Note Intel

Help & User Guide

Everything you need to get the most out of Note Intel — from finding sellers to understanding lead scores.

What is Note Intel?

Note Intel pulls mortgage assignment records from county public records (via ATTOM Data) and turns them into actionable intelligence for note traders. Every time a loan changes hands — a lender sells a note, a servicer transfers rights — it gets recorded at the county level. We collect those records and let you slice them to find who's actively selling, what loan types they move, and how hot they are as a lead.

The core workflow is:

  1. Ingest county data via the Data Ingestion form on the Dashboard.
  2. Find sellers and buyers using the Find Sellers search.
  3. Qualify leads using Lead Scores, Entity Detail, and Market Velocity.
  4. Push promising leads directly into Trade.Paperstac as CRM contacts.

Find Sellers / search

Your primary prospecting tool. Search all entities in the database and rank them by how likely they are to have notes for sale.

Filter options

NameFuzzy search — partial names work. Try "First National" or "ABC Mort".
StateFilter to a single state. Leave blank for national results.
Min / Max LoansVolume floor/ceiling. Start with Min Loans = 5 to filter noise.
Entity TypeLender, Servicer, Investor, Government, MERS. Lenders and Investors are highest-priority seller types.
RoleAssignor = sellers (transferred notes away). Assignee = buyers (received notes). Switch to Assignee to find active buyers for your inventory.
Loan TypeHard Money, Conventional, FHA, VA, Second Lien, Commercial, USDA. Hard Money sellers are typically the highest-value leads.
Sort BySort by Loan Count, Lead Score, or Total Volume. Lead Score is the recommended default — it surfaces the most actionable prospects.

Reading the results

Each row shows the entity name, type badge, loan count, total volume, average loan size, date range of activity, and number of states. Click any entity name to open the Entity Detail page for a full portfolio breakdown.

💡 Best practice

Start with Role = Assignor, Sort = Lead Score, Min Loans = 10. This gives you a ranked list of the most active note sellers. Then narrow by state or loan type based on what your buyers want.

Assignments / assignments

Individual loan-level records straight from county filings. Use this when you need to verify a specific transfer, look up a borrower, or drill into a property address.

Key columns

Recording DateWhen the assignment was officially filed with the county — most reliable date signal.
Assignor / AssigneeRaw county name + resolved canonical entity name in parentheses. If no entity resolved, the raw name is used as-is.
Loan AmountOriginal loan balance at origination — not current unpaid balance.
Servicing TransferFlagged when the transfer is a servicing rights change rather than a full note sale. Useful for separating servicer activity from actual note sales.

💡 Best practice

Use the Servicing Transfer = No filter to exclude routine servicing changes and focus only on actual note sales. Combine with a loan amount range to find portfolio-sized transfers.

Servicer Tracker / servicers

Shows who controls mortgage servicing rights by state — ranked by assignment volume. Servicers with high transfer counts are actively moving loans and may have pools available or incoming inventory.

How to use it

  • Filter by state to see who dominates servicing in your target market.
  • The pie chart shows relative market share — a dominant servicer in a state is a high-value relationship target.
  • Click the servicer name to open Entity Detail and see their full profile and lead score.

Matchmaker / matchmaker

Side-by-side view of the top sellers and buyers for a specific loan type. Designed to answer: "Who has hard money notes to sell, and who is actively buying them?"

How to use it

  • Select a loan type — this is required. Start with Hard Money or Second Lien for the highest-value opportunities.
  • Optionally filter by state to narrow to your target market.
  • The left column is sellers (assignors); the right column is buyers (assignees).
  • Use this to pitch a seller: "We have buyers already active in your loan type in your state."
  • Use this to pitch a buyer: "We have sellers moving this exact loan type — here's the market depth."

Heat Map / map

A choropleth map showing assignment density by state. Darker = more activity. Use it to identify which states have the most active note markets and prioritize your ingestion and outreach strategy.

Metric options

Assignment CountRaw volume of recorded transfers — good for overall market size.
Total VolumeDollar value of all assignments — identifies the highest-dollar markets.
Unique SellersNumber of distinct entities selling — shows market breadth vs. concentration.

💡 Best practice

Filter by Hard Money and switch to Unique Sellers to find states with a diverse pool of hard money lenders. Many sellers in a state = more deal flow potential than a state dominated by one large servicer.

Entity Detail / entity/{id}

The deepest view of any single entity. Access it by clicking an entity name anywhere in the app. It's your pre-call research sheet — review it before reaching out to a seller.

Six data sections

Selling By StateWhich states they sell in and how much — tells you where to focus the conversation.
Buying By StateWhere they buy — useful if they're also a potential buyer for your inventory.
Selling By Loan TypeWhat types of notes they sell — tailor your pitch to their actual product.
Buying By Loan TypeWhat types they buy — useful when positioning them as a buyer on Paperstac.
Monthly ActivitySelling vs. buying over time — look for consistent patterns or recent spikes.
Top CounterpartiesWho they sell to and buy from most. If a counterparty is already on Paperstac, mention it.

