Information Sharing

Definition

Information sharing refers to the structured, lawful, and secure exchange of data, intelligence, and risk-relevant insights among financial institutions, regulators, law enforcement agencies, Financial Intelligence Units (FIUs), industry bodies, and cross-border partners.

The objective of information sharing within AML/CFT frameworks is to enhance the detection, prevention, and disruption of money laundering, terrorist financing, proliferation financing, fraud, sanctions evasion, and other forms of financial crime.

In financial crime compliance, information sharing enables institutions to identify suspicious activity patterns, understand emerging typologies, improve customer risk assessments, and strengthen end-to-end monitoring.

It is conducted under specific legal provisions, regulatory expectations, and data privacy safeguards that govern what information can be shared, with whom, and under what circumstances.

Explanation

Information sharing has become an essential element of global AML/CFT ecosystems due to the complexity, scale, and cross-border nature of modern financial crime.

Criminal networks exploit jurisdictional boundaries, fragmented information flows, and siloed institutional practices to evade detection.

Financial institutions often hold partial datasets that, when combined with intelligence from other institutions or agencies, create clearer visibility into criminal behaviour.

Effective information sharing bridges these gaps by enabling:

• Collaboration between banks on shared fraud or money laundering risks,
• Structured intelligence exchange between public and private sectors,
• Rapid dissemination of alerts on emerging threats,
• Enhanced risk detection through shared transaction patterns,
• Stronger sector-wide and cross-border defences.

Regulators globally emphasise the importance of information sharing to strengthen the financial system’s resilience.

Initiatives such as the U.S. Section 314(b) safe harbour, the UK Joint Money Laundering Intelligence Taskforce (JMLIT), EU FIU cooperation mechanisms, and similar frameworks in APAC and the Middle East illustrate the trend toward more open, intelligence-led AML ecosystems.

Information sharing must operate within strict boundaries of privacy laws, data protection regulations, and confidentiality obligations.

Institutions must balance proactive intelligence exchange with compliance to legal frameworks such as GDPR, national privacy acts, and banking secrecy rules.

Information Sharing in AML/CFT Frameworks

Information sharing supports multiple layers of AML/CFT compliance and financial crime prevention.

Its role spans institutional risk functions, sector-wide networks, and public-private partnerships.

Customer Due Diligence (CDD) and Enhanced Due Diligence (EDD)

Information sharing enhances customer risk profiling by enabling institutions to identify:

• Shared typologies or behavioural red flags associated with certain customer segments,
• Alerts from other institutions regarding high-risk customers or patterns,
• Intelligence about beneficial ownership or associated entities.

Transaction Monitoring and Detection

Shared information helps refine detection models by providing additional insights into:

• Cross-institutional transaction patterns,
• Variations in behavioural expectations,
• Payment chains linked to suspicious activities.

Fraud and Scam Prevention

Fraud events often impact multiple institutions, making real-time information sharing essential.

Shared signals support:

• Prevention of cross-institution mule activity,
• Early identification of fraudulent merchants or beneficiaries,
• Blocking of coordinated APP scam networks.

Terrorist Financing and Sanctions Evasion Controls

Information sharing allows faster identification of:

• Networks of coordinated small-value transfers,
• Entities linked to sanctioned persons or conflict zones,
• Charitable misuse or front organisations supporting extremist groups.

Suspicious Activity Reporting (SAR / STR) Ecosystems

Countries with structured frameworks allow FIs to share insights relevant to SAR filings where legally permissible.

This improves:

• Case completeness,
• Accuracy of red-flag identification,
• Timeliness of reporting.

Key Components of an Effective Information Sharing Framework

Information sharing functions optimally when key components are in place:

Legal and Regulatory Frameworks

Institutions must operate within clearly defined legal boundaries that outline:

• What information can be shared,
• Safe harbour protections,
• Restrictions for customer confidentiality,
• Cross-border privacy obligations.

Structured Governance and Policies

Robust policies govern how institutions engage in information sharing.

Key elements include:

• Clear approval processes,
• Documentation of shared intelligence,
• Escalation channels for sensitive information,
• Regular oversight from legal and compliance teams.

Secure Communication Channels

Information sharing requires secure, encrypted platforms that preserve confidentiality, such as:

• FIU exchange systems,
• Industry-hosted secure intelligence portals,
• Law enforcement–coordinated channels.

Data Quality and Integrity

Institutions must ensure that shared data is:

• Accurate,
• Relevant,
• Timely,
• Supported by documented evidence.

Public-Private Partnerships

Formalised partnerships enhance intelligence exchange between financial institutions and government agencies.

Examples include:

• National financial crime taskforces,
• Sector-wide typology groups,
• FIU-led intelligence briefings.

Analytics and Intelligence Integration

Shared insights must be integrated into internal systems to refine:

• Risk scoring,
• Transaction monitoring,
• Model calibration,
• Investigative case-building.

Examples of Information Sharing Scenarios

Cross-Bank Mule Account Identification

A bank flags an account receiving multiple transfers from unrelated parties.

Through an information-sharing partnership, another bank confirms the same beneficiary pattern, enabling a coordinated investigation.

Industry Alert on High-Risk Beneficiaries

A payments provider identifies a fraudulent merchant operating across multiple platforms.

