14. Ethics, Regulation, Governance and Customer Fairness

Introduction and Context

Insurance is founded on a promise made today against an uncertain future. The insurer receives a premium, assumes a risk, and undertakes to provide financial protection when a specified event occurs. Because the customer cannot fully observe the insurer’s financial strength, underwriting judgment, claims processes, data practices, or internal controls, insurance is a relationship of information asymmetry and delegated trust. Ethics, regulation and governance exist partly to manage that asymmetry.

Underwriting and claims management therefore cannot be evaluated only through loss ratios, settlement speed, expense ratios or profitability. A technically profitable portfolio may still be unsustainable if it is supported by misleading sales practices, discriminatory pricing, inadequate reserves, poor complaint handling, weak controls over intermediaries, or the systematic discouragement of legitimate claims. Conversely, a fair and well-governed insurer is more likely to preserve customer confidence, attract quality business, meet regulatory expectations and make sound long-term decisions.

This chapter examines the institutional framework within which underwriting and claims decisions are made. It connects licensing and solvency with conduct supervision, data protection, delegated authority, conflicts of interest, vulnerable customers, complaints, auditability and model risk. The central managerial challenge is to balance speed, efficiency and commercial performance with fairness, accountability and legal compliance. Regulatory details vary by jurisdiction, so the principles discussed here should always be read alongside the applicable insurance, company, consumer-protection, data-protection and financial-reporting laws.

Learning Objectives

After studying this chapter, a student should be able to:

1. Explain why ethics, regulation and governance are essential to underwriting and claims management.

2. Distinguish prudential regulation from conduct regulation and relate both to insurance performance.

3. Apply principles concerning licensing, solvency, fair treatment, data protection and claims handling.

4. Design governance controls for delegated authority, conflicts of interest, complaints and vulnerable customers.

5. Evaluate audit trails, automated decision systems and model risk.

6. Analyse trade-offs between speed, profitability, customer fairness and accountability.

7. Recommend practical controls for an insurer facing an ethical or regulatory dilemma.

The Regulatory Architecture of Insurance

Insurance regulation normally operates through several connected layers. Licensing rules determine who may conduct insurance business and in which classes. Prudential regulation addresses the insurer’s ability to remain solvent and meet obligations. Conduct regulation governs how products are designed, sold, administered and serviced. Corporate governance rules address boards, senior management, internal controls and accountability. Data-protection and cybersecurity requirements govern the collection, use, storage and disclosure of personal information. Financial-reporting and market-conduct requirements create transparency for regulators, investors and customers.

Licensing and authorisation

An insurer generally requires authorisation before accepting risk from the public. The authorisation process may examine ownership, capital, business plans, proposed products, governance arrangements, reinsurance, information systems, key personnel and compliance capability. Licensing is not merely an entry formality. It establishes the permitted scope of business and creates continuing obligations to notify the regulator of material changes.

Underwriters and claims managers should understand the practical meaning of authorisation. A business must not write a class of insurance, operate in a territory, appoint an intermediary, or outsource a critical function without confirming that the activity is permitted. Misrepresenting the insurer’s licence, using an unauthorised carrier, or accepting business outside approved classes can expose customers to uncertainty about the validity of cover and expose managers to enforcement action.

Prudential supervision and solvency

Prudential supervision seeks to ensure that an insurer can pay valid claims as they fall due. Important elements include eligible capital, technical provisions, asset quality, liquidity, reinsurance arrangements, concentration risk, catastrophe exposure and stress testing. Solvency is not equivalent to profitability. A profitable insurer may face a liquidity crisis, while a temporarily unprofitable insurer may remain financially strong because it has adequate capital and sound risk management.

Underwriting decisions influence solvency through pricing, risk selection, policy terms, accumulation and claims development. Claims decisions influence it through reserving accuracy, settlement practices, litigation strategy and recognition of incurred but not reported losses. Governance should therefore connect underwriting, actuarial, claims, finance, risk and compliance functions rather than treating solvency as the responsibility of finance alone.

