Lender credit teams often piece together conditions data from 20+ government and industry sources for each loan assessment. Here's how that compares to agriIQ's automated pipeline.
| Dimension | Manual gathering | agriIQ |
|---|---|---|
| Time per assessment | Hours of research per loan, repeated for every application — each analyst queries sources, pieces together context, and writes it up from scratch | Conditions intelligence generated from live scored data in minutes — consistent inputs, consistent output |
| Data coverage | Depends on which sources the analyst checks that day; a stress signal on a source the analyst didn't open is a miss | 23 government and industry sources consistently ingested every night and scored across 7 dimensions |
| Consistency | Output varies by analyst and by day — different queries, different lookback windows, different judgement calls | Single scored methodology, applied uniformly across every assessment and every sub-region |
| Sub-regional detail | State-level context is easy to gather; SA4 sub-region-level conditions require targeted sourcing that most teams skip | 57 SA4 sub-regions scored daily with localised rainfall, soil moisture, fire activity, and climate stress indicators |
| Concentration view | Not supported without building a parallel portfolio spreadsheet — commodity-and-region exposure mix stays invisible | Built-in HHI concentration risk and peer benchmarking across the full lending book |
| Daily refresh | Each data point refreshed only when an analyst goes looking for it — stale numbers quietly inform decisions | Fully refreshed overnight; every score, commodity price, and narrative available each morning |
| Data lineage | Notes may cite sources; reproducing the exact data used weeks later is difficult | Every score traces back to named government and industry sources documented on the methodology page |
| Annual effort | Hundreds of analyst hours per year spent re-gathering the same conditions data for each application | Team from $249/mo; Professional from $599/mo; Enterprise custom — consistent coverage whether the team reviews 10 loans or 1,000 |
Manual gathering
Hours of research per loan, repeated for every application — each analyst queries sources, pieces together context, and writes it up from scratch
agriIQ
Conditions intelligence generated from live scored data in minutes — consistent inputs, consistent output
Manual gathering
Depends on which sources the analyst checks that day; a stress signal on a source the analyst didn't open is a miss
agriIQ
23 government and industry sources consistently ingested every night and scored across 7 dimensions
Manual gathering
Output varies by analyst and by day — different queries, different lookback windows, different judgement calls
agriIQ
Single scored methodology, applied uniformly across every assessment and every sub-region
Manual gathering
State-level context is easy to gather; SA4 sub-region-level conditions require targeted sourcing that most teams skip
agriIQ
57 SA4 sub-regions scored daily with localised rainfall, soil moisture, fire activity, and climate stress indicators
Manual gathering
Not supported without building a parallel portfolio spreadsheet — commodity-and-region exposure mix stays invisible
agriIQ
Built-in HHI concentration risk and peer benchmarking across the full lending book
Manual gathering
Each data point refreshed only when an analyst goes looking for it — stale numbers quietly inform decisions
agriIQ
Fully refreshed overnight; every score, commodity price, and narrative available each morning
Manual gathering
Notes may cite sources; reproducing the exact data used weeks later is difficult
agriIQ
Every score traces back to named government and industry sources documented on the methodology page
Manual gathering
Hundreds of analyst hours per year spent re-gathering the same conditions data for each application
agriIQ
Team from $249/mo; Professional from $599/mo; Enterprise custom — consistent coverage whether the team reviews 10 loans or 1,000
