What Is Field-Level Mapping?
Field-level mapping refers to the configuration that links structured outputs from intake and scrubbing workflows to specific CRM fields.
In MCA and small business lending, this makes sure that data extracted from bank statements, IDs, or decision emails populates the correct record attributes such as applicant name, account number, or underwriting status.
This mapping usually occurs after scrubbing and just before CRM write-back. Operators use it to avoid mismatches where data could be placed into the wrong field, which would create errors and slow down underwriting.
How Does Field-Level Mapping Work?
Field-level mapping involves translating parsed outputs into CRM updates.
- Field identification: Key outputs like ADB, NSF counts, or ID expiration dates are identified during scrubbing.
- Mapping rules: Each output is assigned to a target CRM field (e.g., “ADB → Financial Metrics > Average Daily Balance”).
- Validation: The mapping is checked to make sure formats and field types align.
- Write-back: Clean values are written into the correct CRM fields automatically.
In Heron, field-level mapping is a built-in step before CRM write-back.
- Automated parsing: Submissions are ingested and scrubbed for key values and flags.
- Mapping engine: Parsed outputs are matched against preconfigured CRM field rules.
- Structured outputs: Each value is written into its precise field within the system of record.
- Next action: Underwriters open CRM records and see structured fields already populated, without needing to rekey data.
This prevents confusion, reduces errors, and guarantees data consistency across deals.
Why Is Field-Level Mapping Important?
For brokers and funders, field-level mapping is important because misaligned data creates major inefficiencies. If a key figure like ADB is placed in the wrong field, underwriters may overlook it or make decisions based on incomplete information.
Heron makes field-level mapping more valuable by automating the process at scale. Every submission is parsed, mapped, and written into the CRM correctly, giving teams confidence in the data they use to underwrite deals.
Common Use Cases
Field-level mapping is applied in daily submission workflows.
- Assigning parsed bank balances to the correct CRM financial fields.
- Writing identity checks, expiration dates, and fraud flags into compliance fields.
- Updating deal status fields automatically after scrubbing.
- Populating risk metrics like NSF counts or overdraft frequency in underwriting dashboards.
- Standardizing how all brokers’ submissions are recorded in a single CRM system.
FAQs About Field-Level Mapping
How does Heron handle field-level mapping?
Heron automatically matches parsed outputs from scrubbing to preconfigured CRM fields and writes them back with complete accuracy.
Why is field-level mapping critical in MCA workflows?
It reduces errors, eliminates rekeying, and ensures underwriters have the right data in the right place. Without it, mismatches could delay or derail deal flow.
What outputs should teams expect from field-level mapping?
Teams receive CRM records with fully populated, correctly placed fields, including balances, flags, statuses, and completeness scores, all structured for underwriting use.