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Home > Industries > Financial Institutions > AI & Technology  > Entity Recognition and Resolution for Compliance Monitoring

CORE EXPERTISE

AI & Technology

INDUSTRY

Financial Institutions

Use Cases

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Entity Recognition and Resolution for Compliance MonitoringCustomer Relationship Management 

Strategic Market Trend Analysis

Financial institutions manage mass volumes of unstructured data from disclosures, filings, and transactions, making it difficult to identify entities consistently. Variations in company names, complex ownership records, and undisclosed relationships often obscure true identities. This lack of clarity restricts effective compliance monitoring, exposing institutions to fraud, regulatory breaches, and hidden conflicts of interest. AI-driven entity recognition and resolution addresses this challenge by standardizing identities and surfacing hidden links for stronger oversight. 

Workflows

Regulatory Agencies

NER structures unstructured complaints, disclosures, and reports by tagging companies, individuals, and regulated activities.

Tax Authorities

Extract individual names, companies in filings and reports to identify real identity to spot fraud or non-compliance.

Procurement & Anti-Corruption Units

NER surfaces links between vendors, officials, and contract terms in public procurement data to detect conflicts of interest or collusion.

Key Personas

KYC Analysts

Compliance Officers

AML Investigators

Procurement officers

Recommended Products

Handshakes APP

Entity Profile Report

Detailed business report containing key company information, address, shareholders and past charges from official sources. 

RED List Report 

A quick and efective way to check for direct and indirect exposure to regulatory actions.

Entity List & Batch Request

Make COI search through screening large volume of entity data and get a comprehensive result to ease due diligence process.

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KYB Services

Identification & Verification (Upcoming)

Search and verify information of persons and companies against official sources. 

Screening

Screen persons, companies and their connected parties against Politically-Exposed-Persons (PEP) / Sanctions list.

Corporate History (Upcoming)

Historical analysis of company records such as past ownership, business activity changes and more.

Corporate Network (Upcoming)

Network pattern analysis of extended connection of corporate relationships to identify potential risks.

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Handshakes FUSE 

Entity Concordance

This feature allows users to identify the same unique entity across various data sets, allowing users to pull all peripheral data into a more holistic view for the target entity.

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Handshakes SEER

Named Entity Recognition & Linking (NERL)

Named Entity Recognition extracts entities (eg. Company, Person, Location) mentioned in a document. Different occurrences of the same entity are disambiguated and linked to an entry in a database through Entity Linking.

Relationship Extraction  

Relationship Extraction uses AI models to extract relationship between two entities mentioned in an unstructured document.

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Recommended Solutions

Due diligence

With every new board member, vendor, client, or partner, comes new compliance risks. Perform enhanced due diligence checks quickly, with reliable data sourced directly from our database.

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Other Use Cases for Financial Institutions

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