15. Strategy, Governance and the Future of Insurance Markets

Introduction and Context

Insurance markets are shaped by a distinctive strategic problem: insurers must create value under uncertainty while preserving the financial capacity to meet promises that may mature many years later. Marketing, distribution and customer relationship management therefore cannot be treated as isolated commercial functions. Product design affects risk selection; distribution affects customer understanding and conduct risk; remuneration affects advice quality; data affects underwriting and service; and governance determines whether growth is sustainable.

The strategic insurer is not simply the organisation that sells the largest volume of policies. It is the organisation that selects attractive markets, constructs a balanced portfolio, builds trusted relationships, controls conduct and third-party risks, and adapts its operating model to technological and social change. This chapter integrates these concerns through competitive strategy, portfolio thinking, scenario analysis and governance. It also considers open insurance, generative artificial intelligence, prevention-led propositions and changing customer expectations.

Insurance strategy is increasingly influenced by digital platforms, embedded distribution, climate-related events, cyber threats, demographic change and regulatory scrutiny. These developments create opportunities for reach and efficiency, but they also intensify questions about fairness, explainability, privacy, resilience and accountability. Strategic success consequently requires both commercial imagination and institutional discipline.

Learning Objectives

After studying this chapter, students should be able to:

1. Formulate integrated growth strategies for insurance businesses using competitive, portfolio and scenario frameworks.

2. Analyse the relationship between customer value, profitability, risk selection and market conduct.

3. Design governance approaches for remuneration, intermediaries, third parties, data and sustainability.

4. Evaluate the strategic implications of open insurance, generative AI and prevention-led insurance models.

5. Apply strategic reasoning to an insurance market case and identify suitable managerial actions.

6. Assess future customer expectations and translate them into distribution and relationship strategies.

From Growth Targets to Strategic Choices

A growth target such as “increase premium by 20 per cent” is not, by itself, a strategy. Strategy explains where growth will come from, why the organisation can win, what capabilities are required, and how risk will be controlled. In insurance, growth must be examined through at least four linked questions.

First, which customer segments and risks should the insurer serve? A market may be large but unattractive because of intense competition, poor data, volatile claims or weak payment capacity. Conversely, a smaller segment may offer strong retention and profitable cross-selling. Second, what customer proposition will distinguish the insurer? Differentiation may be based on price, specialist expertise, claims quality, convenience, prevention services or trust. Third, which channels and partners will provide efficient and appropriate access? Finally, how will the insurer monitor whether growth is producing sustainable value rather than merely increasing exposure?

A useful strategic hierarchy is:

• Purpose and risk appetite: the type and level of risk the organisation is prepared to accept.
• Market choice: selected customer groups, geographies, products and ecosystems.
• Value proposition: the reason customers, intermediaries and partners should choose the insurer.
• Operating model: people, processes, technology, capital and partners required to deliver the proposition.
• Control and learning: measures, governance and feedback used to correct the strategy.

This hierarchy prevents a common mistake: selecting a distribution opportunity before determining whether the associated customers, risks and service obligations fit the insurer’s capabilities.

Competitive Strategy in Insurance

Competitive strategy concerns how an insurer achieves a defensible position relative to competitors. Traditional approaches include cost leadership, differentiation and focus. Their application in insurance requires adaptation because the product is intangible, claims are uncertain and customers often judge the insurer most clearly when a loss occurs.

A cost-oriented strategy depends on efficient underwriting, automation, low acquisition expense, disciplined claims management and scale. It is vulnerable if price competition attracts poorly understood risks or if cost reduction damages service quality. A differentiation strategy may emphasise specialist underwriting, superior claims advocacy, rapid settlement, risk engineering, transparent communication or a distinctive customer experience. Differentiation is credible only when customers perceive and value the difference. A focus strategy concentrates on a defined segment, such as small exporters, renewable-energy firms, professional practices or elderly customers, and develops expertise that generalist competitors lack.