A useful control cycle is:

• identify material exposures and assumptions;
• estimate expected claims, expenses and capital needs;
• monitor actual experience against assumptions;
• investigate adverse deviations;
• revise underwriting, reserving or reinsurance decisions; and
• report significant matters to senior management and the board.

Capital should not be used as a justification for unfair claims practices. The legitimate response to deteriorating solvency is improved pricing, capital strengthening, portfolio adjustment, reinsurance or orderly withdrawal—not arbitrary rejection or delay of valid claims.

Conduct regulation and fair treatment

Conduct regulation focuses on the customer’s experience and the integrity of market behaviour. Common expectations include clear product information, suitable or appropriate sales, fair pricing practices, accurate disclosure, responsible use of exclusions, prompt and transparent claims handling, accessible complaints procedures and protection from unfair discrimination.

Fair treatment does not mean that every customer receives the same price or outcome. Insurance is risk-based, and differences may be justified by relevant actuarial or underwriting factors. Fairness requires that distinctions be relevant, proportionate, consistently applied, explainable and legally permissible. A decision may be commercially rational but unfair if it relies on irrelevant personal characteristics, opaque proxies, inaccessible communication or a process designed to discourage claims.

Ethical Foundations for Underwriting and Claims

Legal compliance is the minimum standard, not the entire meaning of professional conduct. Ethics asks whether a decision is honest, responsible, proportionate and respectful of persons affected by it. Four principles are especially useful.

Respect for autonomy requires customers to receive information that enables informed decisions. A policyholder cannot meaningfully consent to exclusions, data uses or renewal terms that are hidden in complex or misleading communication.

Beneficence and non-maleficence require the insurer to provide genuine protection and avoid foreseeable harm. This is relevant when designing products, setting deductibles, selecting exclusions, investigating claims or using surveillance tools.

Justice and consistency require comparable cases to be treated consistently while allowing justified distinctions. Claims handlers should not alter outcomes because of personal attitudes, pressure from a powerful broker or assumptions about a customer’s credibility.

Integrity and accountability require professionals to disclose conflicts, maintain accurate records, escalate concerns and accept responsibility for decisions. A performance target is not an ethical defence for manipulating claims reserves, suppressing complaints or refusing escalation.

A practical ethical test is to ask: Is the decision lawful? Is it consistent with the policy and evidence? Would it be understandable to the customer? Would it remain defensible if reviewed by the board, regulator, court or public? Does it distribute benefits and burdens fairly? These questions do not replace technical analysis, but they expose decisions that are formally permitted yet substantively problematic.

Governance: Turning Principles into Control

Governance is the system by which an organisation is directed, controlled and held accountable. Effective governance allocates authority, defines risk appetite, monitors performance, challenges assumptions and ensures that corrective action occurs. It is not synonymous with paperwork. A large policy library is weak governance if employees cannot apply it or if management ignores warning indicators.

The three lines of responsibility

A commonly used model distinguishes:

1. Operational management, including underwriters, claims handlers and delegated partners, owns day-to-day risk decisions and controls.

2. Risk, compliance and actuarial functions provide advice, monitoring, challenge and independent review.

3. Internal audit provides objective assurance on the design and effectiveness of governance and controls.

The board remains responsible for strategy, culture, risk appetite, solvency oversight and the effectiveness of senior management. Independence is important: a compliance function that reports only to the commercial executive whose decisions it is expected to challenge may lack practical authority.

Risk appetite and accountability

A risk appetite statement should address more than financial volatility. It may specify tolerances for regulatory breaches, unresolved complaints, claims delays, inappropriate declinatures, data incidents, model error and outsourcing failures. Each limit should have an owner, a measurement method, an escalation threshold and a defined response.

Accountability is strengthened through a decision-rights matrix. It should specify who may approve new products, exceptions to underwriting rules, large claims settlements, reserve changes, broker remuneration arrangements, data uses and outsourcing contracts. Exceptions should be recorded rather than handled informally. A culture that rewards employees for bypassing controls in order to meet speed targets is a governance failure, even if the bypass appears operationally efficient.

