Competition Law and Insurtech Competition Challenges

1. Introduction

Insurtech refers to the use of digital technologies to provide, distribute, price, underwrite, administer, and claim insurance. It includes:

online insurance marketplaces;

digital brokers;

AI-based underwriting;

automated claims processing;

telematics;

embedded insurance;

comparison platforms;

insurance APIs;

digital identity and KYC systems;

health and behavioural data analytics;

algorithmic pricing;

blockchain-based insurance systems;

insurtech aggregators;

AI-driven fraud detection.

Insurtech can increase competition by lowering transaction costs, improving price comparison, expanding access, reducing underwriting costs and enabling new entrants.

At the same time, it can create new competition problems because insurance increasingly depends upon data, algorithms, platforms, interoperability, distribution networks and technological infrastructure.

The central competition-law question is:

When does technological innovation in insurance improve competition, and when can control over data, platforms, algorithms, distribution or infrastructure be used to exclude competitors or reinforce market power?

2. Main Competition Challenges in Insurtech

The principal competition issues include:

concentration of insurance data;

algorithmic pricing and coordination;

digital comparison-platform power;

exclusionary platform contracts;

tying and bundling;

discriminatory access to insurance APIs;

data portability and switching costs;

vertical integration between insurers and distributors;

preferential ranking on insurance marketplaces;

exclusionary use of AI underwriting;

network effects;

mergers and acquisitions involving insurtech startups;

access to payment and identity infrastructure;

algorithmic discrimination;

standardisation and interoperability;

embedded-insurance foreclosure.

3. Data as a Source of Insurtech Market Power

Insurance is an unusually data-intensive industry.

Insurers can possess information concerning:

claims;

risk profiles;

driving behaviour;

health characteristics;

property;

location;

customer history;

pricing;

fraud;

mortality;

credit-related information.

An established insurer can therefore possess a substantial data advantage over a new entrant.

Competitive concern

Suppose an incumbent possesses millions of historical claims records while a new AI insurer does not.

The incumbent may be able to train more accurate underwriting models.

This can create a feedback loop:

More customers → more data → better algorithms → better risk assessment → lower costs → more customers → more data.

This is sometimes described as a data-network or learning effect.

However, possession of valuable data is not automatically an antitrust violation.

Competition law becomes relevant where the data advantage is combined with exclusionary conduct.

4. Case Law: United States v Microsoft

United States v Microsoft Corp., 253 F.3d 34 (D.C. Cir. 2001)

Microsoft concerned exclusionary conduct associated with Microsoft's dominant position in PC operating systems.

The case is important for insurtech because it illustrates how technological ecosystems can generate competitive advantages beyond the immediate product.

Insurtech relevance

A dominant insurance platform could potentially control:

customer access;

insurance APIs;

claims infrastructure;

distribution;

comparison services;

data interfaces.

If those components are used to disadvantage competing insurers or brokers, competition authorities may examine the conduct under abuse-of-dominance principles.

The case therefore provides an important framework for understanding technology-enabled foreclosure.

5. Digital Insurance Aggregators and Gatekeeper Power

Online insurance comparison platforms can become important intermediaries between:

insurers ↔ consumers.

A successful aggregator may possess:

large consumer traffic;

extensive behavioural data;

detailed pricing information;

insurer performance information;

customer reviews;

switching information.

Network effects can arise:

More insurers → more choice → more consumers → more traffic → greater insurer dependence → more insurers.

A platform can therefore become a competitive bottleneck.

6. Case Law: Google Shopping

Google Search (Shopping), Case AT.39740

The European Commission found that Google had systematically positioned and displayed its comparison-shopping service more favourably than competing comparison services.

Although the case was not about insurance, it is highly relevant to digital insurance marketplaces.

Application to insurtech

Suppose an insurance comparison platform owns or is affiliated with an insurance company.

It might theoretically:

rank its own insurance products more prominently;

place competitors lower;

manipulate recommendation systems;

give affiliated products greater visibility;

use consumer data obtained from the platform to benefit its insurance business.

Such conduct could raise self-preferencing and discriminatory-access concerns, depending on the applicable legal framework and evidence.

The important point is that the competition issue concerns the use of platform control, not merely the existence of vertical integration.