Intelligence is shared with peer institutions, leading to simultaneous account closures.

Terrorist Financing Network Disruption

A government agency shares intelligence about multiple small transactions routed through diverse remittance networks to a conflict zone.

Banks integrate this intelligence into their monitoring rules to detect similar patterns.

AML Typology Dissemination

FIUs publish new typologies on emerging threats, such as crypto-based layering, enabling institutions to adjust detection parameters.

Investigative Collaboration on Cross-Border Transactions

Banks in different jurisdictions share intelligence (permitted under applicable frameworks) on suspicious transactions routed through correspondent relationships, improving clarity on the payment chain.

Fraud Warning on Social Engineering Scams

An industry body distributes alerts about new scam techniques targeting elderly customers.

FIs incorporate these signals into authentication rules and customer advisories.

Impact on Financial Institutions

Information sharing delivers significant benefits to financial institutions and broader financial ecosystems.

Improved Risk Detection

A broader intelligence base enables institutions to detect:

• Sophisticated laundering schemes,
• Coordinated fraud networks,
• High-risk beneficiaries or merchants,
• Patterns not visible from isolated datasets.

Operational Efficiency

Shared insights reduce time spent on duplicate investigations and improve investigative accuracy.

Better Regulatory Alignment

Information sharing demonstrates proactive compliance and supports regulator expectations for intelligence-led AML programmes.

Sector-Wide Crime Prevention

Collaborative intelligence strengthens the collective defence across banks, fintechs, PSPs, insurers, and remittance providers.

Reduction in Financial Losses

Prevention of mule activity, scams, and layering schemes reduces losses for both institutions and customers.

Enhanced Trust Between Institutions

Structured information sharing fosters stronger industry relationships and supports coordinated responses to emerging threats.

Challenges in Managing Information Sharing Frameworks

Despite its advantages, information sharing presents operational, legal, and coordination challenges.

Data Privacy and Confidentiality Constraints

Institutions must navigate restrictions arising from privacy legislation, customer confidentiality, and banking secrecy laws.

Cross-Border Complexity

Differing regulatory regimes complicate intelligence sharing across jurisdictions, especially between high-regulation and low-regulation countries.

Operational Fragmentation

Variances in internal policies, risk appetites, or data standards across institutions can hinder seamless collaboration.

Lack of Standardisation

Inconsistent data formats, documentation fields, and quality of intelligence reduce the utility of shared information.

Resource Constraints

Effective information sharing requires skilled teams capable of handling sensitive intelligence responsibly.

Legal Uncertainty

In some jurisdictions, limited safe harbour protections deter institutions from participating proactively.

Risk of Over-Sharing

Without clear frameworks, excessive sharing may expose institutions to legal challenges or customer disputes.

Regulatory Oversight & Governance

Information sharing is guided by a mix of global standards, national regulatory requirements, and voluntary industry frameworks.

Financial Action Task Force (FATF)

FATF encourages risk-based information sharing across public and private sectors, emphasising its importance in combating financial crime.

Financial Intelligence Units (FIUs)

FIUs coordinate intelligence dissemination and may facilitate domestic or cross-border information sharing through secure systems.

National Supervisory Authorities

Regulators oversee compliance with data protection, AML, and sector-specific legislation that governs how institutions may share information.

Public-Private Partnerships (PPPs)

Countries operate PPPs such as:

• UK JMLIT,
• Singapore AML/CFT Industry Partnership (ACIP),
• Australia Fintel Alliance,
• U.S. FinCEN Exchange.

These PPPs facilitate structured intelligence exchange and typology updates.

Industry Networks and Consortia

Consortia such as global fraud intelligence-sharing networks, banking associations, and industry hubs enable institutions to collaborate on emerging threats.

Importance of Information Sharing in AML/CFT Compliance

Information sharing is essential to modern AML/CFT frameworks due to the global and interconnected nature of financial crime.

Without structured intelligence exchange, institutions are left with fragmented visibility, enabling criminals to exploit systemic blind spots.

Effective information sharing supports institutions in:

• Strengthening monitoring systems,
• Improving typology awareness,
• Detecting cross-bank criminal activity,
• Enhancing SAR quality,
• Supporting public-sector investigations,
• Reducing fraud and money laundering losses,
• Aligning with global regulatory expectations.

When integrated into intelligence-first architectures such as IDYC360’s AML framework, information sharing becomes a core catalyst for faster, smarter, and more accurate financial crime prevention.

It supports advanced analytics, improves network-based detection, and enhances real-time decision-making.

Related Terms

• Data Sharing
• Public-Private Partnerships
• Suspicious Activity Reporting
• Typology Dissemination
• Transaction Monitoring
• Cross-Border Intelligence
• Risk Collaboration

References

• FATF – Guidance on Information Sharing
• UK Joint Money Laundering Intelligence Taskforce (JMLIT)
• FinCEN Exchange – Public-Private Information Sharing
• Europol – Cross-Border Intelligence and Coordination

Ready to Stay
Compliant—Without Slowing Down?

Move at crypto speed without losing sight of your regulatory obligations.

With IDYC360, you can scale securely, onboard instantly, and monitor risk in real time—without the friction.

Get a Demo