Porter’s five competitive forces remain useful, although they must be interpreted carefully in insurance. Rivalry is affected by pricing cycles, capital availability and product similarity. Buyer power increases when customers can compare prices easily or when large commercial buyers negotiate directly. Intermediaries may exercise substantial channel power because they control access to customers. Supplier power includes reinsurers, technology providers, repair networks, data providers and claims specialists. Substitution may arise from self-insurance, risk prevention, warranties, public compensation arrangements or platform-based protection. New entrants may be digital firms, technology companies or established firms from adjacent sectors rather than traditional insurers.

A strategic assessment should therefore distinguish between market attractiveness and competitive capability. A promising market is not necessarily suitable for every insurer. The relevant question is whether the insurer possesses an advantage that can be maintained after competitors respond.

Portfolio Logic: Balancing Growth and Resilience

An insurer should manage products and segments as a portfolio rather than as unrelated sales lines. Portfolio strategy examines the combination of risks, customer relationships, capital requirements and cash flows. The objective is not simply diversification. Poorly selected risks can become correlated during a crisis, so a portfolio must be assessed for common drivers such as inflation, interest rates, catastrophe exposure, litigation trends, cyber dependency or supply-chain disruption.

A practical portfolio map can classify businesses according to market attractiveness and organisational strength:

1. Invest and scale: attractive market and strong capability.

2. Build selectively: attractive market but capability gaps require investment.

3. Harvest and improve: moderate opportunity with established cash generation.

4. Exit, restructure or partner: weak attractiveness or inadequate strategic fit.

This map should be supplemented by portfolio measures. These include growth rate, retention, acquisition cost, loss ratio, expense ratio, combined ratio, customer lifetime value, complaint frequency, solvency or capital consumption, concentration and exposure to adverse scenarios. No single measure is sufficient. High retention can conceal unprofitable pricing; a low complaint rate can reflect barriers to complaint submission; and rapid digital acquisition can produce attractive initial volumes but weak persistency.

Customer lifetime value is particularly useful when interpreted cautiously. It estimates the present value of expected future contribution from a customer, after acquisition, service and claims-related costs. Its use should not encourage unfair treatment of customers who appear less profitable. Strategic portfolio management must balance commercial economics with legal duties, product suitability and the broader reputation of the institution.

Reinsurance is also a portfolio tool. It can reduce volatility, protect capital and support entry into unfamiliar markets. However, reinsurance does not remove the need for sound underwriting. It transfers specified risk under contractual conditions and introduces counterparty, basis and availability risks.

Scenario Planning and Strategic Resilience

Forecasting attempts to identify the most likely future; scenario planning explores several plausible futures and asks whether the strategy remains viable under each. This is especially valuable for insurance because uncertainty is structural. Climate patterns, regulation, technology, customer behaviour and claims inflation may change in combinations that historical data cannot fully represent.

A scenario process normally involves four stages. The organisation first identifies critical uncertainties and predetermined trends. It then constructs a small number of coherent scenarios, tests the current strategy against them, and identifies indicators that would signal movement toward a particular future. Scenarios should be plausible and internally consistent rather than dramatic stories designed merely to alarm managers.

For example, an insurer might examine:

• a regulated trust economy, in which customers value explainability and regulators impose strict controls on data and AI;
• a platform convenience economy, in which insurance is embedded into purchases and digital ecosystems dominate customer access;
• a high-volatility protection economy, in which climate losses, cyber incidents and inflation increase demand but also threaten affordability and capacity; and
• a prevention partnership economy, in which insurers earn value by reducing the frequency and severity of losses rather than paying only after events occur.

For each scenario, managers should assess product demand, pricing adequacy, claims costs, distribution economics, capital needs, technology requirements and governance. The outcome may be a set of no-regret investments, such as data quality, cyber resilience and employee capability; contingent actions, such as entering a new platform partnership; and strategic boundaries, such as refusing business that cannot be monitored fairly.

Governance as a Strategic Capability

Governance is not merely a compliance layer added after commercial decisions. It defines accountability, decision rights, controls and escalation mechanisms through which strategy becomes reliable. Strong governance allows an insurer to innovate while making risk visible and manageable.

