NV Bulletin 24-001
Use of Artificial Intelligence Systems by Insurers
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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STATE OF NEVADA
DEPARTMENT OF BUSINESS AND INDUSTRY
DIVISION OF INSURANCE
Bulletin 24-001
February 23, 2024
Use of Artificial Intelligence Systems by Insurers
This bulletin applies to all insurers subject to Title 57 of the Nevada Revised Statutes
Purpose
This bulletin is issued by the Nevada Division of Insurance (“Division”) to remind all insurers
that hold certificates of authority to do business in this state that decisions or actions impacting
consumers that are made or supported by advanced analytical and computational technologies,
including artificial intelligence (“AI”) systems (as defined below), must comply with all
applicable insurance laws and regulations. This includes those laws that address unfair trade
practices and unfair discrimination. This bulletin sets forth the Division’s expectations as to how
insurers will govern the development/acquisition and use of certain AI technologies, including
the AI systems described herein. This bulletin also advises insurers of the type of information
and documentation that the Division may request during an investigation or examination of any
insurer regarding its use of such technologies and AI systems.
Background
AI is transforming the insurance industry. AI techniques are deployed across all stages of the
insurance life cycle, including product development, marketing, sales and distribution,
underwriting and pricing, policy servicing, claim management, and fraud detection.
AI may facilitate the development of innovative products, improve customer interface and
service, simplify and automate processes, and promote efficiency and accuracy. However, AI,
including AI systems, can present unique risks to consumers, including the potential for
inaccuracy, unfair discrimination, data vulnerability, and lack of transparency and explainability.
Insurers should take actions to minimize these risks.
The Division encourages the development and use of innovation and AI systems that contribute
to safe and stable insurance markets. However, the Division expects that decisions made and
actions taken by insurers using AI systems will comply with all applicable federal and state laws
and regulations.
JOE LOMBARDO
Governor
DR. KRISTOPHER SANCHEZ
Director
SCOTT J. KIPPER
Commissioner
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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The Division recognizes the Principles of Artificial Intelligence that the National Association of
Insurance Commissioners (“NAIC”) adopted in 2020 as an appropriate source of guidance for
insurers as they develop and use AI systems. Those principles emphasize the importance of the
fairness and ethical use of AI; accountability; compliance with state laws and regulations;
transparency; and a safe, secure, fair, and robust system. These fundamental principles should
guide insurers in their development and use of AI systems and underlie the expectations set forth
in this bulletin.
Authority
The regulatory expectations and oversight considerations set forth in the Regulatory Guidance
and Expectations and Regulatory Oversight and Examination Considerations sections of this
bulletin rely on the following laws and regulations:
• Unfair Trade Practices: NRS 686A.010 – 686A.310 collectively referred to herein as
the Unfair Trade Practices Act (“UTPA”), regulates trade practices in insurance by
defining practices that constitute unfair methods of competition or unfair or deceptive
acts and practices and prohibiting the trade practices so defined or determined.
As discussed below, insurers are expected to adopt practices, including governance frameworks
and risk management protocols, that are designed to ensure that the use of AI systems does not
result in unfair trade practices as defined in the UTPA.
• Corporate Governance Annual Disclosure: NRS 692C.3501 – 692C.3509, collectively
referred to herein as the Corporate Governance Annual Disclosure Act (“CGAD”),
requires insurer to report on governance practices and to provide a summary of the
insurer’s corporate governance structure, policies, and practices. The content, form, and
filing requirements for CGAD information are set forth in Nevada Administrative Code
(“NAC”) 692C.200– 692C.220, collectively referred to herein as the Corporate
Governance Annual Disclosure Regulations (“CGAD-R”).
The requirements of CGAD and CGAD-R apply to elements of the insurer’s corporate
governance framework that address the insurer’s use of AI systems to support actions and
decisions that impact consumers.
• Insurance Rating: NRS 686B.010 – 686B.1799 and NAC 686B.400 – 686B.610,
collectively referred to herein as the Insurance Rating Law (“IRL”), requires that
insurance rates not be excessive, inadequate, or unfairly discriminatory.