Delegated Authority and Intermediary Governance

Insurers frequently delegate underwriting, claims administration or settlement authority to managing general agents, brokers, third-party administrators and other service providers. Delegation can improve distribution and specialist capability, but it does not transfer the insurer’s ultimate responsibility to policyholders or regulators.

A sound delegated-authority framework includes due diligence before appointment, written authority limits, permitted classes and territories, referral rules, pricing and wordings controls, claims thresholds, reporting obligations, audit rights, remuneration disclosure, complaints arrangements, data-security requirements and termination provisions. Due diligence should assess financial strength, licensing, competence, staffing, systems, conduct history, conflicts and business continuity.

Oversight must be risk-based and continuous. Useful indicators include referral rates, exception frequency, claims repudiation rates, settlement times, complaints, reserve development, leakage, unusual payment patterns and differences between delegated and centrally managed portfolios. A low complaint rate is not automatically positive; it may indicate that customers cannot access the complaint process or that claims are being abandoned before formal complaint registration.

The principal-agent problem is central. A delegated agent may receive volume-based remuneration while the insurer bears claims risk. Controls should therefore align incentives with sustainable outcomes, not merely premium growth or low settlement ratios. Remuneration linked to claim reduction can create an unacceptable incentive to delay or reject valid claims.

Conflicts of Interest and Professional Judgement

Conflicts arise when a person’s personal, financial or organisational interests could influence professional judgment. Examples include a broker receiving contingent remuneration, a claims assessor handling a claim involving a close associate, an underwriter accepting business from a major client despite unsuitable risk, or a repair network benefiting from inflated invoices.

Conflict management normally involves identification, disclosure, assessment, avoidance or mitigation, and documentation. Disclosure alone may be insufficient. Where the conflict is material, the individual should be removed from the decision, an independent review should occur, or the relationship should be prohibited. Gifts, hospitality, family relationships, ownership interests and performance incentives require clear policies and supervisory judgment.

Professional judgement should be evidence-based but not mechanically evidence-blind. An underwriter may depart from a model when credible new information exists, but the reason, authority and effect should be recorded. Similarly, a claims handler may request additional evidence when proportionate and relevant, but open-ended requests that exhaust the claimant are unfair and operationally risky.

Customer Fairness Across the Insurance Life Cycle

Fair treatment begins before a policy is sold. Product governance should identify the target market, foreseeable customer needs, key exclusions, distribution risks and potential harms. Products should be tested for clarity, value and suitability for the intended segment. A policy with extensive exclusions may be technically valid but offer poor value if customers reasonably believe it covers the principal risk advertised.

At quotation and sale, information should be clear, accurate and timely. Important limitations should not be obscured by promotional language. Intermediaries should explain material conditions and avoid pressuring customers into unnecessary cover. Pricing may be differentiated by risk, but firms should review whether variables are reliable, proportionate and potentially discriminatory.

During administration, customers should be able to update information, receive documents, understand renewal changes and contact the insurer through accessible channels. Automatic renewal, cancellation fees and mid-term adjustments require transparent communication. Digital convenience should not eliminate reasonable alternatives for customers who cannot use online systems.

Claims handling is the moment at which the promise of insurance is tested. A fair process includes accessible notification, acknowledgement, clear information requests, competent investigation, impartial assessment, regular updates, reasoned decisions, timely payment of accepted claims and an effective review or complaint route. Fraud controls are legitimate, but suspicion must be based on relevant indicators. The existence of fraud risk does not justify treating every claimant as dishonest.

A repudiation or partial settlement letter should identify the relevant policy provision, explain the factual basis, distinguish established facts from assumptions, state what further information could change the decision, and describe review and complaint rights. The aim is not merely to defend the insurer’s position but to enable the customer to understand and, where appropriate, challenge it.

