Non-banking financial companies
Borrower records.
Business context.
Connect borrower, loan, business and branch data with the documents your operations team needs.
See the business behind the record.
Start with a borrower ID, then follow business links, branch context and supporting documents.
Borrower 014
borrower:014Keep the source fields and follow declared relationships.
Business profile
business:008Company fields and related-party references.
Branch context
branch:004Portfolio grouping and assigned service records.
Document reference
document:031Original text, source location and document version.
Your application combines the results by ID. Supplied embeddings and searchable text are indexed separately.
Example: group borrower records by branch
Illustrative SQL for a schema with a branch_id field.
SELECT branch_id, COUNT(*) AS borrowers
FROM borrowers
GROUP BY branch_id;5 use cases / NBFCs
The right modalities for your workflow.
Start with the combination that fits your question. These are recommended starting points; the best fit depends on your data and query patterns.
- SQL Filter, join and aggregate records
- Graph Follow relationships between records
- FTS · Full-text search Find keywords, phrases and exact wording
- Vector Find similar items or meaning
| Use case | Recommended modalities | Why this combination fits |
|---|---|---|
| Collections worklists Find overdue instalments and organise follow-up work. | SQL filters due dates and repayment status, joins borrower records and aggregates outstanding amounts. | |
| Borrower relationship review Explore borrower, guarantor and business connections. | SQL provides loan and borrower attributes. Graph follows the declared relationships between borrowers, guarantors and businesses. | |
| Collateral evidence review Trace a financed asset to its owners, loans and supporting records. | SQL selects asset and loan records, Graph connects ownership and financing relationships, and FTS searches collateral descriptions and documents. | |
| Loan file retrieval Find the relevant wording in application and verification documents. | SQL retrieves the application and document metadata. FTS finds references and phrases in the indexed loan file. | |
| Field-team knowledge Find process guidance for a servicing or collections question. | FTS matches product terminology, Vector finds related guidance, and SQL identifies the applicable product and source revision. |
Combine query results in your application using shared record IDs. Keep text indexes and embeddings updated as the source data changes.
Four query models
One application.
Several ways to explore.
OriginChainDB stores and queries the representations. Your application chooses the queries and assembles the results.
Explore the database- SQL
- Structured borrower and loan fields, branch filters and portfolio aggregates.Query records
- Graph
- Declared relationships between borrowers, businesses, branches and partners.Follow relationships
- Vector
- Related servicing notes and document passages, using supplied embeddings.Search by similarity
- Full-text
- Exact phrases, document titles and reference codes in indexed text.Match the wording
Implementation path
Start with one branch or workflow.
- 01 / Connect the sources
Keep stable identifiers.
Register borrower, loan, business and document schemas; retain source IDs and declared relations.
- 02 / Prepare retrieval
Track the separate writes.
Save rows, supply embeddings and index selected document text through their own endpoints.
- 03 / Build the view
Return records with context.
Apply access rules, combine result IDs and show source versions and update times.
Keep ingestion progress and retries explicit when a source record or document changes.
See the ingestion pattern