The board is responsible for direction, oversight and the organisation’s risk culture. Senior management translates strategy into policies, budgets, targets and operating processes. Independent risk, compliance, actuarial, audit and data-governance functions provide challenge, although their exact structure varies by jurisdiction and organisational size. Effective governance requires clear ownership: a committee cannot substitute for an accountable executive.

A useful governance test asks four questions:

1. Who made the decision?

2. What information and assumptions supported it?

3. What risks and customer effects were considered?

4. How will performance and unintended consequences be monitored?

These questions apply to product approval, pricing changes, intermediary appointments, AI deployment, outsourcing and sustainability claims. Documentation should be proportionate but sufficiently clear to permit challenge and later review.

Market Conduct and Customer Outcomes

Market conduct concerns how an insurer behaves toward customers and markets. It includes fair product design, clear communication, appropriate sales practices, claims handling, complaint management, privacy and treatment of vulnerable customers. Conduct risk can arise even where an action is technically lawful. A complex product may satisfy disclosure requirements but still be poorly understood; a sales incentive may not explicitly reward mis-selling but may create pressure that produces it.

Customer-outcome monitoring should cover the entire product life cycle: target-market definition, design, testing, distribution, renewal, claims, complaints and withdrawal. Useful indicators include cancellation and lapse rates, claims repudiation patterns, turnaround times, vulnerable-customer outcomes, sales-quality reviews, complaints by channel and the relationship between remuneration and persistency. Indicators must be interpreted rather than followed mechanically. A high claims acceptance rate, for example, may be positive, but it could also reflect inadequate fraud controls or changes in claim complexity.

Remuneration and Incentive Governance

Remuneration influences behaviour. Commission, bonuses and non-financial recognition can encourage volume, retention, cross-selling, profitable underwriting or high-quality service. They can also encourage unsuitable sales, excessive risk-taking or claims avoidance. Balanced scorecards should therefore combine financial measures with quality and conduct measures, such as persistency, complaint outcomes, audit findings, suitability assessments and customer satisfaction.

Clawbacks, deferred rewards and approval thresholds can reduce short-termism, but they are not substitutes for ethical leadership and effective supervision. Distribution partners should receive transparent remuneration terms, and conflicts should be identified and managed. Managers should be particularly cautious where one party controls customer access while another bears claims and reputational consequences.

Third-Party and Distribution Governance

Intermediaries, aggregators, affinity partners, repair networks, cloud providers and data vendors may perform activities that materially affect customers. Outsourcing a task does not outsource accountability. A third-party framework should include due diligence, financial and operational assessment, licensing checks, information-security review, service-level standards, audit rights, incident reporting, business continuity and exit planning.

The insurer should understand the complete customer journey across the distribution chain. A customer may experience a brand through a comparison site, a call centre, a payment provider and a claims contractor. Fragmented responsibility creates “conduct gaps” in which no party sees the total outcome. Contracts should therefore be supported by monitoring, training, shared data standards and escalation arrangements.

Data, Privacy and Model Governance

Data is a strategic asset only when it is accurate, relevant, lawfully obtained, secure and used for a legitimate purpose. Insurance data governance addresses ownership, access, quality, retention, lineage, consent and accountability. Particular care is required when data is sensitive, inferred or obtained from connected devices.

Model governance applies to pricing, underwriting, fraud detection, marketing propensity, claims triage and customer service. A model should have a defined purpose, documented data sources, validation, performance monitoring, bias assessment, human oversight and a process for handling errors and complaints. Explainability is not merely a technical feature; it is a communication and accountability requirement. Customers and staff should be able to understand material reasons for decisions sufficiently to challenge them where appropriate.

Generative AI creates additional risks because systems may produce inaccurate, fabricated or inconsistent outputs, disclose confidential information or reproduce bias in training data. Appropriate uses may include drafting customer communications, summarising documents, assisting employees and supporting knowledge retrieval. High-impact decisions should not be delegated without controls, human review, audit trails and testing for reliability and unfair outcomes.

