Data Sources

Account Activity Logs record every financial transaction and account setting change, capturing timestamps, user identifiers, and related metadata essential for uncovering anomalies and suspicious behaviors. They are critical for AML/CFT threat modeling, helping trace illicit fund flows and identify potential money laundering or terrorist financing activities.

PEP lists catalog individuals in or with close ties to prominent government roles, capturing their official positions and notable affiliations. This data source is integral for AML/CFT threat modeling, enabling institutions to identify and monitor high-risk exposure to bribery, corruption, or illicit financial activities.

Adverse Media & Court Filings compiles negative news, legal actions, and related misconduct records from media outlets and official court documents, offering critical insights into potential illegal activities or reputational risks essential for AML/CFT threat assessments.

Customs and Border Records provide detailed insights into the cross-border movement of goods and individuals, capturing shipping routes, tariffs, and related documentation. These records are integral to detecting and investigating trade-based money laundering, illicit trafficking, and other complex cross-border financial crimes.

This dataset consolidates country-specific AML/CFT laws, regulations, and enforcement practices to identify high-risk regions and detect anomalies in financial transactions. By highlighting geographic and jurisdictional vulnerabilities, it is instrumental in assessing and mitigating AML/CFT threats.

Professional Licensing & Affiliation Databases provide oversight of valid professional roles and memberships, offering critical intelligence for verifying individuals’ credentials and identifying suspicious affiliations. They enhance AML/CFT threat modelling by uncovering unauthorized activities, enabling more effective detection of potential illicit networks.

Financial, Business & Tax Records furnish verifiable insights into an entity’s financial health and transactions, enabling AML/CFT professionals to spot discrepancies, validate reported performance, and identify potential anomalies indicative of illicit activity.

This data source captures critical digital channel indicators—including IP logs, device fingerprints, and suspicious login attempts—that help institutions detect and investigate unauthorized transactions or anomalous activities. It bolsters AML/CFT threat modeling by providing key insights into potential cyber-enabled fraud, money laundering, and terrorist financing schemes occurring via online and mobile banking.

Commodity Market Data provides historical and current information on commodity prices, indices, origins, types, and values, enabling financial institutions to cross-verify the legitimacy of commodity-related transactions. In AML/CFT adversarial threat modelling, this data is crucial for detecting anomalies and uncovering potential trade-based money laundering activities.

This dataset provides holistic insights into how customers engage with financial offerings, capturing key metrics such as product usage frequency and transaction volumes. In AML/CFT threat modeling, it is crucial for detecting anomalies and suspicious activity patterns indicative of potential money laundering or terrorist financing.

Open-Source Intelligence (OSINT) leverages publicly available data from websites, social media, news outlets, and public records to verify identities and uncover associations. In AML/CFT threat modelling, it provides critical insights into potential illicit networks and suspicious financial activities, thereby enhancing due diligence and risk mitigation.

Trust Information and Accounts provides detailed data on the structure, beneficiaries, trustees, and financial histories of trusts, enabling thorough validation of trust-related activities. This information is critical for verifying identities, detecting suspicious transactions, and mitigating money laundering or terrorist financing risks.

Contractual and Invoice Data provides detailed insights into the nature and legitimacy of commercial relationships by capturing terms, parties, and transaction details. This information is essential in AML/CFT adversarial threat modelling to verify business authenticity, trace suspicious payments, and detect potential illicit financing activities.

Currency Exchange Transactions capture the detailed mechanics of currency conversion activities—including trades, parties, rates, volumes, and settlements—and enable the identification of suspicious patterns and potential cross-border movements that may signal money laundering or terrorist financing risks.

Customs and Asset Seizure Records provide official details on confiscated goods, financial assets, and the parties involved, enhancing visibility into cross-border illicit flows or suspicious activities. This information is crucial for identifying high-risk networks and potential legal or regulatory actions within AML/CFT adversarial threat modelling.

Legal Documentation & Records provide authoritative evidence of parties’ rights and obligations in financial transactions, helping to validate ownership structures, legal relationships, and compliance obligations. By offering verifiable proof of lawful standing, they support the early detection and mitigation of suspicious activities in AML/CFT adversarial threat modeling.

Prepaid Card Transaction Data offers insights into transaction amounts, frequencies, identifiers, and usage patterns of prepaid cards, providing a critical basis for detecting potentially suspicious transactions and identifying emerging threat patterns in AML/CFT analysis.

