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Detect Employee Risk with Identity Resolution Software
Risk management is the process of identifying, analyzing, and addressing risks and threats that can impact a company or organization. While business threats often come from an external source such as natural disasters or an uncertain financial environment, catastrophic damage sometimes comes from within the organization itself.
These types of threats are more likely and devastating in organizations that handle high-value assets such as banks and casinos. Rogue employees may take advantage of their privileged access to engage in criminal or fraudulent behavior for their own personal gain.
Detecting Employee Risk
Fraudulent employee behavior can put an organization’s reputation, financial standing, and shareholder value at risk. For this reason, it is essential that employers perform background checks not only on potential hires but also periodically on employees with access to high-value assets.
There are two main ways to check employees against criminal and public records databases. The primary use case is to check whether an employee name matches a record within a criminal or public records database.
The secondary use case is to check for connections between a potential hire or current employee and an individual on a criminal records database. A close match in name, address, or kinship may indicate such a connection and warrant a closer review.
Detect Employee Risk Automatically with Identity Resolution
Comparing records to find similar ones can be a very complex task because matching records may differ in multiple ways. For instance, matching names may differ due to misspellings, word order variations, nicknames, initials, etc. Matching addresses may differ due to abbreviations, missing words or components, and word order. Comparing records automatically therefore requires robust and accurate Identity Resolution technology.
NetOwl, the winner of the MITRE Multicultural Name Matching Challenge, offers best-of-breed intelligent Identity Resolution based on evidence from any number or combination of entity attributes. With its unique, empirically driven, machine learning-based probabilistic approach and proprietary search and indexing engine, NetOwl’s Identity Resolution provides highly accurate, scalable, and flexible automated record matching for many languages and ethnicities. Additionally, NetOwl’s Identity Resolution is fully tunable and configurable.