Sustainability and Responsible Insurance

Sustainability has strategic, financial and conduct dimensions. Insurers influence society through underwriting, investment, claims practices and risk-prevention advice. Climate change may alter hazard frequency, asset values, affordability and availability of cover. Social issues include accessibility, vulnerable customers, labour practices in supply chains and the fairness of automated decisions.

Responsible strategy requires credible measurement rather than broad claims. An insurer should identify material environmental and social risks, establish governance ownership, use relevant metrics and communicate limitations. Sustainable insurance is not achieved simply by excluding difficult risks. Exclusions may protect capital but can also reduce social resilience. Alternatives include risk-improvement requirements, adaptation incentives, parametric solutions, public-private partnerships and carefully designed coverage limits.

Open Insurance, Platforms and New Value Chains

Open insurance refers broadly to the controlled sharing and use of insurance-related data and services across authorised organisations. It may be enabled by APIs, consent mechanisms, digital identity and common data standards. Potential benefits include more accurate offers, easier switching, embedded protection and improved service continuity. It may also intensify competition and reduce the insurer’s direct relationship with the customer.

Embedded insurance places protection within a non-insurance transaction, such as travel booking, vehicle purchase, equipment leasing or digital payments. It can reduce search costs and improve timing, but convenience may conceal limited choice or inadequate understanding. Governance must clarify who designs the product, who provides advice, who handles complaints and who is accountable for claims.

Platform strategy creates a central strategic tension. A platform can provide reach and behavioural insight, while the insurer may become dependent on a powerful intermediary that controls ranking, data and customer access. Before entering such arrangements, an insurer should assess economics, exclusivity, data rights, brand visibility, portability of customers, operational resilience and the possibility of partner failure.

Prevention-Led Insurance and the Changing Customer Relationship

Traditional insurance primarily compensates customers after a loss. Prevention-led insurance adds services and incentives intended to reduce the probability or severity of loss. Examples include telematics-based driving feedback, leak detection, cyber-security monitoring, health and wellness support, agricultural weather alerts and engineering advice for commercial risks.

The model can create mutual value: customers experience fewer disruptions, while insurers may reduce claims and improve engagement. Yet prevention is not automatically beneficial. Monitoring can become intrusive; incentives can penalise customers who cannot afford protective technology; and responsibility may be unfairly shifted from institutions to individuals. Prevention programmes should therefore be voluntary or transparently justified, accessible, evidence-based and designed with clear data safeguards.

Future customers are likely to expect immediate service, personalised interaction, transparent pricing, simple language, flexible coverage and effortless claims. They may also expect the insurer to demonstrate social responsibility. However, expectations are not uniform. Some customers value digital self-service, while others need human assistance because of age, disability, language, financial stress or the complexity of a claim. A genuinely customer-centred strategy offers choice rather than assuming that digital is always superior.

An Integrated Strategic Process

An integrated strategy can be developed through the following sequence:

1. Diagnose the environment: analyse customers, competitors, regulation, technology, macroeconomic conditions and social risks.

2. Define strategic intent: specify purpose, target markets, value proposition and risk appetite.

3. Select the portfolio: assess products and segments for attractiveness, capability, capital use, correlation and customer value.

4. Choose channels and partners: compare direct, intermediary, platform, embedded and hybrid routes.

5. Design the operating model: align people, processes, technology, data, claims capability and capital.

6. Build governance: establish accountability, controls, remuneration principles, third-party oversight and model governance.

7. Test scenarios: examine resilience under plausible changes in claims, regulation, technology and customer behaviour.

8. Implement and learn: use milestones, outcome measures, customer feedback and independent challenge to adapt the strategy.

The process is iterative. A strategic assumption may be disproved by claims experience or customer research, requiring repricing, redesign or withdrawal. Strategic discipline includes the willingness to stop initiatives that no longer meet their intended objectives.

