Loan document processingfor whole packages.
A loan file is not one document but a package: application, ID, payslips, bank statements, agreements. MiruIQ extracts each one against its schema and then checks the package as a whole, so underwriting starts from decision-ready data.
Process complete loan packages: extract from applications, IDs, payslips and bank statements, then verify that the whole file tells one consistent story.
The risk hides between documents.
Manual processing checks each document in isolation. But the expensive errors are relational: the payslip employer that does not match the application, the bank statement that belongs to someone else, the income that does not support the numbers.
Cross-checking by hand is slow enough that it gets sampled rather than done. Approvals wait on data entry, and wrong-file uploads are discovered late, sometimes after the decision.
Package processing, step by step.
Documents arrive one by one; the checks run on the whole file.
1. Ingest
Applicants upload documents in any order through your portal, or files arrive by API and email.
2. Classify
Each upload is recognized: application, ID, payslip, bank statement, purchase agreement.
3. Extract
Bank statement extraction, payslip fields and ID data, each against its own schema, including complex transaction tables.
4. Cross-check
Integrity checks compare shared fields across the package: names, employers, dates, income figures that must reconcile.
5. Deliver
Decision-ready structured data flows to your underwriting system, with exceptions parked for review.
What changes in origination.
Shorter time to decision
Underwriting starts when the package is complete and consistent, not when data entry catches up.
Lower review effort
Reviewers see only packages that failed a check, with the failing fields highlighted.
Earlier error detection
Wrong-file uploads and inconsistencies surface at intake, while the applicant is still responsive.
Numbers to hold the system to.
Package-level metrics, not per-document ones.
Cycle time
Intake to decision-ready data, the number applicants feel.
Exception rate
Share of packages requiring manual correction, tracked by cause.
Integrity mismatch rate
Share of packages with cross-document inconsistencies, your early fraud and error signal.
Loan processing questions
What lenders evaluating document automation ask most.
Shared fields carry across the package: the applicant's name, employer, dates and income appear on multiple documents, and cross-document validation compares them all. Figures that must reconcile are recalculated. A package where the payslip, statement and application disagree parks for review with the exact mismatches listed.
Yes: bank statement extraction is schema-driven, so you define the fields (balances, transactions, account holder) and MiruIQ extracts them from any bank's layout without per-bank templates. Complex transaction tables are handled, including statements where notes change how the numbers must be read.
ID documents, registry extracts and statements are extracted into structured data on your infrastructure or in Swiss hosting, with local AI models if required: nothing has to leave your environment. Extracted identity data can then be checked against your systems or external registries, and every decision keeps an auditable trail.
See it on your own documents.
The 14-day free trial covers 200 documents: enough to define your schemas, run real files and measure the results before anyone calls you.