The requirements of IRL apply regardless of the methodology that the insurer used to develop
rates, rating rules, and rating plans subject to those provisions. That means that an insurer is
responsible for assuring that rates, rating rules, and rating plans that are developed using AI
techniques and predictive models that rely on data and machine learning do not result in
excessive, inadequate or unfairly discriminatory insurance rates with respect to all forms of
insurance.
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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An insurer’s conduct in this state, including its use of AI systems to make or support actions and
decisions that impact consumers, is subject to investigation, including market conduct actions.
The Regulatory Oversight and Examination Considerations section of this bulletin provides
guidance on the kinds of information and documents that the Division may request in the context
of an AI-focused investigation, including a market conduct action.
Definitions
For the purposes of this bulletin the following terms are defined:
“Adverse consumer outcome” refers to a decision by an insurer that is subject to insurance
regulatory standards enforced by the Division that adversely impacts the consumer in a manner
that violates those standards.
“Algorithm” means a clearly specified mathematical process for computation; a set of rules that,
if followed, will give a prescribed result.
“AI system” is a machine-based system that can, for a given set of objectives, generate outputs
such as predictions, recommendations, content (such as text, images, videos, or sounds), or other
output influencing decisions made in real or virtual environments. AI systems are designed to
operate with varying levels of autonomy.
“Artificial intelligence” refers to a branch of computer science that uses data processing systems
that perform functions normally associated with human intelligence, such as reasoning, learning,
and self-improvement, or the capability of a device to perform functions that are normally
associated with human intelligence such as reasoning, learning, and self-improvement. This
definition considers machine learning to be a subset of artificial intelligence.
“Degree of potential harm to consumers” refers to the severity of adverse economic impact that a
consumer might experience as a result of an adverse consumer outcome.
“Generative artificial intelligence” refers to a class of AI systems that generate content in the
form of data, text, images, sounds, or video, that is similar to, but not a direct copy of, preexisting data or content.
“Machine learning” refers to a field within artificial intelligence that focuses on the ability of
computers to learn from provided data without being explicitly programmed.
“Model drift” refers to the decay of a model’s performance over time arising from underlying
changes such as the definitions, distributions, and/or statistical properties between the data used
to train the model and the data on which it is deployed.
“Predictive model” refers to the mining of historic data using algorithms and/or machine learning
to identify patterns and predict outcomes that can be used to make or support the making of
decisions.
“Third party” means, for purposes of this bulletin, an organization other than an insurer that
provides services, data, or other resources related to AI.
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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Regulatory Guidance and Expectations
Decisions subject to regulatory oversight that are made by insurers using AI systems must
comply with the legal and regulatory standards that apply to those decisions, including unfair
trade practice laws. These standards require, at a minimum, that decisions made by insurers are
not inaccurate, arbitrary, capricious, or unfairly discriminatory. Compliance with these standards
is required regardless of the tools and methods insurers use to make such decisions. However,
because, in the absence of proper controls, AI has the potential to increase the risk of inaccurate,
arbitrary, capricious, or unfairly discriminatory outcomes for consumers, it is important that
insurers adopt and implement controls specifically related to their use of AI that are designed to
mitigate the risk of adverse consumer outcomes.
Consistent therewith, all insurers authorized to do business in this state are expected to develop,
implement, and maintain a written program (“AIS program”) for the responsible use of AI
systems that make, or support decisions related to regulated insurance practices. The AIS
program should be designed to mitigate the risk of adverse consumer outcomes, including, at a
minimum, the statutory provisions set forth in the Background section of this bulletin.
The Division recognizes that robust governance, risk management controls, and internal audit
functions play a core role in mitigating the risk that decisions driven by AI systems will violate
unfair trade practice laws and other applicable existing legal standards. The Division also
encourages the development and use of verification and testing methods to identify errors and
bias in predictive models and AI systems, as well as the potential for unfair discrimination in the
decisions and outcomes resulting from the use of predictive models and AI systems.
