Portfolio Screening & Data Enrichment
Prioritisation, segmentation and risk identification across fragmented portfolios — before the data is good enough to price.
- Portfolio data usually describes the loan. Pricing requires knowing the asset.
- Screening establishes early which assets carry the value and which carry the risk.
- Every correction is logged, so the enriched dataset can be audited rather than trusted.
When this is relevant
Fragmented portfolios rarely arrive in a state that supports pricing. Records are inconsistent between sources, addresses do not resolve, duplicates inflate the count, registered and cadastral floor areas contradict each other, and the encumbrances and occupational status of each asset are only established once the Land Registry excerpt is obtained.
None of this is unusual. What creates risk is pricing as though it were not the case — particularly under the time pressure of a bid process, where the temptation is to treat the dataset as given and reconcile later.
A portfolio priced on unexamined data is not priced. It is estimated.
Where REV contributes
REV works on the dataset before it works on the value. Records are deduplicated, addresses geolocated and verified, floor area and typology fields cross-checked against independent sources, and inconsistencies flagged rather than silently corrected.
The portfolio is then segmented on criteria that matter for pricing: typology, market depth, liquidity, occupancy status and the quality of the evidence available for each group. Assets where the evidence is thin are identified as such, rather than absorbed into an average.
The result is a prioritised view: which assets justify individual attention, which can be treated at group level, and where due diligence effort will change the answer. That prioritisation is usually worth more than any single valuation in the early stages of a process.
- Portfolio screening ahead of a non-binding offer
- REO portfolio pricing support
- NPL collateral review and segmentation
- Data quality assessment before a valuation exercise
- Segmentation for a disposal strategy
- Geolocation and duplicate remediation
- Prioritisation of due diligence effort
- Screening pack with a prioritised asset list
- Data quality report stating what was corrected and what remains uncertain
- Segmentation matrix by typology, liquidity and market depth
- Risk flags with the rationale for each
- Geolocation QA log
- Enriched dataset with provenance recorded per field
- Executive summary for committee review
How the work is structured
- Intake. Data received, scope agreed and known gaps recorded before any processing begins.
- Cleansing and QA. Deduplication, geolocation verification and cross-source validation, with every change logged.
- Segmentation. Assets grouped by typology, market depth, liquidity and evidence quality.
- Risk overlays. Flags applied where execution, legal position or evidence quality materially affect pricing.
- Prioritisation. A ranked view of where attention and due diligence effort will change the outcome.
If you are assessing a fragmented portfolio and need to know what the data supports before you price it, we would be pleased to hear from you.
Discuss a mandate