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Take a tourMany insurance systems still rely on classification standards developed nearly a century ago. As industries have evolved, these older classification codes often fail to reflect modern sectors and business models.
This creates challenges when companies attempt to map legacy industry codes to newer, more accurate systems. The result can be data mismatches, compliance issues, and risk exposure, especially for insurers relying on accurate classification for underwriting and reporting.
Understanding how these classification systems work—and how they differ—is necessary for evaluating legacy system risk in insurance environments.
SIC and NAICS are both systems used to classify businesses by industry. They help organize economic data, support regulatory reporting, and allow insurers to assess risk based on industry sector.
SIC (Standard Industrial Classification) was developed in the 1930s by the U.S. government. It uses a four-digit code to group businesses based on either production or demand characteristics. The system was last updated in 1987 and remains in use in many legacy systems.
NAICS (North American Industry Classification System) was introduced in 1997 as a collaborative effort between the U.S., Canada, and Mexico. It uses a six-digit code structure that allows for more detailed categorization. NAICS is revised every five years to reflect changes in the economy.
Key characteristics of each system:
SIC and NAICS both classify businesses by industry, but they're structured differently and serve different needs in today's economy. The differences are important for insurers working with industry classification data.
NAICS uses a six-digit structure that allows for more specific classification, especially in areas like information technology and professional services. These industries have expanded significantly since SIC was last revised.
Because NAICS groups businesses based on similar production processes, it creates a consistent framework for analyzing industries that are structurally alike. SIC codes, by contrast, were based on broader groupings that may not reflect how businesses operate today.
When industry codes in insurance systems are incorrect or outdated, they create problems for regulatory compliance, risk analysis, and underwriting. These issues begin with mismatched or improperly mapped SIC and NAICS codes in legacy systems.
Regulatory Reporting: Insurance regulators rely on accurate industry classifications to monitor business activity and ensure compliance with state requirements. If a company is misclassified—for example, if a tech company is still coded under a generic manufacturing SIC category—regulatory filings may show inaccurate exposure or premium volume. This can result in delayed approvals or penalties.
Risk Assessment Accuracy: Risk models often use industry classification as a factor in evaluating claims likelihood. A business coded incorrectly may receive a risk score that doesn't match its actual operations. For instance, a logistics company misclassified under a low-risk warehousing code could be underpriced, leading to unexpected losses.
Underwriting Decisions: Underwriters use industry codes to guide decisions on pricing and coverage terms. If a submission includes a misaligned code, the policy may be written with incorrect assumptions. For example, SIC 7389 ("Business Services, Not Elsewhere Classified") once covered activities that today fall under multiple NAICS codes, such as computer systems design (541512) or telemarketing bureaus (561422).
Incorrect classifications have been cited in regulatory reviews where rates were deemed inappropriate for the insured's actual operations. Misclassification can also affect reinsurance treaties, where exposure by industry segment is a key underwriting factor.
Updating from SIC to NAICS involves technical challenges that stem from the limitations of legacy infrastructure. These challenges affect the accuracy of industry classification and the reliability of insurance data.
SIC codes appear in many parts of an insurance organization's technology environment. These codes exist in policy systems, billing platforms, reports, and data warehouses. They may also be embedded in automated workflows or copied into spreadsheets.
Because legacy systems often lack documentation, locating every instance of a SIC code can be difficult. Some systems may use customized versions of SIC codes, increasing the complexity of identification.
Most legacy databases were built before NAICS was introduced. These systems often have fixed field lengths designed to store four-digit SIC codes. Expanding those fields to handle six-digit NAICS codes may require schema changes, which can disrupt dependent systems.
NAICS codes follow a hierarchical structure, which older systems may not support. This structure allows for roll-up and comparison across different levels of industry detail, which may not be possible in databases designed with flat SIC code structures.
Converting from SIC to NAICS is not always straightforward. Some SIC codes map to multiple NAICS codes, and some NAICS codes don't have a SIC equivalent. Automated conversions can result in errors that affect classification accuracy.
During a transition, original SIC data may be overwritten or discarded. If historical data is lost without proper documentation, it may affect trend analysis, claims history review, and long-term reporting.
Transitioning from SIC to NAICS involves several steps to ensure data accuracy and minimize disruption. Here's how to approach updating classification systems in insurance environments:
Crosswalks are reference tools that show relationships between SIC and NAICS codes. They're published by government agencies like the U.S. Census Bureau and provide a starting point for mapping older classifications to newer ones.
These tools aren't always one-to-one. A single SIC code can correspond to multiple NAICS codes, and some NAICS codes don't directly map back to SIC. In these cases, manual checks verify that the selected NAICS code reflects the actual business activity.
Pilot data runs test the conversion process on a small sample of records. This allows teams to examine how SIC codes are mapped to NAICS and identify errors before applying changes to the full dataset.
Validation can include:
Testing in a non-production environment avoids unintentional impacts on operational systems.
High-value accounts often involve unique risks or multi-line exposures that aren't easily classified by automated tools. These accounts may also be subject to closer regulatory scrutiny.
Manual review of these records during the transition helps ensure the correct NAICS code is applied. Prioritization can be based on premium size, policy complexity, or historical claim volume.
NAICS codes are updated every five years to reflect economic changes. Automation tools can help monitor these updates and apply changes to internal systems without manual intervention.
Automation may include scripts that scan for outdated codes, rules that flag new industry segments, and workflows that route exceptions for review. These tools reduce the risk of outdated classifications as industry structures evolve.
When changing from SIC to NAICS codes, companies often use both systems for a period of time. This allows older records to stay consistent while newer records follow the updated classification.
For historical reporting, one method is to keep the original SIC code on legacy records while also adding the mapped NAICS code. Reports can be designed to show both codes or specify which system the data is based on. This helps analysts understand how the classification may have changed over time.
In data warehouses, storing the original and converted codes in separate fields allows systems to retain the full classification history. This makes it possible to track how an industry was classified in past years even after the system has transitioned to NAICS.
Maintaining this continuity is important for long-term analysis, especially for actuarial models and trend reporting. Classification changes can affect year-over-year comparisons, so preserving both codes helps ensure the accuracy of historical insights.
NAICS codes help estimate how much risk a business carries. The type of work a business does affects how likely it is to file a claim and how large those claims might be. Industry classification is one of several inputs underwriters consider when evaluating a policy.
Some industries have a higher chance of accidents, property damage, or legal claims. High risk codes are common in industries with physical labor, hazardous materials, or complex operations.
Examples of higher risk NAICS codes include:
Other businesses are less likely to face claims related to physical injury or property loss. These are often considered low risk and typically operate in office settings with limited exposure to on-site hazards.
Examples of lower risk NAICS codes include:
Every five years, NAICS codes are reviewed and updated to reflect economic changes. New industries may be added, existing definitions revised, or certain categories removed. These updates can change how a business is classified and how its risk is assessed.
For example, the 2022 NAICS revision introduced changes in the technology, healthcare, and logistics sectors. A business that previously fell under a broader category may now be part of a more specific code with a different risk profile.