7. Insurtech and Self-Preferencing

Self-preferencing can arise where a platform simultaneously acts as:

marketplace;

intermediary;

data collector; and

insurance provider.

For example:

Insurance marketplace → consumer data → ranking algorithm → affiliated insurer.

The platform could potentially gain an informational advantage over independent insurers.

Competition authorities may therefore examine:

ranking criteria;

recommendation algorithms;

access to customer data;

visibility rules;

commissions;

search placement;

disclosure requirements.

8. Case Law: Google Android

Google Android, Case AT.40099

The European Commission examined restrictions associated with Google's Android ecosystem.

The case illustrates how a firm with power over an important technological platform can potentially use contractual arrangements to reinforce its position across complementary markets.

Insurtech relevance

A similar issue could theoretically arise where a major digital ecosystem controls:

mobile operating systems;

digital wallets;

identity systems;

app distribution;

insurance applications.

If access to these complementary services is conditioned upon accepting exclusionary restrictions, competition authorities may investigate the arrangement.

9. Algorithmic Pricing in Insurance

AI can allow insurers to calculate premiums using extremely large datasets.

Potential inputs can include:

driving behaviour;

claims history;

location;

vehicle information;

customer behaviour;

risk characteristics.

Algorithmic pricing can increase efficiency.

But competition concerns arise where competing insurers use algorithms that:

exchange competitively sensitive information;

automatically respond to competitors' prices;

coordinate pricing;

reduce independent decision-making.

10. Algorithmic Collusion

Traditional cartel law generally looks for:

communication;

agreement;

coordination;

concerted practices.

Algorithms complicate evidence collection.

Two insurers might independently deploy pricing systems that monitor competitors and automatically adjust prices.

The mere use of similar algorithms does not automatically establish a cartel.

The competition authority must examine whether there is:

communication;

information exchange;

agreement;

coordination;

conscious facilitation;

or other legally relevant conduct.

This requires specialised computational investigation.

11. Case Law: Eturas

Eturas UAB and Others, Case C-74/14

The CJEU considered the use of an electronic booking platform through which a technical mechanism could facilitate uniform commission restrictions.

The case is particularly useful for understanding the intersection between:

technology + information + coordination + competition law.

Insurtech relevance

If an insurance platform distributes pricing information or imposes technical mechanisms that facilitate coordinated pricing among insurers, competition authorities may need to examine the platform's technical architecture.

The lesson is that competition investigations cannot focus exclusively on emails and traditional communications.

They may also need to examine:

software settings;

algorithms;

system messages;

platform configurations;

API communications.

12. Telematics and Data-Based Competition

Telematics can collect driving data such as:

speed;

braking;

acceleration;

mileage;

driving patterns;

location.

This data can be used to offer personalised motor insurance.

Competition concerns can arise if one company controls an essential or commercially important data stream.

For example:

vehicle manufacturer → telematics data → insurer → personalised insurance.

If competing insurers cannot access equivalent data, the manufacturer or integrated insurer could gain an advantage.

13. Case Law: IMS Health v NDC Health

IMS Health GmbH & Co. OHG v NDC Health, Case C-418/01

The CJEU addressed the relationship between intellectual-property protection and access to an important information structure.

The case established a restrictive framework for imposing compulsory access to protected assets.

Insurtech relevance

Insurance ecosystems may contain proprietary:

datasets;

analytical structures;

software;

classification systems;

APIs.

Competition law does not automatically require firms to share proprietary data.

However, exceptional circumstances may make access issues relevant under refusal-to-deal or essential-facility principles.

Thus, competition authorities must balance:

innovation incentives ↔ competitive access.

14. Insurtech APIs and Interoperability

APIs can allow:

banks to connect to insurers;

brokers to access quotes;

comparison platforms to retrieve insurance products;

claims platforms to exchange information;

customers to transfer information.

A dominant insurance infrastructure provider could potentially restrict API access to disadvantage competitors.

Potential concerns include:

discriminatory access;

excessive technical restrictions;

refusal to interoperate;

degrading access quality;

discriminatory API pricing.

15. Case Law: Bronner

Oscar Bronner GmbH & Co. KG v Mediaprint, Case C-7/97

The CJEU developed a strict framework concerning when refusal to provide access to infrastructure can constitute abuse of dominance.

