Kaaj vs Ocrolus (2026)
The decision is where you want the machine to stop: at clean data from the documents, or at a drafted credit memo. Ocrolus stops at the data. It reads bank statements, pay stubs and tax forms at roughly 750,000 applications a month, and its cash flow analytics feed the credit models of more than 175 small business funders, Enova, Square, PayPal and Bluevine among them. Its accuracy has outside backing: data capture is insured through Lloyd's of London, and in mortgage, Fannie Mae and Freddie Mac relief covers its income calculations. Kaaj goes further down the chain. Its agents take a broker's whole package, check the business against Secretary of State filings, read the statements, flag tampering and draft a source linked memo into Salesforce, LTi Aspire or Solifi in about five minutes. Its 99.7 percent statement accuracy is its own measurement. Kaaj does its own parsing, so the two rarely share a stack: a lender that already decides inside its own scorecard needs the feed, and one whose underwriters still assemble the file by hand needs the memo.
- Your underwriters still build the file by hand. Kaaj takes the package as it arrives, by forwarded email, form or API, sorts it, verifies the business and drafts a source linked credit memo for review, so the output is a decision file rather than a data feed.
- You lend in equipment finance or through brokers. Kaaj syncs into Leasepath, LTi Aspire and Solifi as well as Salesforce, Microsoft Dynamics and HubSpot, and its named customers, Quality Equipment Finance, Harbour Capital and Amur among them, are lessors, brokers and specialty lenders.
- You want business verification inside the same review. Kaaj checks Secretary of State filings, web presence and address signals and keeps each finding sourced in the memo, next to merchant cash advance stacking and NSF analysis on the statements.
- Seat pricing is a problem. Kaaj prices on a platform fee plus application volume or usage credits and states that it does not charge per seat, so sales, credit and operations can all work the same deal.
- You already decide inside your own models. Ocrolus delivers income, cash flow and fraud data into your scorecard and origination system through public APIs, and its cash flow analytics already feed the credit models of more than 175 small business funders.
- You need accuracy someone else has priced. Data capture accuracy is insured through Lloyd's of London, and in mortgage, income calculated through Fannie Mae's Income Calculator and Freddie Mac's AIM Check carries representation and warranty relief.
- You lend across products. Ocrolus covers mortgage, small business, consumer and auto lending on one platform, with Encompass integration in mortgage and Encore, a consent based network for brokers and funders to share cash flow profiles, in small business.
- Your vendor review runs on certificates. The security portal offers an ISO 27001 certificate, SOC 2 and SOC 3 reports, PCI DSS and CSA STAR Level 1, and lists its subprocessors, OpenAI among them, in public.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Kaaj and Ocrolus are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI FinTech Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Kaaj | Ocrolus | |
|---|---|---|
| Primary category | Credit Decisioning & Underwriting | Lending & Banking Operations |
| Founded | 2024 | Not published |
| Headquarters | San Francisco, California, United States | New York, New York, United States |
| Website | kaaj.ai | www.ocrolus.com |
Side by Side
| Axis | K Kaaj |
O Ocrolus |
|---|---|---|
| AI Centrality | ||
| Autonomy and Oversight Model | ||
| Model Risk Management and Transparency | ||
| Operational and Outcome Evidence | ||
| AI Safety and Data Stewardship | ||
| GLBA and Data Privacy Posture | ||
| Security Certifications and Trust Center | ||
| Regulatory Status and Licensure | ||
| AI Governance and Bias Disclosure | ||
| AI Liability and Recourse | ||
| Model Supply Chain Disclosure | ||
| Core Systems and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Commercial Transparency | ||
| Institution and Segment Coverage |
The short version of each
Kaaj
Kaaj runs a set of AI agents over a small business borrower's whole package, from a forwarded broker email to a source linked credit memo, in about five minutes. The agents classify documents, verify the business against Secretary of State filings, web presence and address signals, analyze bank statements for revenue, transfers, NSFs and merchant cash advance activity, flag tampered files and test the applicant against the lender's own policy. According to the AI FinTech Index, it publishes a measured parsing accuracy of 99.7 percent on live statements in September 2026, reconciled against printed totals, with no sample size and no outside test. Named customers include Quality Equipment Finance, Harbour Capital and Amur, and results sync into Salesforce, Microsoft Dynamics, HubSpot, Leasepath, LTi Aspire and Solifi. It states SOC 2 Type II compliance, runs on Microsoft Azure and names no model provider.