Sanctions lists are official records of individuals, entities, and jurisdictions subject to financial or trade restrictions due to concerns like terrorism, proliferation, or human rights violations. These lists are essential for AML/CFT/CPF programs, helping institutions screen customers and transactions to prevent dealings with prohibited or high-risk parties.

Transaction Logs provide comprehensive financial transaction records across all channels, capturing essential account details, transactional timestamps, amounts, currencies, and identifying information. They are pivotal in AML/CFT adversarial threat modeling by enabling the detection of suspicious patterns, tracing the flow of funds, and strengthening compliance monitoring.

These databases consolidate verified identity information, entity status, and beneficial ownership details from multiple sources, enabling comprehensive due diligence and risk assessments. Their use ensures more accurate identification of suspicious activity and helps prevent misuse of financial systems for illicit purposes.

Document Management Systems centralize and secure sensitive records such as KYC files and contracts, offering version control, access permissions, and audit trails. In AML/CFT adversarial threat modeling, they play a key role by enabling oversight of document integrity and user activities, helping detect unauthorized access or alterations.

This data source consolidates records from various digital payment platforms and e-wallets, offering detailed transactions, user identifiers, and operational metadata. It is critical for detecting high-risk behaviors, pinpointing suspicious patterns, and tracing illicit flows in digital payment networks within AML/CFT threat modeling.

Bank Account Data provides detailed account information—such as account numbers, ownership details, balances, and transactions—essential for tracing illicit financial flows and identifying potential money laundering or terrorist financing activities. This data is critical for AML/CFT threat modeling because it reveals patterns of suspicious transfers and helps pinpoint high-risk individuals or entities.

Asset Declarations offer a verified snapshot of an individual’s or entity’s wealth, assisting AML/CFT professionals in detecting inconsistencies between declared and actual financial positions. By illuminating potential discrepancies or unexplained assets, they support the identification of suspicious financial activities, such as money-laundering or terrorist financing.

System & Network Access Logs provide a comprehensive record of user activities, authentication events, and traffic patterns, forming a critical evidence source for detecting and investigating potential AML/CFT threats. Their detailed audit trails enable stakeholders to identify unauthorized access, abnormal behavior, and early indicators of malicious tactics, strengthening overall defense mechanisms.

Donation platform and donor records offer detailed insights into individual contributions, including donor identities, amounts, dates, and intended purposes, which help detect suspicious patterns, fund flows, or potential misuse in support of illicit activities.

Document Verification services confirm the legitimacy of official identification documents, detecting forgeries and inconsistencies to mitigate identity fraud risk. Integrating these checks into AML/CFT frameworks fortifies KYC processes and compliance efforts against illicit finance.

Employee Records capture detailed information on employees’ identities, roles, and employment histories, enabling monitoring for insider threats and conflict-of-interest red flags. They are critical in AML/CFT threat modeling to help maintain internal accountability and prevent misconduct.

Money Service Business (MSB) Registries provide authoritative lists of licensed MSBs or remittance providers, detailing their license status and operational scope. Such information is critical for AML/CFT threat modeling to verify legitimate operators, detect unauthorized activities, and identify potential risk patterns in financial transactions.

Business Activity and Operations data offers insights into a company’s revenue, expenses, and operational metrics, enabling the comparison of actual activity to reported financial information. These comparisons help uncover potential anomalies or discrepancies, facilitating the detection of money laundering or terrorist financing risks in AML/CFT threat modelling.

Financial audits offer a critical, independent assessment of an organization’s financial statements and internal controls, helping identify inaccuracies or compliance gaps that may signal money laundering or terrorist financing risks. Their robust, external perspective makes them a key data source in AML/CFT adversarial threat modeling, informing risk assessment and mitigation strategies.

Loan agreements and credit facilities document key borrower details and credit terms, enabling financial institutions to detect irregular repayment or usage patterns that may indicate money laundering or terrorist financing.

Fraud Data captures critical intelligence on emerging and known fraudulent activities—such as identity theft, payment card fraud, and scam patterns—providing valuable insights into adversarial tactics and risk indicators. It enables financial institutions to proactively detect, assess, and counter evolving threats within AML/CFT frameworks.

Safe Deposit Box Access Records provide a chronological log of individuals’ box entries, including their identities, time, and date of access. This information is crucial for detecting suspicious usage patterns, linking individuals to potential illicit activities, and supporting AML/CFT investigations.

Financial Instrument & Securities Market Data provides real-time and historical details for a wide range of investment vehicles, enabling the identification of abnormal price fluctuations and trading volumes. Its comprehensive coverage of instruments and market trends is critical in detecting suspicious transactions and potential money laundering or terrorist financing activities.

