What Is a Loan Tape?
A practical guide to loan tape fields, formats, validation, normalization, and portfolio analysis.
A loan tape is a structured file with one record per loan and columns that describe each loan's identity, terms, borrower or obligor attributes, collateral, balances, and performance. It is commonly delivered as a CSV, spreadsheet, database extract, or machine-readable regulatory filing.
Lenders, investors, servicers, rating agencies, and analysts use loan tapes to evaluate a portfolio at the asset level. The file may support a loan sale, securitization, warehouse facility, due-diligence review, servicing report, regulatory submission, or ongoing credit monitoring.
What fields are in a loan tape?
There is no single universal schema. The required columns depend on the asset class, transaction, reporting date, and intended analysis. Most useful tapes include several groups of fields:
| Field group | Common examples | What it helps answer |
|---|---|---|
| Identity | Loan ID, account ID, issuer, servicer, pool | Is every asset unique, traceable, and assigned to the right population? |
| Origination | Origination date, original balance, term, rate, product | How was the loan structured at closing? |
| Borrower or obligor | Credit score, income, geography, industry, risk grade | What borrower characteristics drive concentration and performance? |
| Collateral | Asset type, value, age, location, loan-to-value ratio | What supports recovery if the borrower defaults? |
| Current status | Current balance, payment status, days past due, modification flag | Which loans are current, delinquent, modified, charged off, or paid off? |
| Cash flow | Scheduled payment, actual payment, principal, interest, recoveries | Are collections matching contractual expectations? |
| Reporting context | As-of date, reporting period, data source, field dictionary | Can the tape be compared consistently across time and sources? |
Consumer loan tapes often include credit score, debt-to-income or payment-to-income measures, collateral details, and delinquency status. Commercial and small-business tapes may emphasize industry, business age, guaranty, use of proceeds, and lender information. A tape should always travel with a data dictionary that defines each field, unit, permissible value, and reporting convention.
Loan tape, data tape, servicing tape, and remittance file
The terms overlap, but they are not always interchangeable:
- Loan tape or data tape: a broad loan-level inventory used for analysis, diligence, reporting, or a transaction.
- Bid tape: a tape distributed to prospective buyers so they can evaluate and price a portfolio.
- Servicing tape: a recurring operational file with payment, delinquency, modification, and collection activity.
- Remittance file: a period-specific report describing cash flows and balances remitted to investors.
The filename is less important than the grain and definitions. Analysts should confirm whether a row represents a loan, borrower, collateral item, payment, or reporting-period observation before calculating anything.
How to analyze a loan tape
- Confirm the grain and as-of date. Establish what one row represents and the period covered.
- Read the data dictionary. Map field names, units, status codes, null conventions, and source-system definitions.
- Validate keys and types. Check identifier uniqueness, dates, numeric formats, percentages, currencies, and categorical values.
- Reconcile control totals. Compare record counts and balances with source reports before relying on derived metrics.
- Profile completeness. Measure missingness by field, issuer, vintage, product, and reporting period.
- Normalize comparable fields. Align inconsistent names and codes without erasing source lineage.
- Build portfolio metrics. Calculate weighted averages, concentrations, delinquency, loss, recovery, prepayment, and transition measures using explicit denominators.
- Segment and trend. Compare performance across origination vintages, credit bands, collateral groups, geographies, lenders, and time.
- Preserve an audit trail. Record exclusions, mappings, assumptions, source versions, and reconciliation results.
What is loan tape cracking?
Loan tape cracking is an informal term for turning an unfamiliar raw tape into an analysis-ready dataset. The work typically includes file ingestion, schema discovery, field mapping, type conversion, code normalization, data-quality checks, reconciliation, and metric construction. The difficult part is usually not opening the spreadsheet. It is determining what every field means and whether apparently comparable values are truly comparable.
Common loan tape data-quality problems
- Duplicate or recycled loan identifiers
- Dates stored in mixed formats or reporting periods assigned incorrectly
- Balances that do not reconcile to portfolio-level totals
- Percentages represented sometimes as decimals and sometimes as whole numbers
- Inconsistent delinquency, payoff, modification, or chargeoff codes
- Missing borrower or collateral fields concentrated in particular issuers or vintages
- Restated historical records without a version or lineage marker
- Performance calculations that mix loan counts and dollar balances
A clean-looking file can still produce misleading results if the denominator changes across periods or a short reporting history silently censors part of the portfolio. Reconciliation and coverage checks belong ahead of charts and models.
Public loan-level datasets as standardized tapes
Some public datasets provide a standardized form of loan-level reporting. The SEC explains that SEC Form ABS-EE can include Schedule AL asset-level data and performance fields such as scheduled collections, actual collections, and delinquency status. LoanTape normalizes these filings for auto ABS loan-level analysis.
The U.S. Small Business Administration publishes SBA 7(a) and 504 FOIA data with downloadable files and a data dictionary. LoanTape uses those public records for SBA 7(a) lender and portfolio analytics and SBA 504 analytics.
How LoanTape uses loan-level data
LoanTape parses public SEC and SBA records into normalized analytical datasets. The public pages show the fields and research built from that work, including the auto ABS dataset field inventory, interactive credit dashboards, and original auto ABS and SBA research.
For access to dashboards, exports, premium research, and analyst workflows, compare the available LoanTape plans.