How Automated Bank Statement Parsing for Thai P2P Lending Cuts Credit Risk Processing to 90 Seconds

It is an intelligent technology workflow that extracts transaction data from Thai mobile banking app screenshots and translates it into standardized JSON payloads to feed automated underwriting credit models without manual data entry.

Manual verification takes up to 45 minutes per statement, introducing a 5% to 8% risk of input errors. It creates massive queues, higher operational costs, and results in a 30% borrower dropout rate due to long wait times.

It uses an advanced image preprocessing pipeline that includes bilateral filtering, adaptive binarization, and horizontal alignment corrections. This allows the system to clean background noise, overcome fonts, and resolve tilted angles found in KBANK, SCB, and Krungsri screenshots.

The JSON Schema structures unstructured textual outputs from the OCR engine into clean, readable parameters. This standardized payload can be read immediately by credit scoring engines to compute debt-to-income ratios and identify risk metrics.

The parsing engine secures client data in alignment with PDPA and BOT rules through automatic data masking of sensitive personal details, secure cryptographic transfer protocols, and strict data retention periods that erase raw documents within 30 days.