Illustrative Case: Horizon Shield Insurance

Background

Horizon Shield is a fictional mid-sized insurer operating in personal motor and household insurance. It has a recognised brand and a large intermediary network but is losing younger customers to digital competitors. Its combined ratio has deteriorated because of repair-cost inflation, fraud and severe weather losses. Management proposes a mobile application, telematics-based motor insurance, an open-data partnership with a vehicle platform and a generative-AI claims assistant.

Situation and Problem

The proposals promise lower acquisition costs and improved engagement, but the board identifies several uncertainties. The vehicle platform wants extensive access to customer and driving data. Brokers fear that direct digital channels will weaken their relationships. Telematics may disadvantage customers with limited digital access, while the AI claims assistant may produce incorrect explanations. Management also lacks a clear view of whether prevention services will reduce claims sufficiently to justify investment.

Analysis

A competitive analysis shows that Horizon cannot reliably win a pure price competition against large digital platforms. Its stronger assets are claims experience, local repair relationships and broker trust. Portfolio analysis indicates that motor is strategically important but exposed to inflation and technology-driven repair complexity. Scenario analysis produces three relevant futures: strict data regulation, rapid platform adoption and high-frequency weather losses.

The proposed initiatives are therefore not evaluated as one technology programme. Each is assessed against customer value, strategic fit, operational readiness, governance and scenario resilience. The board also separates decisions that are reversible, such as a limited pilot, from decisions that could create long-term dependency, such as exclusive data arrangements.

Approach and Strategy

Horizon adopts a phased strategy. It first improves claims data, repair-network controls and customer communication. It then pilots telematics with voluntary participation, transparent consent, non-digital alternatives and a review of differential outcomes. The open-data partnership is renegotiated so that data access is purpose-limited, portable where appropriate and subject to security and exit provisions. The generative-AI tool is restricted initially to internal document search and draft generation; claims decisions remain with trained staff.

The remuneration plan is revised so that channel rewards reflect persistency, complaint quality, appropriate disclosure and claims-service outcomes rather than sales volume alone. A cross-functional governance committee monitors the pilot, while internal audit reviews data access and model performance. Measures include retention, claims frequency, customer understanding, complaints, vulnerable-customer outcomes, fraud indicators, expense savings and employee overrides.

Outcome

The fictional pilot does not produce immediate dramatic growth. It does, however, reveal that telematics is attractive to some customers but unacceptable to others. Claims triage becomes faster for simple cases, while complex cases are escalated to human handlers. The insurer avoids an exclusive platform contract and retains strategic flexibility. Most importantly, the board obtains evidence about which investments improve customer outcomes and which merely create technological novelty.

Learning Points

The case illustrates that digital strategy must be connected to portfolio economics and governance. It also shows the value of phased experimentation, explicit customer safeguards, partner negotiation and scenario testing. Innovation is strategically valuable when it strengthens a distinctive capability and remains accountable to customers; it is weak when adopted simply because competitors use similar language.

Challenges, Risks and Common Strategic Errors

Insurance strategies commonly fail because managers confuse volume with value, underestimate claims complexity, rely on historical correlations, or treat distribution as separate from underwriting. Other errors include excessive dependence on a single platform, weak data lineage, incentives that reward sales without customer outcomes, and assuming that disclosure alone resolves fairness concerns.

Strategic plans can also become too detailed to guide choices. A plan should identify priorities, trade-offs and boundaries, not attempt to predict every event. Conversely, an attractive vision without funded capabilities is only an aspiration. Implementation requires accountable owners, sequencing, investment discipline and measures that can reveal failure early.

Technology introduces risks of cyberattack, vendor lock-in, privacy breach, model drift and operational concentration. Sustainability initiatives may generate greenwashing risk if claims are vague or unsupported. Prevention programmes may create surveillance concerns. These risks should be assessed at design stage rather than after public criticism or regulatory intervention.