Vulnerable customers

Vulnerability may be temporary, permanent, visible or hidden. It can arise from illness, disability, bereavement, financial distress, language barriers, age, cognitive impairment, domestic abuse, displacement or a major traumatic event. Vulnerability is not a fixed label; a customer may become vulnerable because of the insured event itself.

Good practice includes accessible communications, additional time where justified, authorised representatives, interpreter services, alternative formats, sensitive questioning and referral to specialist support. Staff should not assume incapacity or make decisions paternalistically. They should ask what support is needed, record consent appropriately and protect confidentiality. Digital systems should include a route for human intervention when automated communications are unsuitable.

Data Protection, Privacy and Security

Insurance depends on personal and sometimes sensitive information, including health, financial, property, driving and behavioural data. Data governance should address a lawful and transparent basis for processing, purpose limitation, data minimisation, accuracy, retention, access rights, secure sharing and breach response. The exact legal terminology differs across jurisdictions, but the underlying principle is that information should be collected and used for legitimate, defined and proportionate purposes.

Underwriters should avoid collecting data merely because technology makes it available. Claims investigators should distinguish relevant verification from intrusive surveillance. Data obtained from third parties should be checked for accuracy and legal authority. Customers should be informed, subject to lawful exceptions, about significant uses of their information and the consequences of failing to provide it.

Security controls include access management, encryption, segregation of duties, secure APIs, staff training, vendor oversight, incident monitoring, tested backups and documented breach escalation. A privacy breach is also a claims and conduct issue if it exposes medical information, delays settlement or undermines customer trust.

Automation, Analytics and Model Risk

Automated underwriting, fraud scoring, claims triage and reserving tools can improve consistency and speed. They can also reproduce historical bias, rely on poor-quality data, generate opaque decisions or fail under conditions unlike those in the training data.

Model governance should cover an inventory of models, clear purpose and ownership, data lineage, validation, performance monitoring, explainability, access controls, change approval, documentation and retirement. Validation should test not only predictive accuracy but also stability, calibration, fairness, error distribution and outcomes for relevant customer groups. Human oversight must be meaningful: a reviewer who can only approve the system’s recommendation is not exercising genuine control.

Model risk is especially serious where an automated recommendation leads to claim denial, premium loading, cancellation or fraud referral. Customers should receive an understandable explanation of material decisions, and there should be a route to human review. A model’s statistical performance does not by itself establish fairness or legality. Proxies may create discriminatory effects even when protected characteristics are excluded from the input data.

Complaints, Audit Trails and Regulatory Reporting

A complaint is valuable governance information, not merely an administrative burden. A mature complaints system records the issue, product, channel, customer circumstances, root cause, resolution, compensation, response time and recurrence. Management should distinguish between individual remedy and systemic correction. If many customers misunderstand an exclusion, revising the wording or sales process may be more important than resolving each complaint separately.

An audit trail should allow an independent reviewer to reconstruct what happened, who acted, what information was available, which rule applied, what exception was made and why the outcome followed. Records should be contemporaneous, accurate, secure and retained for the required period. Editing or deleting records to improve apparent performance is a serious integrity failure.

Regulatory reporting should be complete, accurate, timely and consistent with internal information. Indicators may include solvency, capital, complaints, conduct incidents, claims settlement, reserves, outsourcing, data breaches and suspicious activity. Senior managers should understand the assumptions behind reports rather than signing them as a ritual. Escalation is required where information is materially uncertain or potentially misleading.

An Integrated Decision Framework

Managers can use a six-stage framework for difficult underwriting or claims decisions:

1. Define the decision and affected stakeholders. Identify the customer, beneficiaries, insurer, intermediary and wider groups affected.

2. Establish the legal and contractual boundary. Locate the policy wording, licence conditions, regulatory requirements and relevant internal authority.

3. Test the evidence and data. Check quality, relevance, accuracy, provenance and whether missing information is being interpreted unfairly.

