REMI AI Delivers Financial Crimes to Cyber SITREP Report in Minutes.
Financial crime investigations often involve records scattered across accounting systems, payment platforms, bank accounts, vendors, and approval workflows. REMI AI brings those sources together and generates a cyber SITREP that explains the situation in plain English. It identifies what happened, how it happened, who or what was involved, where the money went, what losses or exposure are visible, and which records prove the sequence.
Instead of manually comparing ledgers, bank statements, pay-app activity, invoices, approvals, and transaction logs one source at a time, REMI analyzes the full evidence set together. The result is a clear, evidence-backed report package that helps investigators understand the financial event, trace the money movement, identify suspicious behavior, and decide what to review or preserve next.
Supported Financial Sources
Accounting: QuickBooks, NetSuite, Xero, Sage, FreshBooks, Microsoft Dynamics, ledger exports, journal entries, AP/AR records.
Banking: Bank statements, ACH records, wire records, check images, deposits, withdrawals, account histories.
Payment Apps: Stripe, Square, PayPal, Venmo, Cash App, Zelle, merchant processors, payout reports, refunds, chargebacks.
Vendor + Approval Records: Invoices, purchase orders, vendor master files, payee changes, approval records, supporting documents, settlement reports.
REMI Analyzes Every Financial Source at the Same Time
REMI Financial brings together ledgers, bank statements, payment apps, invoices, approvals, vendor records, and transaction exports to produce one forensic view of what happened.
Financial investigations rarely live in one system. Ledgers show what was recorded, payment apps show how funds moved, and bank statements show where the money actually landed. REMI Financial analyzes those sources together, across platforms such as NetSuite, QuickBooks, Square, Stripe, PayPal, Venmo, Cash App, Citibank, Chase, Wells Fargo, and other financial systems.
Instead of reviewing each report separately, investigators can import all available financial records into REMI at the same time. REMI connects related transactions, vendors, accounts, approvals, refunds, deposits, withdrawals, transfers, payment references, settlement records, and ledger changes into a single evidence-backed reconstruction. The result is a clear report package that explains what happened, who or what was involved, how the money moved, what records support the findings, and what questions or documents still need follow-up.
Remi uses behavioral, pattern and correlation analysis to identify fraud, thefts and crimes
REMI Financial scans for high-risk fraud behaviors across the full transaction and account lifecycle, turning raw financial records into evidence-backed findings. Detection coverage includes account takeover, accounting manipulation, AI-automates fraud, audit concealment, crypto movement, GeoIP and infrastructure anomalies, insider misuse, ledger-to-personal diversion, refund and chargeback abuse, money laundering and structuring, mule-account behavior, payment diversion, personal banking and pay app fraud, synthetic identity abuse, and vendor or accounts-payable fraud.
REMI Financial reconstructs what happened, shows how the money moved, identifies who and what was involved, calculates exposure and damages, and cites the records that support each finding.
See How Entities, Payments, and Transfers Connect
Advaned Coorelation is where the story begins
Correlation is where scattered financial activity becomes a fraud case. In larger theft, embezzlement, diversion, and laundering investigations, the evidence is rarely confined to a single ledger or account. It is distributed across accounting records, bank movement, payment apps, settlement activity, user actions, and supporting documents that must be connected in sequence to show how the scheme worked, who participated, who benefited, and where the money went. REMI Financial correlates those records into one evidence-backed chain, helping government investigators identify fraud circles, linked accounts, coordinated actors, concealed relationships, movement of funds, and indicators of intent. The result is a faster path from raw financial data to a defensible reconstruction that can support referral, enforcement, recovery, and prosecution.
Analysis Is Where Correlations Gain Meaning and the “How It Happened” Story Surface
After correlation reveals the relationships, analysis explains the meaning: what happened, how money moved, who was involved, what records changed, and what evidence proves it.
Analysis is where the narrative moves from connected records to investigative meaning. Correlation can show that transactions, accounts, entities, and user actions are linked, but analysis helps explain how the scheme functioned, who likely played which role, whether the behavior reflects coordination, concealment, layering, pass-through movement, or fraud-circle activity, and what evidence best supports those conclusions. It extends the narrative by adding judgment, context, and prioritization, helping investigators understand not only what happened, but how the conduct was carried out, who benefited, and which leads are most important to pursue next.
View Our Use Cases
A regional bank’s fraud operations team received complaints from multiple commercial customers that approved vendor payments had not reached the intended vendors. The customers reported that invoices appeared legitimate, approvals were recorded in their accounting systems, and payments were released through normal banking channels.
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Shell Companies Move $14.2M Through Pass-Through Accounts and Offshore Entities
Federal investigators receive a referral after a corporate audit, bank alert, and customer complaint point to the same problem: money that should have remained inside normal commercial payment channels moved through newly formed entities, domestic pass-through accounts, payment processors, and offshore destinations. Several entities appear legitimate on paper, but their formation dates, bank details, invoice descriptions, and transfer timing do not match the normal business purpose of the payments appear legitimate on paper, but their formation dates, bank details, invoice descriptions, and transfer timing do not match the normal business purpose of the payments.
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Hidden Revenue and Offshore Transfers Points to Tax an Evasion Scheme
A regional business reported unusually low taxable income despite strong sales activity, large customer deposits, increased inventory movement, and continued expansion. The first concern appeared when a bank review, customer-payment records, and tax-support schedules did not agree with the company's accounting exports.
Revenue appeared to be split across operating accounts, merchant processors, related entities, and offshore transfers before some funds were later reintroduced as loans, consulting payments, or owner distributions.