The case is highly relevant to digital insurance infrastructure.

Application

An insurtech platform should not automatically be required to open every proprietary system to competitors.

Authorities would need to consider questions such as:

Is the infrastructure indispensable?

Can competitors realistically replicate it?

Would refusal eliminate effective competition?

Is access technically and economically feasible?

Are there objective justifications?

This prevents competition law from becoming a general compulsory-sharing mechanism.

16. Embedded Insurance

Embedded insurance integrates insurance into another product.

Examples include:

travel insurance at airline checkout;

device insurance at electronics purchase;

automobile insurance during vehicle purchase;

insurance embedded in financial applications.

This can increase convenience.

But vertical integration can also produce foreclosure risks.

For example:

Automobile platform → financing → insurance → repair network.

The platform might condition access to one service on acceptance of another.

17. Tying and Bundling

Insurtech ecosystems can generate tying concerns.

Potential examples include:

insurance tied to financing;

insurance tied to payment services;

insurance tied to telematics;

insurance tied to cloud services;

insurance tied to identity systems.

The competition question is whether the arrangement produces exclusionary effects and whether the products are sufficiently distinct for tying analysis.

18. Case Law: Microsoft Corp. v Commission

Microsoft Corp. v Commission, Case T-201/04

The European Union Microsoft litigation provides an important framework for analysing tying, interoperability and ecosystem power.

Insurtech relevance

Suppose a dominant insurance technology provider supplies:

claims software;

customer-management software;

underwriting systems;

and conditions access to one service on the purchase or use of another.

Competition authorities could examine whether the arrangement forecloses competing providers.

The case demonstrates why competition authorities must examine the architecture of digital ecosystems, not just individual products.

19. Vertical Integration Between Insurers and Platforms

An insurer may acquire:

a broker;

comparison website;

claims platform;

telematics provider;

healthcare-data platform;

payment company;

AI underwriting startup.

Vertical integration can generate efficiencies.

But it can also create foreclosure.

For example:

Insurer owns marketplace → marketplace controls customer traffic → rival insurers become dependent on the marketplace.

The authority must distinguish legitimate efficiencies from exclusionary strategies.

20. Insurtech Mergers and Killer Acquisitions

AI-driven insurtech startups may have:

low turnover;

high technological value;

proprietary data;

talented engineers;

novel underwriting models.

A large insurer may acquire such a company before it becomes a major competitor.

Traditional turnover-based merger thresholds may therefore fail to capture some strategically significant transactions.

Competition authorities may need to examine:

innovation potential;

data assets;

future competitive constraints;

pipeline products;

technological capabilities;

customer acquisition potential.

21. Case Law: FTC v Facebook/Meta

The litigation concerning Facebook's acquisitions of Instagram and WhatsApp illustrates the broader issue of acquisitions of emerging digital competitors.

Its relevance to insurtech is primarily analogical.

An established insurance platform acquiring an innovative insurtech startup may eliminate a future competitive constraint even if the target currently has:

small revenues;

limited market share;

relatively few customers.

The authority must therefore examine competitive potential rather than relying exclusively on current market position.

22. Data Portability and Customer Lock-In

Customers may find it difficult to change insurers because information is spread across:

insurance platforms;

brokers;

healthcare providers;

telematics systems;

claims databases;

identity systems.

High switching costs can reduce competitive pressure.

Competition authorities may therefore examine whether firms:

make data portability unnecessarily difficult;

impose restrictive contractual terms;

prevent interoperability;

make switching technically costly.

However, privacy and data-protection law must also be considered.

23. Case Law: Google Android and Switching Costs

The Android case demonstrates how restrictions across a technological ecosystem can affect competitive conditions.

In insurtech, similar concerns could arise when customers depend upon an integrated ecosystem consisting of:

identity + payment + insurance + claims + healthcare + financial services.

The more services become interconnected, the more difficult switching can become.

24. AI Underwriting and Entry Barriers

AI underwriting may generate economies of scale.

A large insurer may possess:

huge datasets;

computing resources;

actuarial expertise;

AI specialists;

established customer relationships.

This can produce a substantial learning advantage.

A new insurer may therefore face a combination of:

data disadvantage + capital disadvantage + customer-acquisition disadvantage + regulatory compliance costs.

