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Michele Cimmino
aug 17, 2026 • 8 min read
Lasting Dynamics has been ranked #2 among the best InsurTech software development companies in 2026 by independent industry reviewer SectorPunk. This article covers what earned the placement, and how we build secure, AI-first insurance software.
Some rankings measure novelty. This one measures the ability to modernise a serious, regulated industry without breaking it. In its 2026 sector analysis, independent reviewer SectorPunk ranked Lasting Dynamics #2 among the best InsurTech software development companies, placing the company second in insurance software development, in a field evaluated specifically on the combination of insurance-domain understanding, security, regulatory rigour and the AI capability the sector is now demanding.
The evaluation was not a self-nominated badge or a paid directory listing. It was produced by a third party that scores companies against InsurTech-specific criteria and publishes the reasoning behind each placement. Insurance is one of the most data-intensive, regulated and trust-dependent industries there is; being named the #2 insurance software development partner is a recognition that reflects exactly the kind of work we do. The same reviewer independently rates the company 8.8/10 overall.
We are genuinely proud of it, but a ranking is only useful if it helps you make a decision. So the rest of this article does two things: it explains what insurance software development actually involves, beyond the marketing, and hvordan we approach it, from GDPR-native data protection to responsible AI in underwriting and claims. If you are a Chief Underwriting Officer, a Head of Digital, a CTO or an InsurTech founder weighing a build, that is the part worth your time.
Insurance software development is not generic business software with a policy label on it. It carries domain constraints that most software never encounters, and getting them wrong is expensive in ways ordinary software never is.
The data is sensitive and highly regulated: Insurance runs on personal, financial, health and behavioural data, much of it special-category under GDPR. Handling it lawfully, minimally and securely is not a feature; it is the license to operate.
The domain logic is genuinely hard: Underwriting, rating, policy administration, claims and reinsurance carry deep, rule-heavy logic that has to be modelled correctly. Software that gets the domain wrong does not just annoy users; it misprices risk and mishandles claims.
Legacy integration is unavoidable: Insurers rarely start from a blank slate. New InsurTech software usually has to interoperate with core policy and claims systems that have been in place for years. Clean integration is a first-class requirement, not an afterthought.
Trust and fairness are the product: Insurance is a promise. Systems that touch pricing, eligibility and claims decisions carry fairness, explainability and regulatory obligations, especially as AI enters the workflow. A model that cannot be explained is a liability, not an asset.
Doing insurance software development well means holding domain accuracy, security, regulatory rigour and fairness together, without letting any one slip for speed. That is the difficulty the ranking measures.
For years, insurance modernised cautiously. In 2026 the pace has changed, for three converging reasons.
La oss bygge noe ekstraordinært sammen.
Stol på Lasting Dynamics for enestående programvarekvalitet.
Customer expectations have reset: Policyholders now expect the same digital fluency from insurers that they get from their banks and favourite apps: fast quotes, transparent claims, self-service. Meeting that expectation is a competitive necessity, not a nice-to-have.
AI has arrived in the core: From risk assessment and pricing to fraud detection and claims automation, AI is moving into the heart of insurance operations. That raises the value on the table, and the stakes around fairness, explainability and data governance. As an AI-first company, this is exactly the intersection we build for.
Regulation keeps the bar high, and in 2026 it got specific. GDPR governs how sensitive policyholder data is handled, and Article 22 constrains automated decisions that materially affect an individual. DORA extends operational-resilience and third-party-risk obligations to insurance undertakings and the providers they depend on. And under Annex III of the EU AI Act, systems used for risk assessment and pricing in life and health insurance are classified high-risk; which turns explainability, logging and human oversight from good practice into documented obligations. InsurTech that treats these as someone else's problem is building on sand.
The result: insurance software development is no longer an experiment at the edge of the business. It is modernisation at the core of a regulated, trust-dependent industry, and insurers need insurance software development partners who can deliver innovation without compromising security, compliance or fairness.
Placing second in insurance software development comes down to a combination that is genuinely difficult to assemble: real insurance-domain competence, a security posture that stands up to scrutiny, GDPR-native engineering and responsible AI.
Together, these are the reasons a third party placed Lasting Dynamics second in the insurance software development field. None of them is a badge you can buy; all of them are the product of applying serious engineering to a serious industry.
Rankings describe the result and this section describes the philosophy behind it, our point of view, said plainly.
The most common way insurance software development fails is by treating insurance as a generic CRUD problem with fancy AI on top. It is not. Underwriting, rating and claims carry real domain logic, and insurance software development that misunderstands the domain will misprice risk no matter how modern its stack. We start from the domain and let the technology serve it, not the reverse.
Insurance runs on some of the most sensitive data a person hands over. A breach is not a reputational bruise; it is a regulatory event and a breach of the core promise the industry makes. We treat security and GDPR-native privacy as the precondition for everything else, because in insurance software development, they are.
