulnerability;

   • service interruption consequence;

   • and expected emergency cost.

     The attached document proposes an estimated loss formula:

     [

     L_e = TIV \times \Phi(I, ISO_{class})

     ]

     Where:

   • Le = estimated loss

   • TIV = total insurable value

   • Φ = fragility curve specific to ISO class and hazard

   • I = event intensity

That formula is a useful conceptual bridge between the SOV and parametric insurance.

But for government recovery, the payout function should also consider public service criticality. A $5 million firehouse may be more important than a $20 million administrative

building if the firehouse is essential to emergency response. Therefore, a municipal

parametric registry should include both asset value and mission value.

 

Page 9 — Key Smart Asset Registry Data Points for Parametric Triggers

The parametric layer requires specific data fields that go beyond ordinary insurance values.

1. Latitude and Longitude

   Lat / long is the foundation for every parametric trigger. It maps assets to:

   • wind grid cells;

   • storm surge basins;

   • rainfall pixels;

   • river gauges;

   • USGS shaking maps;

   • wildfire perimeters;

   • heat grids;

   • and observed / modeled hazard footprints.

     Without coordinates, the payout cannot be reliably linked to the asset.

2. Hazard Zone Assignment

   Each asset should be assigned to hazard zones:

   • flood zone;

   • surge zone;

   • wind zone;

   • wildfire zone;

   • seismic zone;

   • hail zone;

   • extreme heat zone;

   • landslide zone;

   • drainage / watershed area;

   • power outage zone.

     This allows different triggers to apply to different assets.

3. ISO Construction Class

   ISO class gives a first-order vulnerability proxy. The attached document uses ISO classes to distinguish frame, joisted masonry, non-combustible, masonry non-combustible, modified fire-resistive, and fire-resistive construction.

   For parametric design, ISO class helps determine whether a given wind speed, flood depth, fire perimeter, or ground shaking level should produce a high or low expected damage percentage.

4. First Floor Elevation and Base Flood Elevation

   Flood parametrics require vertical data, not just horizontal location. Two buildings in the same flood zone may have completely different damage if one has a first floor elevation above flood level and the other has basement electrical systems below grade.

   The attached document identifies first floor elevation versus base flood elevation as a critical flood-parametric data point.

5. MEP Elevation

   MEP means mechanical, electrical, and plumbing. For public facilities, MEP damage can drive both repair cost and service interruption.

   The registry should identify whether each major system is:

   • basement-level;

   • first-floor level;

   • rooftop;

   • elevated platform;

   • floodproofed;

   • protected by barriers;

   • or redundant.

     This is especially important for hospitals, police stations, fire stations, pump stations,

     wastewater plants, shelters, schools, and emergency operations centers.

6. Roof and Envelope Integrity

   Wind and hail triggers should not treat all roofs equally. Registry fields should include:

   • roof age;

   • roof geometry;

   • roof material;

   • roof attachment;

   • roof rating;

   • rooftop equipment anchorage;

   • opening protection;

   • impact glazing;

   • door ratings;

   • cladding type.

     The attached document identifies roof geometry, roof material, opening protection, and

     envelope integrity rating as important secondary COPE / parametric-readiness data points.

7. Business Interruption or Service Interruption Per-Diem

   For municipal assets, the better term may be service interruption per-diem rather than business interruption. A city hall, police precinct, wastewater plant, or transit facility may not generate ordinary commercial income, but its downtime imposes real costs.

   Registry fields should include:

   • daily cost of temporary relocation;

   • daily cost of emergency operations;

   • daily cost of service disruption;

   • daily rental / modular replacement cost;

   • daily overtime / mutual aid cost;

   • daily emergency contractor cost;

   • daily revenue loss if applicable.

     The attached document identifies BI per-diem as a parametric-readiness field where

     payout can be tied to a pre-agreed number of days after the trigger.

8. Vulnerability Coefficient

Each asset should have a vulnerability coefficient or fragility curve assignment by hazard.

This is the analytical bridge between event intensity and expected damage. For example:

Hazard	Trigger Variable	Registry Vulnerability Variable
Wind	110 mph wind speed	ISO class, roof type, envelope rating
Flood	3 feet above first floor	FFE, BFE, MEP elevation
Earthquake	PGA / shaking intensity	structural system, retrofit status
Wildfire	burned area / ember exposure	roof material, defensible space
Rainfall	10 inches / 24 hours	drainage basin, basement, pump dependency

The attached document expressly recommends vulnerability functions, fragility curves, and trigger grids to achieve near-instantaneous validation.

 

Page 10 — Settlement Protocol: How the Smart Registry Can Shorten the Time to Cash

A traditional indemnity claim asks:

What damage occurred, what does the policy cover, what is excluded, what is the actual repair cost, and what proof supports the claim?

A parametric settlement protocol asks:

Did the agreed event occur at the agreed intensity, at the agreed location, according to the agreed data source, and what payout does the schedule require?

The attached document provides a simple wind example: event occurs, wind speeds are recorded at 105 mph, the system cross-references the wind grid against the asset’s coordinates, and different ISO classes receive different payout percentages.

A municipal version could work like this:

Step 1 — Event Occurs

A hurricane, inland flood, wildfire, earthquake, or severe convective storm affects the

jurisdiction.

Step 2 — Hazard Data Is Certified

The calculation agent obtains data from the agreed source, such as:

• NOAA wind field;

• National Weather Service station;

• USGS ShakeMap;

• river gauge;

• rainfall grid;

• storm surge gauge;

• wildfire perimeter;

• or satellite-derived flood footprint.

