Not historical claims. Not declared information. Not product activity. Real life happens in places traditional insurance systems were never designed to see – in financial behavior, mobility, and everyday situations where risk and need form long before a claim or policy change ever appears.

Internal data explains the contract. External signals explain the human behind it. And that is where the industry’s competitive edge is moving.

Insurance doesn’t have a data shortage - it has a visibility problem. The most relevant signals exist outside the insurance stack.

— Jakub Hytka, Director, Consulting & Insurance, Trask

From collecting data to accessing reality

Insurance companies are still in the midst of modernization – building data platforms, renewing cores, and rethinking how information flows across the enterprise. These initiatives are essential, but they are not yet complete.

Traditional insurers with legacy systems face a clear disadvantage compared to younger, digital-native players whose architectures were designed for agility from the start. While the newcomers can focus directly on insight and customer value, incumbents are still working to enable the very foundations – integration, data platforms, and process optimization.  

But even the most advanced internal systems still see a limited slice of reality. They see what customers told them, what happened in the past, what exists in internal tables.

They do not see:

• when financial stability shifts before a missed payment,

• when someone’s life rhythm changes after a milestone,

• how a person actually behaves behind the wheel,

• or the early signals of risk and opportunity emerging in the flow of daily life.

And the truth is: those signals don’t originate in insurance. They originate across industries.

The future of underwriting, pricing, and customer relevance will depend less on how much data insurers own, and more on how responsibly they can access and interpret real-world signals beyond their boundary.

New data sources are changing the game

This responsibility is now being shaped not only by ethics, but by regulation – through frameworks like FIDA and the EU AI Act, which define how data and AI can be used to support fairness, transparency, and explainability.

Data is becoming the critical input for advanced models, including AI-driven ones, and its misuse can quickly translate into bias, customer disadvantage, or loss of trust. In volatile times when customers need clarity and confidence most, the ability to use data responsibly – not just effectively – will define the insurers people choose to trust.

This is already happening. In collaboration with Mastercard, insurers can now work with derived financial behavior attributes - safely, transparently and without touching raw transactions - to understand life patterns, economic rhythm and signals of change that traditional data cannot surface.

And through Škoda vehicle connectivity, insurers gain insight into real driving behavior and vehicle usage, processed and contextualized into insurance-ready signals - allowing fairer, more nuanced motor risk decisions grounded in how people actually drive, not who they are on paper.

These are not enrichment exercises. They are new lenses on risk and relevance, born from other industries.

Cross-industry signals don’t replace actuarial logic – they anchor it in real behavior.
— Valeriya Turussova, Principal Business Consultant

Regulation is not the obstacle — it’s the enabler

Europe is not moving toward free-for-all data sharing. It is moving toward consent-driven, transparent, explainable data mobility, where customers choose who uses which signal on their behalf.

The winners won’t be those who hoard data – but those who earn the right to use it, who protect it, and who can explain decisions clearly to customers and regulators alike.

This is why cross-industry intelligence is not just a data topic. It is:

• a trust framework,

• a governance model,

• an interpretation layer,

• and an ability to operationalize insight responsibly.

And it is becoming a strategic capability.

What changes when insurers can actually see?

Pricing becomes fairer because it reflects reality, not averages. Prevention becomes proactive instead of reactive. Customer interaction becomes timely and relevant, not periodic and generic. Trust increases, because decisions feel earned – not opaque.

Internal data built the first phase of digital insurance. Cross-industry intelligence will define the next one.

To see customers as they truly are – not as static profiles frozen in forms, but as people whose needs and risks evolve in motion. Insurance has always been about understanding the world. Now, it must learn to see the world it protects – and that world no longer fits inside a single industry.  

Insurance has never worked in isolation. Now its intelligence can’t either. That’s why new sources of insight are emerging – not just from payments or mobility, but from digital behavior itself. In cooperation with CredoLab, Trask enables insurers to tap into non-personal signals from web and mobile interactions – such as app usage patterns or device behavior – and translate them into actionable insights like risk scores, lifestyle segments and fraud alerts. This adds a deeper layer of context to underwriting and prevention, making pricing fairer and engagement more relevant, all while remaining transparent and compliant.

Mini Case Studies: Where Cross-Industry Intelligence Is Already Delivering Value

Case: Mastercard × Trask – Turning payment behavior into understanding

Context

Insurance rarely sees a customer’s real financial rhythm – yet life stability, routine shifts and economic signals form outside policy systems.

What we enabled

Trask and Mastercard provide insurers with GDPR-safe, derived behavioral attributes and segmentation, delivered through a secure and explainable model – without touching raw transactions.

What it changes

Instead of guessing intent or waiting for lagging events, insurers can understand when and how life is shifting, and respond with relevance, not noise.

Why it matters
Fairness and accuracy grow when decisions reflect how a person actually lives, not only how they once answered a form.

Case: Škoda × Trask – Seeing real driving, not assumed profiles

Context

Motor pricing often relies on demographics and declarations – proxies for behavior that don’t reflect real-world risk.

What we enabled

Using connectivity data from Škoda and Trask’s processing layer, insurers can work with actual driving patterns, vehicle usage and contextual signals to inform PHYD/UBI models responsibly and transparently.

What it changes

Risk becomes observed, not assumed – shifting motor products toward fairness and proactive safety.

Why it matters

Insurance moves closer to the road, and customers feel seen not just as profiles, but as drivers.

Case: Combining worlds – mobility + financial context

Context

No single signal defines a customer; meaning emerges when industries meet.

What we enabled

Trask orchestrates compliant signal translation between payments and mobility environments – combining behavior and context in a structured, explainable way.

What it changes

Insurers gain a more complete, real-world view of customers – one tied to how they live and how they move, not only how they look in internal systems.

Why it matters

The next generation of insurance will not be built inside one industry. It will be built between them.

[.infobox][.infobox-heading]What to take away[.infobox-heading]The strongest insurance insight no longer lives in insurance systems. Real-world signals now emerge in banking, mobility, and daily behaviour – and carriers that can responsibly access and use them will lead. Internal data shows history. Cross-industry signals reveal reality.

This shift isn’t about having more information – it’s about seeing what truly shapes risk and need:
- financial rhythm → stability, change, life triggers
- driving patterns → real behaviour, not assumptions
- consent-based data sharing → trust, fairness, explainability

Europe isn’t enabling data hoarding – it’s enabling customer-controlled, transparent data mobility. The future of insurance intelligence sits between industries. Those who can connect worlds will set the standard for fairness, relevance, and performance. [.infobox]

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