The controls and processes that an insurer adopts and implements as part of its AIS program
should be reflective of, and commensurate with, the insurer’s own assessment of the degree and
nature of risk posed to consumers by the AI systems that it uses, considering: (i) the nature of the
decisions being made, informed, or supported using the AI system; (ii) the type and degree of
potential harm to consumers resulting from the use of AI systems; (iii) the extent to which
humans are involved in the final decision-making process; (iv) the transparency and
explainability of outcomes to the impacted consumer; and (v) the extent and scope of the
insurer’s use or reliance on data, predictive models, and AI systems from third parties. Similarly,
controls and processes should be commensurate with both the risk of adverse consumer
outcomes and the degree of potential harm to consumers.
As discussed in the Regulatory Oversight and Examination Considerations section of this
bulletin, the decisions made as a result of an insurer’s use of AI systems are subject to the
Division’s examination to determine that the reliance on AI systems are compliant with all
applicable existing legal standards governing the conduct of the insurer.
AIS Program Guidelines
1.0
General Guidelines
1.1
The AIS program should be designed to mitigate the risk that the insurer’s use of
an AI system will result in adverse consumer outcomes.
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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1.2
The AIS program should address governance, risk management controls, and
internal audit functions.
1.3
The AIS program should vest responsibility for the development, implementation,
monitoring, and oversight of the AIS program and for setting the insurer’s
strategy for AI systems with senior management accountable to the board or an
appropriate committee of the board.
1.4
The AIS program should be tailored to and proportionate with the insurer’s use
and reliance on AI and AI systems. Controls and procedures should be focused on
the mitigation of adverse consumer outcomes and the scope of the controls and
procedures applicable to a given AI system use case should reflect and align with
the degree of potential harm to consumers with respect to that use case.
1.5
The AIS program may be independent of or part of the insurer’s existing
enterprise risk management (“ERM”) program. The AIS program may adopt,
incorporate, or rely upon, in whole or in part, a framework or standards developed
by an official third-party standard organization, such as the National Institute of
Standards and Technology (“NIST”) Artificial Intelligence and Risk Management
Framework, version 1.0.
1.6
The AIS program should address the use of AI systems across the insurance life
cycle, including areas such as product development and design, marketing, use,
underwriting, rating and pricing, case management, claim administration and
payment, and fraud detection.
1.7
The AIS program should address all phases of an AI system’s life cycle, including
design, development, validation, implementation (both systems and business),
use, on-going monitoring, updating and retirement.
1.8
The AIS program should address the AI systems used with respect to regulated
insurance practices whether developed by the insurer or a third-party vendor.
1.9
The AIS program should include processes and procedures providing notice to
impacted consumers that AI systems are in use and provide access to appropriate
levels of information based on the phase of the insurance life cycle in which the
AI systems are being used.
2.0
Governance
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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The AIS program should include a governance framework for the oversight of AI systems used
by the insurer. Governance should prioritize transparency, fairness, and accountability in the
design and implementation of the AI systems, recognizing that proprietary and trade secret
information must be protected. An insurer may consider adopting new internal governance
structures or rely on the insurer’s existing governance structures; however, in developing its
governance framework, the insurer should consider addressing the following items:
2.1
The policies, processes, and procedures, including risk management and internal
controls, to be followed at each stage of an AI system life cycle, from proposed
development to retirement.
2.2
The requirements adopted by the insurer to document compliance with the AIS
program policies, processes, procedures, and standards. Documentation
requirements should be developed with the Regulatory Oversight and
Examination Considerations section in mind.
2.3
The insurer’s internal AI system governance accountability structure, such as:
a) The formation of centralized, federated, or otherwise constituted committees
comprised of representatives from appropriate disciplines and units within the
insurer, such as business units, product specialists, actuarial, data science and
analytics, underwriting, claims, compliance, and legal.
b) Scope of responsibility and authority, chains of command, and decisional
hierarchies.
c) The independence of decision-makers and lines of defense at successive
stages of the AI system life cycle.
d) Monitoring, auditing, escalation, and reporting protocols and requirements.
e) Development and implementation of ongoing training and supervision of
personnel.
2.4
Specifically with respect to predictive models: the insurer’s processes and
procedures for designing, developing, verifying, deploying, using, updating, and
monitoring predictive models, including a description of methods used to detect
and address errors, performance issues, outliers, or unfair discrimination in the
insurance practices resulting from the use of the predictive model.