  Step 3 — Registry Match

  The calculation agent overlays the hazard data onto the Smart Asset Registry using lat / long coordinates and hazard zone assignments.

  Step 4 — Trigger Test

  For each asset or portfolio zone, the system checks whether the trigger threshold was met. Example:

• Wind speed ≥ 105 mph in Grid Cell A.

• Flood depth ≥ 2 feet above first floor elevation.

• River gauge ≥ 18 feet.

• Peak ground acceleration ≥ agreed threshold.

• Rainfall ≥ 10 inches in 24 hours.

Step 5 — Payout Formula

The payout is calculated using an agreed schedule. Example:

[

Payout = TIV \times Vulnerability\ Factor \times Trigger\ Layer\ Percentage

]

Or:

[

Payout = Service\ Interruption\ PerDiem \times Covered\ Days

]

Or:

[

Payout = Fixed\ Emergency\ Liquidity\ Amount \times Trigger\ Severity\ Tier

]

Step 6 — Liquidity Injection

Funds can be used for emergency work, temporary facilities, debris, pumps, generators, shelters, professional estimates, engineering, or non-federal match strategy, subject to policy terms and legal restrictions.

This is where the Smart Asset Registry aligns with FEMA readiness. It does not replace FEMA. It supplies rapid liquidity while FEMA eligibility, cost estimating, environmental review, insurance review, and grant processing proceed.

 

Page 11 — Basis Risk: The Central Technical Problem

Parametric insurance has one unavoidable challenge: basis risk.

Basis risk is the mismatch between the payout and actual loss. A policy may pay when damage is lower than expected, or fail to pay enough when damage is higher than expected.

The attached document correctly states that the more granular the registry, especially with secondary COPE data, the lower the basis risk. It also notes that municipalities may use a parametric-first layer for immediate liquidity followed by a traditional indemnity layer for the tail of the loss.

A Smart Asset Registry reduces basis risk in five ways.

1. Better Geocoding

   Precise coordinates prevent the wrong hazard intensity from being assigned to the wrong asset.

2. Better Vulnerability Classification

   ISO class, roof type, MEP elevation, opening protection, floodproofing, and retrofit status help differentiate assets.

3. Better Trigger Zoning

   Assets can be grouped into rational zones: coastal surge, inland rainfall, riverine flood, wind grid, wildfire interface, seismic basin, or drainage catchment.

4. Better Payout Curves

   Instead of one flat payout for all buildings, payout curves can vary by facility class,

   construction type, hazard, and criticality.

5. Better Hybrid Design

A public entity can use parametric insurance for immediate liquidity and traditional

insurance, FEMA PA, reserves, or bond proceeds for longer-tail reconstruction.

The key is not to make parametric insurance pretend to be indemnity insurance. The key is to design parametric coverage for what it does best: speed, liquidity, transparency, and pre-agreed settlement.

 

Page 12 — Smart Asset Registry and FEMA Compliance: Avoiding the Wrong Message

The Smart Asset Registry should not be marketed as a way to bypass FEMA rules. That would be the wrong message.

It should be marketed as a way to prepare better FEMA submissions.

Current FEMA PA eligibility still requires disaster causation, designated-area location, and legal responsibility. (eCFR) FEMA also evaluates facility eligibility, work eligibility, cost reasonableness, insurance, environmental and historic compliance, procurement, and documentation.

A Smart Asset Registry helps with those requirements by organizing evidence before the

disaster.

It supports pre-disaster condition.

Photos, inspection reports, maintenance logs, roof age, equipment inventories, and asset

condition records help distinguish disaster damage from preexisting damage.

It supports legal responsibility.

Ownership, leases, maintenance obligations, mutual aid agreements, operating agreements, and service responsibilities can be linked to each asset.

It supports cost reasonableness.

Unit costs, replacement cost new, local escalation factors, contractor pricing, and prior

comparable projects can support early cost estimates.

It supports insurance review.

The registry links insurance policy schedules, deductibles, limits, sublimits, NFIP policies,

self-insurance, and parametric proceeds to the damaged asset.

It supports mitigation.

The registry identifies which facilities are below base flood elevation, lack roof protection,

have basement MEP, lack backup power, or need code upgrades.

It supports audit and closeout.

The registry creates a consistent record from pre-disaster asset condition to damage

estimate, grant award, procurement, construction, progress reporting, and final closeout.

Under proposed §409, annual progress reports would include funded projects, permitted and commenced projects, completed projects, and remaining project status, with reports made publicly available. A Smart Asset Registry can become the backbone of that reporting system.

 

Page 13 — Governance: Who Owns the Smart Asset Registry?

A Smart Asset Registry cannot live only in the insurance office. It must be governed as an enterprise disaster finance system. Risk Management owns insurance values.

Risk management maintains SOV values, policy schedules, deductibles, sublimits, catastrophe modeling data, and insurance recovery records.

Public Works / Facilities owns asset condition.

Facilities teams maintain roof data, systems data, maintenance history, inspection records, drawings, and capital repair needs.

Emergency Management owns disaster function.

Emergency managers classify criticality, continuity needs, shelter status, emergency operations use, and response dependencies.

Finance / Budget owns fiscal exposure.

Finance tracks replacement cost, reserves, matching funds, debt capacity, disaster accounts, and cost-share risk.