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R&D Project "Laven"

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square with tentacles  Project title

R&D Project "Laven"

outline of the upper man silhouette  Name of Beneficiary/Beneficiaries

Laven S.A.

briefcase icon  Name of programme

Smart Growth Operational Programme

newspaper icon  Competition

BRIdge Alfa

two heaps of coins icon  Project value

PLN 578,981.35

hand icon with two circles above it  Funding value

PLN 463,185.08

clock icon  Project delivery period

from 17 August 2021 to 16 March 2023

What problem does our project solve?

The primary success of the project lies in the commercialisation of its outcomes, as well as the successful development and ongoing updating of the actuarial model. While the concept of complementary insurance is not new and this type of insurance is recognized in the insurance market, no insurance company operating on the Polish market has so far succeeded in introducing a similar product for sale. This fact confirms that the actuarial model owned by Laven is unique and unparalleled on the Polish market.

The project activities focused on four main tasks:

1. Differentiation of the premium collection and claims payout timeline in the actuarial model.

2. A component to differentiate the premium calculation depending on whether it is a product sold on its own (Laven model) or as an add-on to products offered by other insurance companies.

3. Expansion of the model to include the option for individual/family insurance and the ability to continue individual insurance coverage for ongoing customer therapy under the policy when a group insurance agreement is terminated by the policyholder (employer).

4. Implementation of new medical technologies into the actuarial model.

All planned tasks were successfully completed, thus:

1. a tool was developed to calculate premiums based on the anticipated duration of the insurance policy,

2. a tool was created to calculate premiums and their components depending on the sales channel of a given policy,

3. the capability to calculate individual and/or family premiums was introduced,

4. technologies deemed attractive from an insurance perspective were identified, evaluated, and implemented into the actuarial model, including risk assessment, premium calculation, and integration into the sold policies. Consequently, the success metrics established for the project were achieved, specifically the expansion of the actuarial model to support at least 280 medical technologies. Additionally, technologies already included in the policies were reviewed, and those covered under the National Health Fund's guaranteed benefits package were removed.

Throughout the project, progress, emerging risks, and obstacles were analysed on an ongoing basis. Based on this, decisions were made regarding the potential reallocation of funds provided under the project between tasks to utilise them as efficiently as possible and allocate resources to areas that were continuously identified as more critical from the perspective of the project and the company’s current needs.

Furthermore, in addition to tasks related to product development, Laven S.A. and its management were recognised and appreciated by industry media, receiving awards such as "Company of the Month," "Product of the Month," and a nomination for "Manager of the Year" for Piotr Karda, the President of the Management Board of the Company.

Who will benefit from the project's results?

The tool is currently utilised by the company in relationships with insurance companies and brokers to provide precise premium calculations tailored to the needs and expectations of all stakeholders—insurers, brokers, and customers. Implementing solutions for distributing products via the bancassurance channel (as an add-on to banking products) required not only developing and agreeing on premium calculation algorithms but also consulting with and obtaining approval from the reinsurer to establish maximum compensation levels for all sales process participants.

What was the biggest challenge for us in implementing the project?

The biggest challenge was accessing reliable claims data.

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