Jenfi announced upgrades to its in-house bank-statement analysis and underwriting infrastructure to support faster financing decisions for small and medium-sized enterprises (SMEs) across Singapore and Vietnam. The enhancements combine AI-assisted document extraction, transaction reconciliation, and document-risk checks, supporting Jenfi's ability to provide same-day underwriting decisions for qualified applicants.

For businesses managing time-sensitive working capital needs, a prompt decision helps them plan inventory purchases, supplier payments, and other operating expenses with greater clarity. On the lender side, that speed is only as reliable as the document pipeline behind it: every application depends on converting raw bank records into data a credit team can trust and act on.

The upgrades address a practical challenge in SME underwriting: converting financial records submitted across different banks and document formats into structured information that credit teams can check and assess. The workflow is already in use within Jenfi's bank-statement review process.

The enhanced infrastructure connects three capabilities:

• Hybrid document extraction: Deterministic parsers and an AI fallback support processing across PDF and Excel bank statements. Extraction results can be reused, reducing the need to repeat document-processing steps.
• Financial-data verification: Transaction reconciliation checks the consistency of extracted information, while document-fraud checks flag potential irregularities for further assessment.
• Traceable review: Processing status, document-risk status, and AI-assisted review outcomes are visible separately, with inconclusive cases escalated for human assessment.

"Our approach combines rules-based processing, AI-assisted extraction, and reconciliation checks, with clear escalation when a document needs further assessment," said Justin Louie, Co-founder and Chief Technology Officer of Jenfi. "The goal is to give our credit team structured information they can inspect, alongside visibility into unresolved issues and the review steps taken."

In September 2026, Jenfi introduced separate processing, fraud-review, and AI-assisted review states within its bank-statement workflow. The change gives reviewers clearer visibility into whether a document is awaiting extraction, requires assessment of a potential irregularity, or has produced a review outcome that requires action. That separation helps the team distinguish a processing problem from an unresolved document-risk flag and determine the appropriate next step. The distinction matters in practice: processing issue points to work that still needs to be completed on a document, while a risk flag requires assessment before it can inform a credit decision.

Credit teams review flagged or inconclusive cases and retain responsibility for accepting documents. In this setup, the automated components assist with extraction, reconciliation, and flagging, while the decision on whether to accept a document stays with human reviewers.

Developing the processing and verification workflow in-house gives Jenfi greater control over document coverage, extraction logic, and exception handling. The company can adapt these components as new statement formats and operational requirements emerge. That adaptability is the practical angle to watch: as borrowers submit statements in new formats across its Singapore and Vietnam operations, the in-house setup's ability to absorb those changes will bear directly on whether same-day decisions remain within reach for qualified applicants.