None of these alone necessarily establishes unlawful conduct.

The competition concern becomes stronger where an incumbent deliberately uses its position to prevent rivals from obtaining competitively necessary inputs.

25. Exclusive Distribution Agreements

Insurers and platforms may enter agreements involving:

exclusivity;

preferred placement;

commission arrangements;

loyalty incentives;

bundled distribution.

These arrangements can sometimes be efficient because they:

reduce transaction costs;

encourage investment;

create predictable distribution.

But exclusivity can also foreclose competing insurers where a powerful intermediary controls an important route to customers.

26. Case Law: Intel

Intel Corp. v Commission, Case C-413/14 P

The CJEU's Intel litigation is important for analysing exclusionary rebate arrangements.

Insurtech application

Suppose a dominant insurance platform gives distributors significant financial incentives conditional upon dealing predominantly or exclusively with its affiliated insurance products.

The authority may need to examine:

the structure of the rebates;

coverage;

duration;

foreclosure capability;

competitive effects;

efficiencies.

The lesson is that formal contract language alone may not reveal the actual competitive effects.

27. Refusal to Deal and Essential Digital Infrastructure

Insurtech could involve potential bottlenecks such as:

claims databases;

identity verification;

vehicle telematics;

payment infrastructure;

insurance APIs;

comparison platforms.

But competition law should not automatically convert every commercially valuable database or API into an essential facility.

Aspen Skiing

Aspen Skiing Co. v Aspen Highlands Skiing Corp., 472 U.S. 585 (1985)

The case provides a narrow framework concerning refusal to deal.

Its relevance is that competition authorities may examine whether conduct represents an intentional exclusion of a rival rather than simply an independent business decision.

28. Standardisation in Insurtech

Insurance increasingly depends upon common standards for:

claims information;

digital identity;

APIs;

electronic policy documentation;

telematics;

risk classifications.

Standard-setting can promote interoperability.

But competitors participating in standard-setting can theoretically use the process to:

exclude rivals;

impose discriminatory requirements;

favour proprietary technology;

disadvantage new entrants.

29. Case Law: Allied Tube & Conduit v Indian Head

Allied Tube & Conduit Corp. v Indian Head, Inc., 486 U.S. 492 (1988)

The U.S. Supreme Court examined exclusionary conduct associated with private standard-setting.

Insurtech relevance

If insurers or technology providers collectively develop technical standards, competition authorities should examine whether the standard-setting process:

genuinely improves interoperability;

establishes legitimate technical requirements;

or is being used strategically to exclude competing technologies.

30. Insurance Marketplaces and Self-Preferencing

A major future issue may be:

Should an insurance marketplace that sells its own insurance products be permitted to rank those products more favourably?

Competition analysis may consider:

market power;

transparency;

ranking criteria;

consumer choice;

availability of alternatives;

effects on rival insurers;

efficiencies.

Google Shopping provides a useful framework, although it does not automatically establish that every instance of self-preferencing is unlawful.

31. Competition Concerns in Health Insurtech

Health-insurance technology can involve highly valuable information.

Potential data sources include:

medical records;

claims histories;

prescription information;

wearable devices;

health applications.

Competition issues may arise if a vertically integrated company controls both:

health-data infrastructure + insurance distribution.

But competition analysis must be coordinated carefully with privacy and health-data regulation.

32. Insurtech and Consumer Discrimination

Algorithmic underwriting can generate differential treatment.

Competition law and discrimination law are not identical.

A pricing algorithm may produce discriminatory outcomes without necessarily violating competition law.

Competition authorities should therefore distinguish:

consumer-protection concerns;

privacy concerns;

discrimination concerns;

competition concerns.

The same conduct may potentially raise multiple regulatory issues, but each legal regime has its own requirements.

33. Indian Competition Law

The Competition Act, 2002 provides several relevant provisions.

Section 3

Section 3 addresses anti-competitive agreements.

Potential insurtech issues include:

coordinated premium-setting;

information exchange;

restrictive platform arrangements;

bid rigging;

exclusionary vertical agreements.

Section 4

Section 4 concerns abuse of dominant position.