Best Practices for Strategic Insurance Management

Effective practice can be summarised in several principles:

• Link growth decisions to risk appetite, capital, claims capability and customer outcomes.
• Treat products, channels and partners as parts of one customer journey.
• Use portfolio measures that combine profitability, resilience, conduct and social impact.
• Apply scenario planning to major strategic assumptions and investments.
• Make senior accountability explicit for third-party, data and AI risks.
• Use balanced remuneration that rewards sustainable value rather than volume alone.
• Introduce technology through controlled pilots, independent testing and clear exit options.
• Preserve human support for complex, vulnerable or contested customer situations.
• Communicate uncertainty, limitations and data use honestly.
• Build organisational learning through complaints, claims evidence, audits and customer research.

Chapter Summary

Insurance strategy integrates market choice, customer value, portfolio management, distribution, operating capability and governance. Competitive frameworks help insurers decide how to create a defensible position, while portfolio analysis balances growth, profitability, capital and correlation. Scenario planning tests whether strategic choices remain viable under uncertain technological, regulatory, climate and economic conditions.

Governance is a source of strategic strength. Market conduct, remuneration, third-party oversight, data governance, model controls and sustainability practices determine whether growth is trustworthy and resilient. Open insurance and embedded distribution can expand access but may weaken direct customer relationships or increase dependency on platforms. Generative AI can improve productivity but requires human oversight, validation and accountability. Prevention-led models may transform insurance from post-loss compensation to continuous risk partnership, provided privacy, accessibility and fairness are protected.

The central managerial lesson is that future-ready insurance is neither purely digital nor purely traditional. It combines disciplined risk selection, reliable claims service, responsible data use, flexible distribution and a governance culture capable of learning under uncertainty.

Key Terms

Competitive strategy: A coordinated approach for achieving a defensible position relative to competitors.

Cost leadership: Competing through superior efficiency and lower sustainable operating cost.

Differentiation: Creating valued distinctiveness in product, service, expertise or experience.

Market focus: Concentrating resources on a defined customer or risk segment.

Portfolio strategy: Managing products and risks collectively to balance return, capital and resilience.

Customer lifetime value: The expected present value of future contribution from a customer relationship.

Scenario planning: Exploring plausible alternative futures to test strategic resilience.

Risk appetite: The amount and type of risk an organisation is willing to accept.

Market conduct: Organisational behaviour affecting fairness, suitability and customer outcomes.

Conduct risk: The possibility that organisational actions produce unfair or harmful customer or market outcomes.

Remuneration governance: Controls ensuring that rewards do not encourage inappropriate or excessive risk-taking.

Third-party risk: Risk arising from suppliers, intermediaries, platforms or outsourced service providers.

Data governance: Policies and accountabilities governing data quality, access, use, security and retention.

Model governance: Processes for approving, validating, monitoring and controlling analytical models.

Open insurance: Controlled sharing and use of insurance data or services across authorised organisations.

Embedded insurance: Insurance offered within a non-insurance purchase or digital customer journey.

Prevention-led insurance: Insurance that combines protection with services intended to reduce loss frequency or severity.

Generative AI: Artificial intelligence capable of producing text, images, code or other content from learned patterns.

Customer outcome: The actual effect of an insurance product or process on the customer.

Strategic resilience: The capacity to remain effective and adapt under changing conditions.

Review Questions

Short Answer Questions

1. Why is premium growth alone an inadequate measure of insurance strategy?

2. What is the difference between competitive strategy and portfolio strategy?

3. Identify four matters that should be considered in third-party governance.

4. What is the purpose of scenario planning in insurance management?

5. Why does generative AI require model and human governance?

Long Answer Questions

1. Explain how cost leadership, differentiation and focus strategies can be applied to insurance markets.

2. Discuss the role of portfolio analysis in balancing growth, profitability, capital and resilience.

3. Examine how remuneration and market-conduct governance influence customer outcomes.

4. Analyse the opportunities and risks created by open insurance and embedded distribution.

5. Explain how an insurer can develop an integrated strategy from environmental diagnosis through implementation and learning.

Analytical / Application Questions

1. An insurer has rapidly increased digital sales, but retention is falling and complaints about unclear exclusions are rising. Using the frameworks in this chapter, diagnose the problem and recommend corrective actions.

2. Design a scenario-planning exercise for a household insurer facing climate-related losses, platform competition and stricter data regulation. Identify scenarios, indicators and no-regret investments.

