Reviewing bank statements manually can mean going through hundreds of transactions one by one. In its Bank Statement Analyzer update, Sxored describes analysts trying to identify cashflow patterns, transfers between related parties, and suspicious activity within that volume of information.
Important signals can be difficult to see in unstructured data. The update highlights window dressing, irregular transactions, and manipulated cashflow patterns. Sxored links overlooked signals to poorer credit decisions, greater fraud exposure, and longer analysis time.
Turning transaction data into financial insights
The problem described is limited visibility into the data. Sxored presents Bank Statement Analyzer as a way to organise complex bank statements into structured financial information that is easier for credit teams to analyse.
The announced capabilities include:
- Detection of fraud indications.
- Cashflow netting.
- Automated transaction categorisation.
- Identification of related-party transactions.
Together, these functions help credit teams work faster with a clearer view of risk. The update centres on making financial data easier to understand as the starting point for better credit decisions.
Read the original Bank Statement Analyzer update.