Potential insurtech theories include:

denial of market access;

discriminatory API access;

unfair contractual conditions;

tying;

bundling;

leveraging;

discriminatory treatment of rival insurers.

Again:

Being a large insurer or platform is not itself unlawful. The concern is abuse of dominant position.

Sections 5 and 6

These provisions become relevant to combinations involving:

insurers;

insurance technology companies;

digital brokers;

data platforms;

payment systems;

healthcare technology companies.

The CCI may need to examine whether a transaction strengthens control over an important digital ecosystem.

34. Important Indian Regulatory Interface

Insurtech competition does not operate in isolation.

The sector can intersect with:

Insurance Regulatory and Development Authority of India;

Competition Commission of India;

Reserve Bank of India where payment/financial infrastructure is involved;

data-protection authorities;

consumer-protection authorities.

Institutional coordination is therefore particularly important.

35. Six Major Competition-Law Lessons for Insurtech

36. Practical Competition-Law Test for Insurtech

When investigating an insurtech practice, a competition authority can ask:

Step 1 — What is the relevant market?

Is it:

insurance?

digital brokerage?

comparison services?

telematics?

claims processing?

insurance APIs?

AI underwriting?

Step 2 — Who controls the bottleneck?

Possible bottlenecks include:

data;

customers;

technology;

distribution;

APIs;

infrastructure.

Step 3 — Is there substantial market power?

Consider:

market share;

network effects;

switching costs;

data advantages;

entry barriers;

vertical integration.

Step 4 — What conduct is occurring?

Examples:

tying;

bundling;

exclusivity;

discrimination;

self-preferencing;

refusal to deal;

rebates;

information exchange.

Step 5 — What are the competitive effects?

Does the conduct:

exclude rivals?

increase entry barriers?

reduce innovation?

increase switching costs?

reduce consumer choice?

increase prices?

reduce quality?

Step 6 — Are there efficiencies?

Potential justifications include:

fraud reduction;

lower underwriting costs;

improved claims processing;

risk reduction;

cybersecurity;

consumer convenience.

37. Key Institutional Challenge: Balancing Innovation and Competition

Insurtech competition policy must avoid two opposite errors.

Error 1: Treating innovation as automatically pro-competitive

A technological innovation can simultaneously produce substantial entry barriers.

Error 2: Treating technological integration as automatically anticompetitive

Integration can generate:

better underwriting;

faster claims;

lower costs;

fraud detection;

improved customer experience.

The appropriate analysis therefore focuses on competitive effects and evidence, rather than the mere presence of technology.

38. Future Insurtech Competition Issues

Future investigations are likely to involve:

AI insurance agents

Autonomous systems comparing and purchasing policies.

Machine-to-machine insurance

Connected vehicles and devices automatically selecting coverage.

Predictive underwriting

Continuous risk assessment using real-time data.

Embedded insurance ecosystems

Insurance integrated into finance, transportation and commerce.

Insurance super-apps

Multiple insurance and financial services controlled by one platform.

Data monopolisation

Large insurers accumulating uniquely valuable datasets.

Algorithmic coordination

Automated systems responding to competitors' pricing.

AI claims systems

Automated claims decisions affecting market competition.

Digital identity infrastructure

Control over identity verification affecting insurance-market access.

39. Conclusion

Insurtech can substantially improve competition by reducing transaction costs, increasing price transparency, expanding distribution, improving underwriting and allowing new firms to enter insurance markets.

However, the same technologies can create new forms of market power.

The most important competition challenges concern data concentration, algorithmic pricing, platform gatekeeping, self-preferencing, interoperability, APIs, exclusivity, vertical integration, AI underwriting, network effects and acquisitions of emerging competitors.

The case law of Microsoft, Google Shopping, Google Android, IMS Health, Bronner, Intel, Aspen Skiing, Allied Tube and Eturas provides useful legal frameworks for addressing these issues, although most are not insurance-specific and should therefore be applied by analogy rather than treated as direct insurtech precedents.

For Indian competition law, Sections 3 and 4 of the Competition Act, 2002, together with merger-control provisions under Sections 5 and 6, provide the principal competition framework. The central legal principle remains that innovation, scale, data ownership or technological sophistication is not itself unlawful; the competition concern arises when market power is used through legally prohibited conduct to restrict or distort competition.