Directe toegang tot contractinformatie en polisvoorwaarden aan de apothekersbalie door onze virtuele assistent
Nederlandse Farmaceutische Zorggroep (NFZ)
Data & AI for insurers
An insurer works with large volumes of text and numbers at the same time.
Policy terms, contracts, claims, customer interactions and financial data are spread across different systems and documents. Staff therefore spend a long time looking for the right answer, while patterns in claims or cancellations only become visible later. Data and AI make this information easier to find and use.
Challenges,
Customers expect a clear answer quickly, while policy terms and regulations are becoming more complex. At the same time, regulators set requirements for explainability, privacy and fair treatment of customers. This calls for applications that genuinely help staff and whose workings can be accounted for.
How we support you,
We build assistants that help staff identify the relevant policy terms more quickly, and models that use claims and customer data to flag anomalies and cancellation risks earlier. For NFZ, we developed a virtual assistant that gives staff at the pharmacy counter direct access to contract information and policy terms. These are just a few examples of what is possible. The right solution always depends on the challenge and the organisation.
DSL in numbers,
40
Data experts
10+
Years of experience
200+
Projects completed
8,7
Client satisfaction
Get in touch with our experts,
Want to know what we can do for your organisation?
Younes Seghrouchni
Managing Consultant GenAI & Data StrategyE-mail info@datasciencelab.nl
Carmen Wolvius
Managing Consultant Data Science & AIE-mail info@datasciencelab.nl
Stef Stoelwinder
Business DevelopmentE-mail info@datasciencelab.nl
Where we do that,
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The organisations that do this,
Frequently asked questions,
AI can search policy terms, contracts and past cases, and combine them with claims and customer data. This helps staff find the right answer faster and allows the organisation to spot unusual claims or customers who may leave sooner.
Start with a task that currently takes staff a lot of time searching, such as answering questions about coverage and policy terms. You can quickly see what an assistant delivers, and apply what you learn to the next step.
Policy terms and contracts, claims history, customer interactions, premium and payment data, and sometimes external sources. The work lies in making the documents accessible and connecting the data, so a model or assistant works from a single reliable source.
By showing which policy term or document each answer comes from, documenting and monitoring models, and defining in advance where a member of staff must always make the decision. That makes it possible to account for how an outcome was reached.
By displaying the assistant or alert in the system staff already use, and agreeing who will keep it up to date when policy terms, products or regulations change. An assistant using outdated policy terms does more harm than good.