3.0
Risk Management and Internal Controls
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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The AIS program should document the insurer’s risk identification, mitigation, and management
framework and internal controls for the AI systems generally and at each stage of the AI system
life cycle. Risk management and internal controls should address the following items:
3.1
The oversight and approval process for the development, adoption, or acquisition
of AI systems, as well as the identification of constraints and controls on
automation and design to align and balance function with risk.
3.2
Data practices and accountability procedures, including data currency, lineage,
quality, integrity, bias analysis and minimization, and suitability.
3.3
Management and oversight of predictive models (including algorithms used
therein), including:
a) Inventories and descriptions of the predictive models.
b) Detailed documentation of the development and use of the predictive models.
c) Assessments such as interpretability, repeatability, robustness, regular tuning,
reproducibility, traceability, model drift, and the auditability of these
measurements where appropriate.
3.4
Validating, testing, and retesting as necessary to assess the generalization of AI
system outputs upon implementation, including the suitability of the data used to
develop, train, validate and audit the model. Validation can take the form of
comparing model performance on unseen data available at the time of model
development to the performance observed on data post-implementation,
measuring performance against expert review, or other methods.
3.5
The protection of non-public information, particularly consumer information,
including unauthorized access to the predictive models themselves.
3.6
Data and record retention.
3.7
Specifically with respect to predictive models: a narrative description of the
model’s intended goals and objectives and how the model is developed and
validated to ensure that the AI systems that rely on such models correctly and
efficiently predict or implement those goals and objectives.
4.0
Third-Party AI Systems and Data
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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Each AIS program should address the insurer’s process for acquiring, using, or relying on (i)
third-party data to develop AI systems; and (ii) AI systems developed by a third party, which
may include, as appropriate, the establishment of standards, policies, procedures, and protocols
relating to the following considerations:
4.1
Due diligence and the methods employed by the insurer to assess the third party
and its data or AI systems acquired from the third party to ensure that decisions
made or supported from such AI systems that could lead to adverse consumer
outcomes will meet the legal standards imposed on the insurer itself.
4.2
Where appropriate and available, the inclusion of terms in contracts with third
parties that:
a) Provide audit rights and/or entitle the insurer to receive audit reports by
qualified auditing entities.
b) Require the third party to cooperate with the insurer with regard to regulatory
inquiries and investigations related to the insurer’s use of the third-party’s
products or services.
4.3
The performance of contractual rights regarding audits and/or other activities to
confirm the third-party’s compliance with contractual and, where applicable,
regulatory requirements.
Regulatory Oversight and Examination Considerations
The Division’s regulatory oversight of insurers includes oversight of an insurer’s conduct in the
state, including its use of AI systems to make or support decisions that impact consumers.
Regardless of the existence or scope of a written AIS program, in the context of an investigation
or market conduct action, an insurer can expect to be asked about its development, deployment,
and use of AI systems, or any specific predictive model, AI system or application and its
outcomes (including adverse consumer outcomes) from the use of those AI systems, as well as
any other information or documentation deemed relevant by the Division.
Insurers should expect those inquiries to include (but not be limited to) the insurer’s governance
framework, risk management, and internal controls (including the considerations identified in the
Regulatory Guidance and Expectations section). In addition to conducting a review of any of the
items listed in this bulletin, a regulator may also ask questions regarding any specific model, AI
system, or its application, including requests for the following types of information and/or
documentation.
1. Information and Documentation Relating AI System Governance, Risk Management, and
Use Protocols
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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1.1
Information and documentation related to or evidencing the insurer’s AIS
program, including:
a) The written AIS program.
b) Information and documentation relating to or evidencing the adoption of the
AIS program.
c) The scope of the insurer’s AIS program, including any AI systems and
technologies not included in or addressed by the AIS program.
d) How the AIS program is tailored to and proportionate with the insurer’s use
and reliance on AI systems, the risk of adverse consumers outcomes, and the
degree of potential harm to consumers.
e) The policies, procedures, guidance, training materials, and other information
relating to the adoption, implementation, maintenance, monitoring, and
oversight of the insurer’s AIS program, including:
i.
Processes and procedures for the development, adoption, or acquisition
of AI systems, such as:
(1) Identification of constraints and controls on automation and
design.