Source: AI FinTech Index, 2026
Ocrolus
Ocrolus reads the documents a borrower submits, from bank statements and pay stubs to tax forms and roughly a thousand other types, and turns them into income, cash flow and fraud data for lenders, at around 750,000 applications a month across mortgage, small business, consumer and auto lending. Its cash flow analytics feed the credit models of more than 175 small business funders, including Enova, Square, PayPal and Bluevine. According to the AI FinTech Index, its accuracy carries outside backing: data capture is insured through Lloyd's of London, and in mortgage its integrations with Fannie Mae's Income Calculator and Freddie Mac's AIM Check carry representation and warranty relief. Its security portal offers ISO 27001, SOC 2, SOC 3 and PCI DSS reports and names OpenAI among its subprocessors. Its published customer count fell from more than 500 to more than 400 between late 2024 and early 2026.
Source: AI FinTech Index, 2026
Common questions
Is Kaaj or Ocrolus better for bank statement analysis?
It depends on what has to come out the other end. Ocrolus returns structured transactions, cash flow analytics and fraud signals for your own models, with data capture accuracy insured through Lloyd's of London. Kaaj parses the statements itself, 99.7 percent without a material dollar error on its own September 2026 measurement, and carries revenue, transfer, NSF and merchant cash advance findings into a drafted credit memo. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Can Kaaj replace Ocrolus?
For a lender that wants a finished file, Kaaj covers the parsing Ocrolus would do and adds business verification and the memo. For a lender or platform that consumes document data through an API into its own decision engine, Kaaj itself states that it is not a drop in replacement for the Ocrolus API, and Ocrolus's range across mortgage, consumer and auto lending has no Kaaj equivalent. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
How accurate are Kaaj and Ocrolus?
Ocrolus states accuracy above 99 percent and insures its data capture accuracy through Lloyd's of London, so an outside underwriter has priced the error rate. Kaaj measured 99.7 percent of live statements parsed without a material dollar error in September 2026, reconciling parsed totals against printed totals, with no sample size and no outside test. Neither publishes accuracy by document type or borrower population, or an error rate for the analysis built on top of the extraction. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Which works better for equipment finance and broker lending?
Kaaj is built around it, with sync into Leasepath, LTi Aspire and Solifi, intake straight from broker emails and named customers such as Quality Equipment Finance, Harbour Capital and Amur. Ocrolus serves small business lending broadly rather than equipment finance specifically, and its Encore network lets brokers and funders share a processed cash flow profile, with both parties' consent, instead of raw statements. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Will Kaaj and Ocrolus pass a bank's vendor security review?
Ocrolus offers an ISO 27001 certificate, SOC 2 and SOC 3 reports on a half yearly cycle, PCI DSS and CSA STAR Level 1 through its security portal, and runs on Amazon Web Services. Kaaj states SOC 2 Type II compliance, runs on Microsoft Azure and keeps its report and policies in a trust center behind an access request. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Where does each publish the most, and the least?
Ocrolus publishes most on its customer results, its security certifications and the outside backing for its accuracy, and says little about pricing, bias and fairness or what happens when a borrower disputes a figure. Kaaj publishes most on its workflow, its customer results and its parsing accuracy, and says little about pricing, the models it is built on, its privacy terms or what a declined applicant can do. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Fraud Detection & Transaction Risk page.
Neither publishes prices. Kaaj describes its model, a platform fee with included volume and usage overages, and Ocrolus describes none. Neither says whether borrower files processed for one lender inform models serving another. That matters for Kaaj, whose broker customers send the same application to several lenders, and for Ocrolus, whose Encore network passes cash flow profiles between counterparties with both parties' consent.
Neither describes what a declined small business applicant is told or how a misread statement gets corrected, although ECOA adverse action notice rules reach business credit. Ocrolus names OpenAI as a subprocessor without saying which tasks it performs, and Kaaj's eight subprocessors include no model provider at all. Kaaj publishes its own Kaaj versus Ocrolus comparison. Its claim that Ocrolus human review takes 45 minutes to an hour is attributed to lenders Kaaj spoke with, not to any published Ocrolus service level.