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REMI AI Delivers Financial Crimes to Forensics Report in Minutes.

RemiFetch uses AI to rapidly detect the most common and high-impact financial crimes—analyzing activity across accounting systems, payment platforms, and financial records to identify fraud, theft, and suspicious transactions in minutes.

But detection doesn’t stop at a single system. RemiFetch correlates financial activity across accounting packages and personal banking applications—linking transactions, tracing payment flows, and uncovering how funds move between accounts. This cross-source visibility enables investigators to follow the money, identify hidden relationships, and understand the full scope of financial misconduct.

The result is faster detection, deeper insight, and a clear, evidence-backed view of financial activity across both business and personal financial environments.

  • ✓ Detects the top fraud, theft, and financial crime patterns automatically
  • ✓ Analyzes accounting systems, payment platforms, and transaction data
  • ✓ Correlates activity with personal banking apps to trace payments
  • ✓ Follows the movement of funds across accounts and financial systems
  • ✓ Identifies hidden relationships between transactions and entities
  • ✓ Detects anomalies, unusual transfers, and suspicious financial behavior
  • ✓ Produces evidence-backed findings and transaction-level reporting

Import Corporate Ledgers, Bank Records, and Pay Apps. Get an Evidence-Backed Forensics Report in Minutes.

REMI Financial is built for speed when the evidence is messy. Instead of manually separating corporate ledgers, bank records, payment-platform exports, and supporting files before an investigation can even begin, examiners can place the mixed financial evidence into one case package and move it directly into the pipeline. REMI Financial cleans, sorts, categorizes, and normalizes the records automatically, then carries the case forward through analysis and reporting. The result is a faster path from scattered exports to an evidence-backed financial reconstruction, helping investigators spend less time preparing data and more time understanding what happened.

Remi uses behavioral 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-assisted 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.

✓ Account Takeover and Unauthorized Access
✓ Accounting Manipulation and Ledger Abuse
✓ AI-Assisted Fraud and Synthetic Deception
✓ Audit Concealment and Evidence Suppression
✓ Crypto Wallet Movement and Digital Asset Laundering
✓ GeoIP, Device, and Infrastructure Anomalies
✓ Insider Approval Abuse and Privilege Misuse
✓ Ledger-to-Personal Banking Diversion
✓ Merchant Refund and Chargeback Abuse
✓ Money Laundering, Structuring, and Layering Activity
✓ Money Mule and Pass-Through Account Behavior
✓ Payment Diversion and Beneficiary Manipulation
✓ Personal Banking and Pay App Fraud Patterns
✓ Synthetic Identity and KYC Evasion
✓ Vendor and Accounts Payable Fraud

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 THE CONNECTIONS GAIN MEANING

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.

AI Generated Reporting

Our financial reporting suite delivers transaction analysis, ledger validation, access auditing, payment fraud detection, identity verification, and cross-system correlation—transforming fragmented financial data into a clear investigative narrative.

  • Identity & Entity Analysis
  • Financial Crime & Laundering Analysis
  • Core Financial Reports
  • Accounting & Ledger Analysis
  • Payments & Transfer Analysis
  • Artifact & Intelligence Reports
  • Transaction & Activity Analysis

Accounting Systems Detections

Accounting AI analyzes QuickBooks and NetSuite activity beyond basic rule checks—reviewing ledgers, journal entries, AP/AR flows, and user actions to detect fraud behaviors like approval bypasses, duplicate vendors, and unusual timing. It correlates related transactions and account activity to reveal hidden relationships between vendors, employees, and payments that are hard to spot inside a single system. The result is an evidence-backed trail showing what changed, who initiated it, and why the pattern indicates potential theft or misconduct.

Pay Apps Detections

AI traces pay-app activity by starting with QuickBooks/NetSuite ledger and payment records, extracting the invoice/bill, vendor/customer, amount, and processor references tied to each disbursement or receipt. It then correlates those identifiers to PayPal/Venmo/Stripe events (payouts, transfers, fees, chargebacks) and reconciles net-of-fees settlement amounts against personal bank statement deposits/withdrawals using ACH descriptors, trace numbers, and posting dates. The result is an evidence-backed chain—ledger entry → pay-app transaction → bank settlement—that exposes suspicious movement patterns like split transfers, rapid pass-throughs, round-trips, or timing anomalies designed to obscure who received the funds.