(2) Data governance and controls, any practices related to data lineage,
quality, integrity, bias analysis and minimization, suitability, and
data currency.
ii.
Processes and procedures related to the management and oversight of
predictive models, including measurements, standards, or thresholds
adopted or used by the insurer in the development, validation, and
oversight of models and AI systems.
iii.
Protections of non-public information, particularly consumer
information, including unauthorized access to predictive models
themselves.
1.2
Information and documentation relating to the insurer’s pre-acquisition/pre-use
diligence, monitoring, oversight, and auditing data or AI systems developed by a
third party.
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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1.3
Information and documentation relating to or evidencing the insurer’s
implementation and compliance with its AIS program, including documents
relating to the insurer’s monitoring and audit activities respecting compliance,
such as:
a) Documentation relating to or evidencing the formation and ongoing operation
of the insurer’s coordinating bodies for the development, use, and oversight of
AI systems.
b) Documentation related to data practices and accountability procedures,
including data lineage, quality, integrity, bias analysis and minimization,
suitability, and data currency.
c) Management and oversight of predictive models and AI systems, including:
i.
The insurer’s inventories and descriptions of predictive models, and AI
systems used by the insurer to make or support decisions that can
result in adverse consumer outcomes.
ii.
As to any specific predictive model or AI system that is the subject of
investigation or examination:
(1) Documentation of compliance with all applicable AI program
policies, protocols, and procedures in the development, use, and
oversight of predictive models and AI systems deployed by the
insurer.
(2) Information about data used in the development and oversight of
the specific model or AI system, including the data source,
provenance, data lineage, quality, integrity, bias analysis and
minimization, suitability, and data currency.
(3) Information related to the techniques, measurements, thresholds,
and similar controls used by the insurer.
d) Documentation related to validation, testing, and auditing, including
evaluation of model drift to assess the reliability of outputs that influence the
decisions made based on predictive models. Note that the nature of validation,
testing, and auditing should be reflective of the underlying components of the
AI system, whether based on predictive models or generative AI.
Carson City: 1818 E. College Parkway, Suite 103 Carson City, Nevada 89706 - Telephone (775) 687-0700 - Fax (775) 687-0797
Las Vegas: 3300 W. Sahara Avenue, Suite 275 Las Vegas, Nevada 89102 - Telephone (702) 486-4009 - Fax (702) 486-4007
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2. Third-Party AI Systems and Data
In addition, if the investigation or examination concerns data, predictive models, or AI
systems collected or developed in whole or in part by third parties, the insurer should also
expect the Division to request the following additional types of information and
documentation.
2.1
Due diligence conducted on third parties and their data, models, or AI systems.
2.2
Contracts with third-party AI system, model, or data vendors, including terms
relating to representations, warranties. Data security and privacy, data sourcing,
intellectual property rights, confidentiality and disclosures, and/or cooperation
with regulators.
2.3
Audits and/or confirmation processes performed regarding third-party compliance
with contractual and, where applicable, regulatory obligations.
2.4
Documentation pertaining to validation, testing, and auditing, including
evaluation of model drift.
The Division recognizes that insurers may demonstrate their compliance with the laws that
regulate their conduct in the state in their use of AI systems through alternative means, including
through practices that differ from those described in this bulletin. The goal of the bulletin is not
to prescribe specific practices or to prescribe specific documentation requirements. Rather, the
goal is to ensure that insurers in the state are aware of the Division’s expectations as to how AI
systems will be governed and managed and of the kinds of information and documents about an
insurer’s AI system that the Division expects an insurer to produce when requested.
As in all cases, investigations and market conduct actions may be performed using procedures
that vary in nature, extent, and timing in accordance with regulatory judgment. Work performed
may include inquiry, examination of company documentation, or any of the continuum of market
actions described in the NAIC’s Market Regulation Handbook. These activities may involve the
use of contracted specialists with relevant subject matter expertise. Nothing in this bulletin limits
the authority of the Division to conduct any regulatory investigation, examination, or
enforcement action relative to any act or omission of any insurer that the Division is authorized
to perform.
Questions about this bulletin may be directed to insinfo@doi.nv.gov.
_____________________________
SCOTT J. KIPPER
Commissioner of Insurance