Show false positives the door

Improve investigator efficiency with advanced post-processing that puts false positives in their place

Bar chart titled 'Alerts recommended for hibernation (numbers view)' showing counts for March to June 2023. The y-axis represents the number of TPs/FPs/UNKs recommended for hibernation, ranging from 0 to 80. Green bars indicate the number of false positives (FP), blue bars indicate unknowns (UNK), and red bars indicate true positives (TP). From March to May, the FP count is high (around 50 to 70), and the UNK count is low (around 4 to 7). In June, the FP count drops sharply while UNK count rises sharply. No red bars for TPs are visible.

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Two overlapping tables: the back table shows model information with columns for Model ID, Model Name, Description, and Status, listing models like WLM Detection Model and Production Snapshot with statuses 'Currently in Use' or 'Previously in Use.' The front table titled 'Match Exclusion Rules' shows columns for ID, Name, Description, Data Source, and Data Source Field, listing entries such as OSAMA BIN LADEN, John_Ru, ID with data sources like SWIFT and GenericTransaction and 'All' in Data Source Field.

Reduce false positives with Match Exclusion

Allow certain matches to be excluded by targeting known patterns of false positives for specific watchlists, while retaining a strong audit trail.

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Screenshot showing parsed SWIFT message fields with Name and Value columns listing codes and data such as FISA103I00073, amount 10300073, currency EUR, and Ordering Customer details. Below, an alert table displays a checked alert A2404064444 labeled as Electronic Transfer with description New Alert, age 43 days, assigned to System User, and priority Medium.

Prioritize the greatest risk

Streamline investigations with machine learning models that score alerts to automatically prioritize true positives while auto-hibernating known false positives.

Two overlapping user interface panels displaying subject data details and data source fields. The left panel lists fields such as delta_record_flag set to Y, timestamp 2023-12-13 19:57:51, organization EUR, address 20 Salway Road, city London, country United Kingdom, country code GB, date of birth 1985/04/21, subject ID CUST-EU-110, name Fethi Al-Haddad Ben Hassen, place of birth Birmingham, and role CUSTOMER. The right panel shows subject details including type Personal, category Retail, full name, subject ID CUST-LIST-110, tax number 1111111111, address with postal code, email, and phone number, with options to add notes.

Look beyond name matches

Empower investigators and enable faster decision-making and disposition with advanced post-processing that consolidates the context, history, and risk of transactions on a single screen.

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Reduce false positives by 80% with AI Overlay for Screening

Enhance screening accuracy with the power of predictive and generative AI to significantly reduce false positives. AI Overlay for Screening is included as standard in our Name and Transaction Screening solutions.

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Screenshot of a web interface showing a steps list with columns for Validation Required and Step, indicating which steps require validation with Yes or No. Steps include A: Filing Type, B: Select Financial and Filing Institutions, C: Filing Institution Details, D: Financial Institution Details, E: Subjects, F: Accounts, G: Transactions, H: Activity Details, I: Commodity Types (Optional), J: Product/Instrument, N: Contact Details, O: Narrative, and P: Attachment (Optional). Buttons labeled Delete, Preview, Submit, Add To E-File, and options to Submit or Decline under Matching Disclosures are visible.

Simplify regulatory reporting

Satisfy regulatory obligations with automated out-of-the-box reports for FinCEN CTR and FinCEN SAR amongst others.

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Screenshot of SymphonyAI Investigation Hub showing financial transactions for John Rolands with a chart of credits and debits from June 2022 to May 2023. Below the chart is a list of transactions dated March 27, 2023, including debit and credit wire transfers of USD 9,539.00 to John Rolands. Beside this, a chat interface displays a user's question about suspicious foreign credits from a known offender and an AI Copilot response detailing a suspicious $65,000 credit linked to John Doe from the Cayman Islands, noting a bank fraud conviction and a March 5, 2023 wire transfer labeled 'loan repayment.' Chat contains buttons to show subject risk and recent transactions.

SRI Investigation

Integrate screening with AI-powered case management

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

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Discover more features and functionality of Sanctions Screening

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Solution benefits

Improve detection accuracy

Identify sanctioned entities, PEPs and high-risk individuals and rapidly screen, detect and track beneficial owners and their linkages in real-time.

Accelerate investigations

Maximize investigator efficiency by automatically enriching and prioritizing the most high-risk alerts while significantly reducing false positives.

Enhance customer experience

Intelligent matching and AI-driven analytics goes beyond pure name matches to ensure real-time onboarding and instant payment processing are not hindered by unnecessary friction points.

Scalable compliance

Comply with global watchlist enforcement regulations, respond to regulatory changes in real-time, and easily configure to suit your requirements.