Buyer Appetite section

Shows their preferred states and preferred loan types when buying — built from actual transaction history, not self-reported. Use this to match them with sellers who have the right inventory.

💡 Push to Trade

When you're ready to pursue a lead, use the "Push to Trade" button on the Entity Detail page to create a CRM contact in Trade.Paperstac automatically — no copy-pasting required.

Lead Score

Every entity gets a score from 0–100 based purely on their public record transaction history — no guesswork. The score tells you how likely they are to have notes available and be receptive to outreach.

Score bands

Hot 70–100 — Active, high-volume, recent. Call these first.
Warm 45–69 — Active but lower volume or older activity. Worth outreach.
Cold <45 — Low volume, old records, or low-value entity type. Deprioritize.

Scoring factors (100 pts total)

25

Volume

75+ loans → full 25 pts. 30+ loans → 20 pts. More loans = more consistent deal flow.

25

Recency

Active within 90 days → full 25 pts. Within 6 months → 20 pts. Older records score lower — stale leads rarely convert.

20

Loan Type Premium

Hard Money → 20 pts (most tradeable). Second Lien → 18. Commercial → 15. Conventional/FHA/VA → 8–10. Mixed/Unknown → 5.

15

Entity Type

Lender → 15 pts. Investor → 12. Servicer → 8. Government → 2. Lenders and investors are more likely to sell whole notes vs. just transfer servicing.

15

Geographic Concentration

Active in 1–2 states → full 15 pts. 8+ states → 0 pts. Concentrated sellers are easier to pitch; national players are harder to reach the right person.

💡 Score context

A score of 66 (Warm) with 25/25 on Volume but only 5/20 on Loan Type means the entity moves a lot of loans but the type is unclear — worth a call to clarify what's in the pipeline. Don't dismiss Warm leads if their Volume is maxed out.

Data Ingestion

The app pulls data from ATTOM Data on demand — the database only knows about counties you've explicitly ingested. Use the Ingest County Data form on the Dashboard to add new counties.

Fields

FIPS Code5-digit county identifier. Use the Florida FIPS reference grid on the Dashboard, or look up any county at USDA FIPS list.
State2-letter abbreviation (FL, TX, CA). Must match the county FIPS.
Date From / ToOptional. Leave blank to get all available records. Narrow the range to pull a specific time window without using up API calls on old data.
Max PagesEach page = up to 100 records. Default 10 (1,000 records). Increase to 50 for high-volume counties like Miami-Dade or Los Angeles.

💡 Strategy

Start with your highest-priority states (Florida, Texas, California, Georgia are high-volume note markets). Ingest the top 2–3 counties per state first — most activity concentrates in major metros. Re-ingest monthly to keep data fresh and catch new sellers.

Trade.Paperstac Integration

Push any entity directly into Trade.Paperstac as a CRM contact with one click from the Entity Detail page. This connects your research pipeline to your deal-making pipeline.

Workflow

  1. Find a promising lead in Note Intel (score ≥ 45, recent activity).
  2. Review their Entity Detail page — states, loan types, counterparties.
  3. Click "Push to Trade" on the Entity Detail page.
  4. A CRM contact is created in Trade.Paperstac with the entity name and type.
  5. Open Trade.Paperstac, find the contact, and add notes from your research before calling.

Already pushed?

The Entity Detail page shows a "Synced to Trade" badge if the entity has already been pushed — no duplicates created.

Pro Tips

🎯
Use the Matchmaker before calling a seller. Know who the active buyers are for their loan type before you pick up the phone. Being able to say "We have 3 active buyers for hard money notes in Florida right now" is a powerful opener.
📅
Re-ingest counties monthly. Assignment records trickle in as counties process filings. A county you ingested 3 months ago will have new records. Set a monthly reminder to re-pull your top counties.
🔍
Search by partial name. Lenders often file under multiple legal entity names (e.g., "First National Bank" vs. "FNB Holdings LLC"). Try searching the root word rather than the full legal name to catch all aliases.
📊
Prioritize single-state sellers. Geographic concentration scores high (15 pts) because sellers focused on one state are easier to pitch — they have a clear profile and your buyers can target them precisely.
Spikes = urgency. A seller who had 5 assignments per month and suddenly jumped to 40 in one month is liquidating a portfolio. That window is narrow — move quickly when Market Velocity shows a spike.
🔄
Check Top Counterparties for warm intros. On the Entity Detail page, if a counterparty is already a contact in Trade.Paperstac, you have a mutual connection — use it as a reference in your outreach.
🌙
Dark mode is available. Click the moon/sun icon at the bottom of the sidebar to toggle dark mode. Your preference is saved automatically.
Note Intel is powered by ATTOM Data public records. Data reflects county filing dates and may lag actual transfer dates by 30–90 days depending on the county.