3. Evaluate whether an insurer should introduce a voluntary telematics programme. Consider customer value, portfolio economics, privacy, fairness, governance and operational requirements.

22. Multiple Choice Questions with Answers

Question 1

Which statement best describes an integrated insurance growth strategy?

A. Increasing premium volume regardless of claims and conduct outcomes

B. Selecting markets, propositions, capabilities and controls that jointly support sustainable value

C. Using the cheapest available distribution channel for every product

D. Replacing underwriting judgement with automated sales targets

Correct Answer: B. Selecting markets, propositions, capabilities and controls that jointly support sustainable value

Question 2

An insurer has strong underwriting capability but operates in a stagnant and highly exposed market. In a portfolio map, the most appropriate initial conclusion is to:

A. Scale immediately because capability is strong

B. Ignore market attractiveness and maximise sales

C. Consider harvesting, restructuring or exiting unless a new opportunity is identified

D. Transfer all responsibility to intermediaries

Correct Answer: C. Consider harvesting, restructuring or exiting unless a new opportunity is identified

Question 3

What is the principal purpose of scenario planning?

A. To predict one certain future with precision

B. To replace financial planning and budgeting

C. To test strategy against several plausible futures and identify resilient actions

D. To justify any innovation proposed by management

Correct Answer: C. To test strategy against several plausible futures and identify resilient actions

Question 4

Which remuneration design is most consistent with sound conduct governance?

A. Rewarding sales volume only

B. Paying bonuses immediately for every policy sold

C. Combining financial results with persistency, complaints and customer-quality measures

D. Allowing each intermediary to set undisclosed incentives

Correct Answer: C. Combining financial results with persistency, complaints and customer-quality measures

Question 5

A cloud claims provider suffers a major outage. Which governance principle is most relevant?

A. Outsourcing transfers accountability to the provider

B. Third-party arrangements require resilience, incident reporting and exit planning

C. Customer outcomes are irrelevant if the contract is valid

D. The insurer should permanently avoid all technology providers

Correct Answer: B. Third-party arrangements require resilience, incident reporting and exit planning

Question 6

Which practice best supports responsible insurance use of customer data?

A. Collecting all available data without a defined purpose

B. Using inferred sensitive data without controls because it improves prediction

C. Applying purpose limitation, quality controls, security, accountability and appropriate consent

D. Allowing models to make unreviewable decisions

Correct Answer: C. Applying purpose limitation, quality controls, security, accountability and appropriate consent

Question 7

What is a distinctive feature of prevention-led insurance?

A. It pays claims only after a loss and provides no other service

B. It combines protection with actions intended to reduce the frequency or severity of losses

C. It eliminates the need for underwriting and pricing

D. It requires continuous surveillance of every customer

Correct Answer: B. It combines protection with actions intended to reduce the frequency or severity of losses

Question 8

Why can an exclusive arrangement with a powerful digital platform create strategic risk for an insurer?

A. It always reduces customer convenience

B. It may create dependency concerning customer access, data, ranking and exit

C. It prevents any form of embedded insurance

D. It automatically violates all insurance regulation

Correct Answer: B. It may create dependency concerning customer access, data, ranking and exit

Question 9

In the Horizon Shield case, why was the generative-AI claims tool initially limited to internal assistance?

A. Generative AI has no possible insurance application

B. Internal assistance allows controlled testing while complex claims decisions remain accountable to trained staff

C. Regulators require every AI tool to be used only for marketing

D. The insurer wanted to eliminate all human involvement gradually

Correct Answer: B. Internal assistance allows controlled testing while complex claims decisions remain accountable to trained staff

Question 10

Which measure would best indicate whether a digital insurance strategy is producing sustainable customer value?

A. Number of app downloads alone

B. Initial policy count without retention data

C. A combination of retention, claims experience, complaints, customer understanding and profitability

D. Amount spent on advertising alone

Correct Answer: C. A combination of retention, claims experience, complaints, customer understanding and profitability