Trade Documentation, encompassing shipping logs, customs declarations, bills of lading, and related records, is crucial for validating cross-border transactions and uncovering potential trade-based anomalies. In AML/CFT adversarial threat modeling, these documents enable the detection of suspicious patterns and discrepancies that may indicate illicit trade-financing and money laundering schemes.

Job Recruitment Data provides insights into unusual hiring practices, such as the recruitment of money mules, supporting the detection and disruption of potential money laundering or terrorist financing activities. By examining candidate applications and employment details, investigators can identify suspicious patterns that signal illicit financial flows.

VASP data delivers granular insight into digital asset transaction patterns, user accounts, and exchanges, enabling detection of suspicious cryptocurrency activities. This detailed transactional and user behavior information is critical for identifying and mitigating money laundering and terrorist financing risks in virtual asset ecosystems.

KYC and Customer Due Diligence Records provide verified identities, beneficial ownership details, and in-depth financial and business activity information, serving as a key dataset for detecting and assessing risks in AML/CFT adversarial threat modeling. This dataset underpins customer profiling, supports compliance checks, and enhances anomaly detection across financial transactions.

ATM Usage & Geolocation Data provides vital insights into customers’ transaction patterns—combining location, timing, and transaction metadata—to identify high-risk activities, suspicious withdrawals, or structuring attempts. By analyzing this granular data, financial institutions can enhance AML/CFT adversarial threat modeling through early detection of anomalous behavior tied to money laundering and terrorism financing.

Casino and Gambling Transaction Records provide a comprehensive view of gambling activities—covering game types, betting frequency, transaction amounts, participant identities, and deposit/withdrawal data—enabling investigators to detect high-risk patterns, uncover suspicious flows, and identify potential money laundering or terrorist financing schemes.

Communication Records provide critical metadata and, where permissible, content of electronic interactions that uncover potential insider collusion, suspicious instructions, or other high-risk exchanges. By tracing communication patterns among individuals and entities, this data source enables targeted AML/CFT threat detection and investigation.

This data source offers comprehensive details on real property and high-value asset ownership, including transaction dates, purchase values, and beneficial ownership information. It is critical for tracking hidden or complex asset holdings in AML/CFT threat modelling, helping to detect illicit financial flows and flag possible money laundering activities.

Commodity Transaction Data captures comprehensive details of commodity trades—including dates, parties, types, quantities, and prices—enabling verification of transaction legitimacy and scope. This data source is crucial for detecting anomalous or suspicious flows in trade finance, supporting effective AML/CFT threat assessments.

This data source provides critical visibility into the flow of digital assets by capturing transaction IDs, timestamps, wallet addresses, and transaction amounts on public blockchain ledgers. It is essential for tracing illicit activities, identifying high-risk entities, and detecting patterns of money laundering or terrorist financing attempts involving cryptocurrencies.

Exchange & Trading Activity Records offer detailed insights into securities, commodities, derivatives, and cryptocurrency transactions, capturing key data points like trade volumes, dates, counterparties, and compliance indicators. They are critical for detecting potential illicit flows, anomalies, and patterns relevant to AML/CFT adversarial threat analysis.

This dataset offers critical insight into cross-border money flows, including transaction details, institutional partnerships, and account relationships, enabling the detection of complex laundering structures and jurisdictional risk. By tracing the movement of funds and identifying high-risk or sanctioned endpoints, investigators can more effectively uncover and mitigate global money laundering and terrorism financing networks.

Geographical Transaction Data captures origin, destination, timing, amounts, and geolocation metadata for financial transactions, enabling the detection of suspicious cross-border flows. By highlighting jurisdictional interactions and transaction pathways, this data source is crucial for spotting potential AML/CFT threats and unraveling complex illicit networks.

Company & Beneficial Ownership Registries consolidate key organizational data—including formation, shareholder and director details, and ownership structures—into a single authoritative source. They are crucial for uncovering hidden ownership networks and potential shell entities, making them an essential resource in AML/CFT adversarial threat modelling.

Aggregated device-ID, browser-fingerprint and behavioural-biometric telemetry captured during digital-channel sessions, enabling linkage of seemingly unrelated accounts controlled by the same automation tool.

Detailed audit trails of programmatic payment instructions (open-banking APIs, SFTP/Bulk files), including client ID, token scope, job status and payload metadata, essential for detecting scripted mass-payment behaviour.

Daily or monthly acquiring-bank files that list gross card-sales volumes, refund totals, and terminal IDs for a merchant.