Payment Fraud

Perform entity-based risk evaluations

Expose hidden payment fraud by linking fragmented behavioural patterns that remain hidden in isolated signals

User interface showing buttons labeled Acquit, Confirm, Assign, Request Info, and Refer alongside a table with columns Alert Identifier, Description, Created On, Type/Sub-Type, Priority, Status, Web Event ID, and Web Event Type, displaying an alert with ID PF_1904202300026577, description referring website, creation date 19/04/2023 15:44:42, type Online, high priority, closed automatic status, and a web event ID link labeled WEBEVE-20210711-141524-00000231 of login event type.
A large translucent pale blue gradient circle on the right side fading into white.
Screenshot of a financial alert interface showing two alerts for AML Correspondent Banking with identifiers A2022062523509 and A2022062223516, both with description CB014: The customer trans. A separate parsed data panel shows SWIFT message details including amount 100013 EUR and sender as BANCO NACIONAL DE CUBA, Federico Boyo Avenue & 51 Street, Panama City, PANAMA.

Connect risk signals across multiple channels and payment types

Provide investigators with all risk event information in one place for faster, more effective risk evaluations.

Screenshot of a financial software interface showing recent originator payments for customer Eugene Gadson. The highlighted row shows an outbound credit transfer payment of EUR 10,999 on 19/04/2023 at 14:47 via mobile banking, with account debited as ACC100001ACC belonging to Eugene Gadson and account credited as ACCT-FRN-1002568. An overlay displays beneficiary account details for account ACCT-FRN-1002570 named RoryAir, a business account with routing number 100000640, sort code 3570, IBAN IE31SFEO35042312966030, BIC 9999-761264, account age, and monitoring and exemption status indicated as No.

Enable faster level 1 payment triage

Ensure all information and actions are readily available for a decision on a held payment within 90 seconds.

Screenshot of a monitoring dashboard displaying alert details and detection results. The top section shows a table with alert identifiers, types, descriptions including flagged entities like BANCO NACIONAL DE, AL RASHEED BANK, and suspicious names in lists, assigned to system users with high priority marked. The bottom overlapping window titled Detections offers options to mark alerts as Suspicious or Not Suspicious, showing a default view with columns for score, time period, event date, reason explaining AML credit monitoring, and scenario name AML22 Growing credit averages.

Connect fraud with AML and expose hidden signals across risk typologies

Seamlessly integrate payment fraud with transaction monitoring detection, enabling fraud activities to expose signals for money laundering behavior and vice-versa.

Screenshot of a software alert interface showing one fraud alert for a payment transaction exceeding 200,000 euros, and a pop-up window with originator account details including Account ID ACC100005ACC, Account Name One Holiday, SME account type, branch name, routing number, sort code, IBAN, BIC, account age, and account monitoring status.

Provide investigators with all the context they need

Enable longer-running forensic investigations to build a book of evidence for each customer or incident and create searchable repositories of bad actors across all financial crime types.

SymphonyAI Investigation Hub user interface displaying investigation details for John Rolands, including a narrative describing suspicious activity with incoming and outgoing wire transfers, and an action list on a mobile screen with steps like checking web results, reviewing transactions, and uploading proof of identity documents.
SRI Investigation

Integrate payment fraud with AI-powered case management

Unify your enterprise-wide risk and compliance tech stack and arm every investigator with a generative AI-powered assistant.

Discover more features and functionality of Payment Fraud

Close-up of a smooth, curved, spiral-shaped gray object against a blurred light gray background.

Solution benefits

Prevent fraud at the source

Significantly reduce fraud losses with real-time fraud detection that identifies and stops bad actors in their tracks.

Enable faster customer journeys

Remove unnecessary friction and only invoke processes like step-up authentication when needed.

Share intelligence seamlessly

Easily share risk and case information across fraud, risk, and compliance functions for a holistic approach to risk management.

Adapt detection models in-house

Enable in-house teams to easily create, configure or fine-tune detection models with self-service capabilities.