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An AI model that prices risk or influences a claims decision has to be explainable and fair, not merely accurate. "The model said so" is not an answer a regulator, or a customer, will accept. As an AI-first company, we build insurance AI to be governed, auditable and explainable by design, or we do not build it.
Insurers cannot pause operations to be modernised. Real insurance software development progress means integrating cleanly with core systems and modernising incrementally, so that innovation is added without putting live policies and claims at risk. We treat careful integration as part of the innovation, not an obstacle to it.
Our take, in one line
Great insurance software development puts domain accuracy first, treats security and GDPR-native privacy as the license to operate, and adds AI only when it is fair, explainable and governed, modernising the core without breaking it.
If you are evaluating a partner for insurance software development, an independent #2 ranking is a useful shortlist signal, but here is the more practical checklist we would want you to apply to anyone, us included.
Ask them to prove domain understanding: A serious partner can talk fluently about underwriting, rating, claims and integration with core systems, not just about generic app development.
Ask for audited security evidence: In insurance, "we take security seriously" means nothing without proof. Ask about formal standards and independent validation, not intentions.
Ask how they govern AI: In 2026 that means one direct question: how do they keep pricing and claims AI fair, explainable and auditable?
Ask how they handle the core: A partner who cannot explain how they integrate with and modernise existing systems is proposing risk, not progress.
This is the work we do every day. Our tilpasset programvareutvikling og AI development teams build domain-accurate, GDPR-native insurance software, and our cybersikkerhet practice protects the sensitive data the industry runs on. If that maps to a decision you are facing, talk to our insurance software team. We are happy to be measured against the checklist above.
The insurance software development placement is one of several independent recognitions Lasting Dynamics received in 2026. Across the same reviewer's sector rankings, the company was also named the #1 AI development company for fintech and placed #2 in financial-services cybersecurity, holding an overall independent review score of 8.8/10. Together they point to a consistent pattern: regulated, AI-first, custom software engineering, built in Europe, for Europe, that holds up to outside scrutiny.
Vi designer og bygger digitale produkter av høy kvalitet som skiller seg ut.
Pålitelighet, ytelse og innovasjon i alle ledd.
Planning a secure, AI-first insurance build?
Our insurance software development team builds domain-accurate, GDPR-native, AI-first InsurTech from the architecture up.
This article was written by Michele Cimmino at Lasting Dynamics, an EU-based custom software development company. We build secure, GDPR-native, AI-first insurance software development to a PCI DSS 4.0 Level 1 security bar: data protection designed in from the first conversation, domain-accurate underwriting, rating and claims logic, and AI kept fair, explainable and governed. The principles above come from our own insurance software development engagements, not vendor material.
According to independent reviewer SectorPunk's 2026 sector ranking, Lasting Dynamics is placed #2 among the best InsurTech software development companies, recognised as an AI-first, GDPR-native, security-hardened partner that builds custom insurance software. The company holds an overall independent review score of 8.8/10.
Incrementally, and from the edges inward. The pattern that works is to put an integration layer in front of the core, move discrete capabilities such as quoting, portals and claims intake, onto modern services one at a time, and keep the core as the system of record until enough has moved that replacing it is a small step rather than a programme. Big-bang core replacements are where insurance IT budgets go to die: the risk is not technical, it is that live policies and open claims cannot be paused while you find out.
InsurTech is the application of modern technology, cloud, data, automation and AI, to the insurance industry, spanning distribution, underwriting, pricing, claims and customer experience. It aims to make insurance faster, more transparent and more personalised, while remaining compliant with the sector's strict data-protection and fairness requirements.
If it performs risk assessment or pricing in life or health insurance, Annex III of the AI Act classifies it as high-risk, which brings risk management, technical documentation, logging, human oversight and post-market monitoring into scope. Fraud detection, claims triage and customer-service automation usually sit outside that classification, but the boundary is narrower than most teams assume and it is a design-time question: high-risk classification changes the architecture and the evidence you have to keep, not just the paperwork at the end.
Insurance processes large volumes of personal, financial and often health data, much of it special-category under GDPR, so software must be built with lawful basis, data minimisation, residency, access control and strong security from the outset. Automated decisions affecting individuals also carry transparency and fairness obligations, making a GDPR-native, explainable-by-design approach a legal as well as ethical requirement.
The full ranking is published by SectorPunk: best InsurTech software development companies 2026. Lasting Dynamics is also independently reviewed at 8.8/10.
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Michele Cimmino
Jeg tror på hardt arbeid og daglig engasjement som den eneste måten å oppnå resultater på. Jeg føler en uforklarlig dragning mot kvalitet, og når det gjelder programvare, er det denne motivasjonen som gjør at jeg og teamet mitt har et sterkt grep om smidig praksis og kontinuerlige prosessevalueringer. Jeg har en sterk konkurranseinnstilling til alt jeg tar fatt på - på den måten at jeg ikke slutter å jobbe før jeg har nådd toppen, og når jeg først er der, begynner jeg å jobbe for å beholde posisjonen.