4. Assess risk and alternatives. Compare possible decisions, including partial settlement, additional support, referral, independent review or product redesign.

5. Evaluate fairness and conflicts. Ask whether the result is consistent, proportionate, explainable and free from unmanaged incentives.

6. Decide, document, communicate and learn. Give reasons, preserve the audit trail, provide review rights and feed lessons into controls and reporting.

This framework supports speed because it clarifies escalation thresholds and prevents repeated reconsideration. It supports profitability because sound decisions reduce leakage, disputes, regulatory costs and reputational damage. Most importantly, it makes accountability visible.

Illustrative Case: Automated Claims Triage and Vulnerable Customers

Background

HarbourShield Insurance, a fictional mid-sized insurer, introduced an automated motor-claims triage system. The system classified claims as low, medium or high complexity. Low-complexity claims were settled rapidly; high-risk claims were referred to a specialist investigation unit. Management expected lower costs and faster service.

Situation and problem

After six months, average settlement time improved. However, complaints increased among older customers and customers who reported accidents by telephone. The model assigned a disproportionately high number of telephone-reported claims to investigation. A review also found that some customers with limited digital literacy struggled to upload documents, leading to repeated requests and delays. Claims managers initially defended the system because overall fraud detection had improved.

Analysis

The problem was not simply technical accuracy. The model had learned from historical data in which telephone claims were more likely to receive manual investigation, creating a feedback loop. Telephone reporting was acting as a proxy for customer characteristics unrelated to fraud. The process also lacked a vulnerability flag and offered no effective human review before intrusive investigation began.

Governance weaknesses included unclear model ownership, insufficient fairness testing, no defined threshold for customer-impact review and performance targets focused on speed and fraud savings. The insurer had measured aggregate accuracy but not false-positive rates, complaint patterns, outcomes by channel or the experience of vulnerable customers.

Approach and solution

HarbourShield suspended automatic investigation referrals based solely on reporting channel. It commissioned an independent model validation review, tested outcomes across relevant customer groups, and introduced a human review for adverse or intrusive actions. Claims staff received training on vulnerability and accessible communication. Customers could submit evidence by telephone, post, assisted upload or through an authorised representative.

The insurer also revised its scorecard. In addition to settlement time and fraud savings, it monitored false-positive referrals, complaint rates, repeat information requests, vulnerable-customer outcomes, explanation quality and overturned decisions. The model documentation was updated to identify data sources, assumptions, limitations, approval authority and monitoring responsibilities.

Outcome

The fictional insurer accepted that a faster process was not necessarily a fairer process. Investigation referrals became more targeted, explanations improved and customer complaints declined. Some operating costs increased because human review was restored in high-impact cases, but management considered this an appropriate cost of accountable automation. The revised governance process also improved confidence in future technology deployments.

Learning points

The case demonstrates that model performance must be assessed in context. A system can improve an aggregate metric while producing unfair outcomes for a subgroup. Customer channel, disability, language or help-seeking behaviour may become unintended proxies. Human oversight, alternative communication routes, impact monitoring and clear accountability are essential when automated decisions affect access to insurance benefits.

Challenges and Common Governance Failures

Several recurring failures deserve attention. First, organisations may confuse compliance documentation with ethical behaviour. Policies have little value if incentives reward their violation. Second, firms may outsource activities without outsourcing risk; inadequate oversight of a third-party administrator remains the insurer’s problem. Third, excessive reliance on averages can conceal harm to minorities or vulnerable customers. Fourth, fraud prevention may become an excuse for suspicion without evidence. Fifth, speed targets can create premature denials, incomplete investigations and poor explanations.

Other weaknesses include fragmented data, inconsistent definitions of complaints, weak management information, inadequate succession planning, untested business continuity, poor record retention and conflicts between sales and claims functions. Regulatory change also creates risk when staff receive rules without practical training or when systems are not updated consistently with revised policy wording.

