Cloudvirga has introduced a cash flow analysis tool designed to automate the review of bank statement income, a process commonly associated with Non-QM and alternative documentation lending.
The feature is integrated into the company’s Tropos point-of-sale platform and is intended to assist with evaluating income for borrowers with nontraditional earnings, including self-employed individuals and gig workers.
According to the company, the tool analyzes bank statement data to identify and categorize deposits, producing income summaries that can be used to support loan qualification. The process, which is typically performed manually, can take several hours; Cloudvirga said the tool is designed to complete the analysis in a matter of minutes.
Income calculation for bank statement loans has historically required manual interpretation of cash flow patterns, which can vary widely across borrowers. The introduction of automated analysis tools reflects a broader effort within the mortgage industry to standardize elements of nontraditional income evaluation — particularly as lenders expand their focus on Non-QM borrowers and more complex financial profiles.
Recent developments across the sector point to increased investment in automation for these use cases. A newly launched platform from JAUST, for example, applies real-time guideline logic to streamline underwriting decisions in jumbo and Non-QM lending, with the goal of reducing costs and accelerating loan processing.
At the same time, lenders and brokers are increasingly pairing Non-QM growth strategies with in-house or integrated technology. Firms focused heavily on Non-QM production have begun developing proprietary AI tools to handle complex borrower scenarios and improve efficiency in high-volume environments.
Cloudvirga said the tool is not intended to replace underwriting standards or lender-specific guidelines. Credit decisions remain subject to each lender’s criteria and program requirements.
Instead, the technology is positioned as a workflow enhancement that can be used during early stages of the loan process, including prequalification and structuring, where faster income assessment may help determine borrower eligibility.
The release comes as lenders and technology providers continue to expand the role of artificial intelligence across mortgage origination, with a growing emphasis on embedding automation within core processes such as income analysis and underwriting support.
