Street prices, land prices, hazards, geology and registry on one map. The AI briefs you on unfamiliar areas and prepares a draft review memo (the evaluation judgement stays with the analyst) — helping reviewers cover the same points and prepare decisions.
Sound familiar?
Examples of problems regional-bank credit and collateral teams may face. *The Service does not perform collateral valuation or real-estate appraisal.
Street prices, land prices, hazards, registry… half a day just jumping between sites.
With MAPRISE
Land prices, transactions, registry maps, hazards and geology on one screen, with a direct link to the NTA street-price map.
Just ask the AI
“Pull together what I need to value this collateral”
Collateral data gathering
Gathered across many sitesTogether on one screen
Out-of-prefecture collateral — I have no feel for the area at all.
With MAPRISE
The AI summarises 19 years of land prices, future population and livability, helping reviewers cover the same points.
Just ask the AI
“What is this area like? And the price trend?”
Out-of-area market read
Local enquiries, outside researchOverview from an AI summary
Each analyst checks disaster risk to a different depth.
With MAPRISE
Flood, landslide, tsunami and geology checked the same way every time, and shows a reference risk score using the same steps.
Just ask the AI
“Score this property’s disaster risk”
Standardised risks
4 risks, one standard
Writing the credit-memo comment eats time on every file.
With MAPRISE
The AI drafts a review memo organising price trends, risk indicators and local market data (the valuation judgement remains with the analyst); analysts focus on reviewing and editing.
Just ask the AI
“Draft a review memo on this property for the credit memo”
Draft review memo
Drafted by the AI
* Comparisons illustrate how the workflow changes; they are not measurements. Actual results vary by environment and usage.
Before and after
Places to check
Collected by hand, retyped into the memo
Regulations
Hazards
Prices & population
Includes analyst review
* Comparisons illustrate how the workflow changes; they are not measurements. Actual results vary by environment and usage.
Nothing to learn
No menus or jargon to memorise. Ask in your own words and the AI looks up the data on the map and answers — qualitative questions like "what kind of area is this?" and quantitative ones like "by what percentage did it change?" alike.
No training needed
Enter an address and say what you want to know. No manuals or training sessions.
Ask how to use it, too
Ask "how do I show flood depth on the map?" and the AI walks you through it.
Qualitative and quantitative
Get both the narrative ("what is this area like?") and the numbers (percent, people, scores), with charts.
A conversation with MAPRISE AI
Summarise this collateral’s risks for the credit memo
Inside a 0.5–3 m flood-inundation area. Ground risk is low, but the surrounding population keeps declining, which may weigh on land prices long-term.
How do land prices in flood zones compare with outside?
Within 3 km, areas with 0.5–3 m flooding show land-price change up to 14.3% lower (2020–2025).
I have never covered this area. What is it like?
A residential area clustered around the station, with good healthcare and schools that draw families.
How has land value here moved over 19 years?
Here is 2007–2025 as a chart; the recent trend is upward.
* The conversation illustrates the shape of the answers; figures are examples unless quoted from a real screen. AI answers are for reference only — please confirm important decisions with a specialist.
By the numbers
Share of regional banks' loan balance allocated to real estate-related lending (including individual mortgages, etc.); real estate and construction corporate lending alone is approx. 20%. Standardising collateral evaluation is a board-level priority.
Source: Bank of Japan, "Financial System Report"
Share of regional banks' corporate loans extended outside their home prefecture (real-estate lending is said to be similar). Reading out-of-area markets is a challenge.
Source: Japan Research Institute, "Expansion of Real Estate-Related Lending by Regional Banks and the Risks It Entails" (Oct 2025), citing the FSA
regional banks and shinkin cite legacy systems as a barrier to operational efficiency.
Source: METI, "DX Report 2" (estimate)
Breakdown: Collateral data — street prices, hazards and registry on one screen / Draft review memo prepared by AI (evaluation judgement stays with the analyst) / 19-year land-price timeline shows the trend
* The comparison illustrates how the workflow changes; it is not a measurement. Actual results vary by environment and usage.
| Scenario | Before | After (MAPRISE) |
|---|---|---|
| Collateral investigation | Manually gather street-line / land / hazard from many sites | All data unified on one screen; AI prepares a draft review memo (evaluation judgement stays with the analyst) |
| Out-of-area market analysis | Call local branches; outsource market research | 19 years of land-price trends + recent comparables visualised on the map |
| Mid-loan monitoring | Staff periodically re-check each portal manually | Hazard changes and land-price moves for registered properties auto-alerted (planned) |
| Emergency lending post-disaster | Matching damage reports to collateral is laborious; rapid lending hard | All collateral properties listed on the hazard map; exposure visible on the map |
| Credit-committee writeup | Manual comment-writing across multiple sources | AI integrates land-price, risk, and market trend into a draft review memo (evaluation judgement stays with the analyst) |
The Before / After above illustrates how the workflow can change with MAPRISE; it is not a measured result. Actual results vary by environment and usage.
Note: the registry map data does not constitute official certification by the Legal Affairs Bureau. For formal verification of rights, please obtain a certified copy of the registry.
| Step | MAPRISE step |
|---|---|
| 1 | Corporate client submits a loan application; collateral and certificate confirmed |
| 2 | Enter the address → street-line / hazard / geology / registry / land-price trend all on one screen |
| 3 | Click "Generate draft review memo" → the AI outputs a draft (evaluation judgement stays with the analyst) |
| 4 | Confirm and edit the AI draft (professional judgement stays with the analyst) |
| 5 | Finalise the credit-committee package with the land-price chart PDF attached |
| Ongoing | Mid-loan monitoring: land-price moves and hazard changes auto-alerted (planned) |
* An example of the workflow. Time required varies by property and usage.
Q. How can I check the rosenka (roadside land price) value?
A. Type in an address, and a link labeled "Inheritance Tax Rosenka (National Tax Agency)" appears in the search result popup. Clicking it opens the matching rosenka map (a PDF published by the National Tax Agency) directly. When a neighborhood spans multiple sheet numbers, every plausible sheet is listed. We don't recreate the map ourselves — this routes you directly to the page published by the National Tax Agency. Available across all 47 prefectures.
Q. Can the credit-committee template be customised?
A. Yes — on the Business plan, output layouts can be customised to match in-house formats. The Enterprise plan (coming soon, timing TBD) will also include one-on-one work with our CSM.
Q. How is security and information handling structured?
A. Hosted in the cloud with TLS encryption end-to-end. The property information you input is not shared with other tenants. SSO/SAML support is planned for the Enterprise plan.
Q. Is on-premises deployment supported?
A. Today we offer cloud (SaaS) only. We can discuss dedicated environments under the Enterprise plan.
Q. Can it integrate with our existing lending systems via API?
A. API-key based integration with external systems is planned. Specific requirements are scoped under the Enterprise plan.
Q. What does mid-loan monitoring notification cover?
A. Email alerts covering hazard-info changes and land-price moves around registered properties are planned (Business / Enterprise). Integration with flood and landslide warnings is also on the roadmap.
For collateral evaluation across a regional bank or shinkin, we recommend the Business plan.
Use case: for collateral valuation and loan screening, AI quantifies how disaster risk affects land prices (Kyushu-only data), and a reference risk score organises supporting material for credit memos (the judgement stays with the analyst).
Free during beta — try any plan
The beta is free to try. We're also happy to schedule a demo.
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