Current Developments and Best Practices

Insurance governance is increasingly shaped by digital distribution, artificial intelligence, climate-related risk, cyber threats, embedded insurance and cross-border data flows. Regulators are paying greater attention to operational resilience, algorithmic accountability, outsourcing chains and the value delivered to customers. Climate and catastrophe risks also challenge traditional assumptions about pricing, availability and claims capacity.

Strong practice includes a board-level conduct and culture agenda; clear product-governance ownership; risk-based oversight of intermediaries; independent complaints and quality assurance; documented vulnerability support; privacy-by-design; model inventories and impact testing; scenario analysis; protected whistleblowing; and remuneration linked to sustainable customer and risk outcomes. Senior leaders should review not only whether targets were achieved, but how they were achieved and who bore the cost.

Chapter Summary

Ethics, regulation and governance provide the framework through which insurers convert a promise of protection into responsible practice. Licensing establishes legitimate authority; prudential supervision protects solvency and claims-paying capacity; conduct regulation protects customers from unfair treatment. Effective governance allocates responsibility, controls delegated authority, manages conflicts and creates reliable escalation.

Fair treatment must operate across product design, sale, administration, renewal and claims. Vulnerable customers require adaptable support rather than uniform procedures. Data protection limits excessive or inappropriate information use, while model governance is necessary when automation influences pricing, investigation or settlement. Complaints, audit trails and regulatory reports are sources of accountability and organisational learning. The strategic objective is not to choose between efficiency and fairness, but to design processes in which speed and profitability are achieved without sacrificing lawful, explainable and humane decision-making.

Key Terms

Conduct regulation: Rules governing how insurers design, sell, administer and service insurance products.

Prudential regulation: Supervision concerned with financial strength, solvency, liquidity and claims-paying capacity.

Licensing: Formal authorisation to conduct specified insurance activities.

Solvency: The capacity of an insurer to meet its obligations as they become due.

Technical provisions: Financial estimates of future insurance obligations, including expected claims and related expenses.

Risk appetite: The level and type of risk an organisation is willing to accept in pursuing its objectives.

Delegated authority: Permission granted to another party to perform specified underwriting, claims or administrative functions.

Principal-agent problem: The risk that an agent’s incentives differ from those of the party bearing ultimate responsibility.

Conflict of interest: A situation in which personal or organisational interests may improperly influence professional judgment.

Fair treatment: Consistent, proportionate, transparent and non-discriminatory treatment of customers.

Vulnerable customer: A customer whose circumstances may make it difficult to understand, access or benefit fairly from insurance services.

Audit trail: A reliable record enabling a decision or transaction to be reconstructed and reviewed.

Model risk: The possibility that a model is unsuitable, inaccurate, misused or poorly governed.

Data minimisation: Collecting and using no more personal data than is necessary for a defined legitimate purpose.

Complaint: An expression of dissatisfaction requiring a response or resolution under the firm’s complaints process.

Operational resilience: The capability to continue important services and recover from disruption.

Conduct risk: The risk that organisational behaviour produces unfair customer or market outcomes.

Whistleblowing: Reporting suspected wrongdoing through protected internal or external channels.

Review Questions

Short Answer Questions

1. Distinguish prudential regulation from conduct regulation.

2. Why does delegated authority not remove the insurer’s ultimate responsibility?

3. What is meant by fair treatment in risk-based insurance pricing?

4. Identify four elements of an effective claims audit trail.

5. Why can a low complaint rate be misleading?

Long Answer Questions

1. Explain how underwriting and claims management contribute to solvency and financial governance.

2. Discuss the ethical principles that should guide claims investigation and repudiation decisions.

3. Describe a comprehensive governance framework for a delegated underwriting authority.

4. Examine the requirements for fair treatment of vulnerable customers throughout the insurance life cycle.

5. Analyse the benefits and risks of automated underwriting and claims systems.

Analytical / Application Questions

1. An insurer’s claims department is rewarded primarily for reducing settlement costs. Analyse the governance and ethical risks and propose a revised performance framework.

