Blog: The complexities of IPT determination

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The insurance industry is navigating a period of economic instability and is still unsure what long-term effects the pandemic will have on direct and indirect taxes. Despite this lack of current clarity, it is sensible to plan for all eventualities, suggests James Buckley, Sovos managing director – Europe.

More so than ever, insurers are exploring ways to streamline processes, improve efficiency, strengthen the bottom line and prevent costly errors that could affect their reputation with tax authorities, regulators and customers.

While Insurance Premium Tax might not be top of the agenda for insurers, in comparison to Value Added Tax or other tax requirements, the fact that filing is becoming increasingly complex means current processes warrant attention.

Navigating tax remediation across the globe

The complexity of IPT determination is in part due to the different rates and filing processes. Unfortunately, there is very little consistency between authorities, meaning that staying informed of the latest rate changes and filing requirements is an essential but time-consuming task.

Many tax authorities are looking to close tax gaps and improve visibility into insurers’ liabilities. Within Europe we’ve seen the introduction of real-time VAT reporting in Spain, Italy and Hungary.

IPT is following in VAT’s footsteps - for example, Spain’s Consorcio de Compensación de Seguros strict requirements and Portugal’s upcoming stamp duty reporting changes are both leading the charge for a digitised approach to reporting. Other countries including Morocco, Jordan, Poland, Greece and France are also looking to introduce e-invoicing and no doubt, others will follow.

The detail required by authorities for tax remediation is, as a result, becoming increasingly granular. For insurers, this means shoring up data management, validation and processing.

As always, reporting accuracy and compliance is key to avoid unwelcome (and unnecessary) penalties, interest and audits.

And then there is the elephant in the room for UK-based insurers. Brexit hasn’t gone away despite the pandemic and is set to bring further complications for any cross-border insurer conducting business in the UK.

It remains to be seen if the UK can strike a deal with the EU and stay in the internal market. Negotiations are still ongoing. However, it’s looking most likely that the UK will exit the EU with a “no deal”.

For UK insurers this will create tax and regulatory challenges if writing business in the EU. Some UK based insurers have taken prudent steps already and set up new entities in the EU in order to continue to carry out their insurance business effectively.

Information overload

Other complexities can arise with the launch of new customer-focused insurance products.

Take the popularity of pay-per-mile and other short-term insurance policies as an example. The potential risk for error and incorrect filing could likely increase. With filing done in bulk and taxes for different policies being due early on inception or on maturity of policy, filing systems must be accurate and updated to avoid missed payments.

This is why digitisation should be seen as a positive for the industry, even if it can feel like additional work. Machine learning and artificial intelligence technologies are assisting insurers with the increased data processing and filing while insurtech solutions can  provide and apply the latest rates to accurately calculate IPT and relevant parafiscal taxes.

As the move towards a more digital insurance landscape continues, capturing the correct policy information will become crucial for insurers to avoid late reporting, penalties and interests.

The complexities of IPT can be navigated with the right tools and strategy. In this time of uncertainty, both economically and from a reporting perspective, insurers should not be disheartened but instead see this is as a golden opportunity to think about what improvements can be applied now to make future IPT and VAT reporting more manageable, effective and accurate. 

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