2. A model refers substantially more claims from one communication channel for fraud investigation. Design an investigation covering data, fairness, governance and customer remedy.

3. A third-party administrator repeatedly misses reporting deadlines but produces profitable results. Advise the insurer’s board on whether and how the relationship should be continued.

22. Multiple Choice Questions with Answers

Question 1

Which statement best distinguishes prudential regulation from conduct regulation?

A. Prudential regulation concerns solvency, while conduct regulation concerns customer and market treatment.

B. Prudential regulation concerns advertising, while conduct regulation concerns capital.

C. Prudential regulation applies only to brokers, while conduct regulation applies only to insurers.

D. There is no meaningful distinction between the two.

Correct Answer: A. Prudential regulation concerns solvency, while conduct regulation concerns customer and market treatment.

Question 2

An insurer delegates claims authority to a third-party administrator. Which control is most appropriate?

A. Allow the administrator to operate without review because authority has been transferred.

B. Use written limits, reporting duties, audit rights and ongoing performance monitoring.

C. Measure only the administrator’s premium income.

D. Require the administrator to create its own regulatory licence for the insurer.

Correct Answer: B. Use written limits, reporting duties, audit rights and ongoing performance monitoring.

Question 3

Which action most clearly demonstrates fair claims handling?

A. Requesting unlimited documents before acknowledging the claim.

B. Rejecting all claims from customers previously suspected of fraud.

C. Providing a reasoned decision linked to evidence and relevant policy provisions.

D. Using settlement speed as the only quality measure.

Correct Answer: C. Providing a reasoned decision linked to evidence and relevant policy provisions.

Question 4

Why may a low number of recorded complaints indicate a governance problem?

A. Complaints are always evidence of insurer insolvency.

B. Customers may face barriers that prevent them from making complaints.

C. A low complaint number automatically proves unfair treatment.

D. Regulators prohibit insurers from recording complaints.

Correct Answer: B. Customers may face barriers that prevent them from making complaints.

Question 5

Which is the strongest response to a material conflict of interest in a claim?

A. Ignore it if the employee believes they can remain objective.

B. Disclose it only after the claim is settled.

C. Remove the individual or introduce an independent review and document the action.

D. Offer the employee a higher performance bonus.

Correct Answer: C. Remove the individual or introduce an independent review and document the action.

Question 6

A model produces accurate aggregate fraud predictions but disproportionately refers claims from older customers. What should management do first?

A. Use the model unchanged because aggregate accuracy is sufficient.

B. Delete all customer age information and continue without testing.

C. Investigate subgroup outcomes, possible proxy variables and the need for human review.

D. Reject every referred claim automatically.

Correct Answer: C. Investigate subgroup outcomes, possible proxy variables and the need for human review.

Question 7

Which principle is most directly associated with collecting only information necessary for a defined purpose?

A. Data minimisation

B. Delegated authority

C. Capital adequacy

D. Risk appetite

Correct Answer: A. Data minimisation

Question 8

What is the principal strategic danger of linking claims-handler remuneration only to reduced settlement costs?

A. It may create incentives to delay or reject valid claims.

B. It guarantees excessive claims payments.

C. It eliminates the need for claims reserves.

D. It prevents all forms of fraud detection.

Correct Answer: A. It may create incentives to delay or reject valid claims.

Question 9

Which item belongs in an effective model-governance framework?

A. An undocumented model with no accountable owner.

B. Model inventory, validation, data lineage and change approval.

C. Automatic implementation of every model recommendation.

D. Monitoring only after a regulatory investigation.

Correct Answer: B. Model inventory, validation, data lineage and change approval.

Question 10

In the illustrative case, why was telephone reporting a governance concern?

A. Telephone reporting is unlawful for motor claims.

B. It may have acted as an unintended proxy unrelated to genuine fraud risk.

C. It always produces lower claim values.

D. It prevents insurers from keeping records.

Correct Answer: B. It may have acted as an unintended proxy unrelated to genuine fraud risk.