Process orchestration (PO) and artificial intelligence (AI) can significantly enhance health insurance underwriting by streamlining processes, enhancing risk evaluation accuracy, and boosting overall efficiency. The key to achieving these improvements is by joining forces with process orchestration and artificial intelligence.
Let’s start by taking a look at how artificial intelligence enhances fairness in risk assessment for healthcare insurance underwriting.
Enhance risk assessment
With the introduction of AI into your organization’s processes and operations, you can analyze vast amounts of structured and unstructured data including medical records, genetics, and lifestyle habits, significantly enhancing the accuracy and scope of risk assessments. By identifying intricate patterns that may be missed by human analysis, AI provides more detailed and personalized evaluations of individual health risks.
AI enhances your underwriting models by focusing on individual health factors rather than relying on broad demographic categories. This approach minimizes the potential for biased assessments based on age, gender, or ethnicity, emphasizing the unique health profiles and behaviors of individuals instead.
If you take advantage of these capabilities of AI and integrate them into your underwriting process, you can make faster, more accurate decisions concerning risk. Models can be used to forecast potential health risks, likelihood of claims, and associated medical costs, which helps improve both the underwriting accuracy and the speed of making decisions. With natural language processing (NLP) automatically extracting relevant information from data, the information can be simplified and summarized in advance for underwriters streamlining the review process.
As shown in the example process below, prior to underwriter review, you can take advantage of AI to review and summarize various records as well as do an initial risk assessment. This streamlines the process and expedites the review by providing the underwriter with an overview of the applicant, extracting highlights and potential risks for the review process.

Additionally, machine learning continuously updates risk models with new data, allowing for ongoing improvement. This adaptability ensures that evaluations remain precise and aligned with evolving healthcare trends and risks.
Process orchestration and automation with AI
Now that we have addressed AI and risk assessment, let’s look at a few of the ways process orchestration and automation (PO&A) with AI can make a significant impact on your health insurance underwriting operations and provide fairer risk assessment.
Make decisions faster
Quick decisions can make or break the customer experience, but including AI in your process can help improve and even automate decisions for you.
There are several tasks that can be automated to help reduce the manual workload of underwriters. These can include policy renewals and eligibility checks, for example. By automating these repetitive tasks, you can speed up the underwriting process.
There are several different ways to automate these types of tasks, which can be further enhanced by adding AI in the mix. AI enables your process to pull real-time data from electronic health records (EHRs), wearable devices, and databases to make faster, more dynamic decisions.
Streamline workflow
Most underwriting process orchestrations have several decision points and steps, including data gathering, document processing, decision approval, and risk assessment. Integrating various systems, automating repetitive tasks and enhancing data gathering with AI can ensure faster and more efficient underwriting cycles.
With true process orchestration, you can provide cross-functional collaboration to coordinate tasks and communication between different departments sharing data across those teams. Automating processes improve both transparency and customer satisfaction by allowing staff to provide quicker, more informed feedback to customers and agents.
Improve accuracy and reduce bias
Consistency in processes and decisions is essential for fairness. AI models reduce human error and variability, leading to more uniform and impartial risk assessments across applicants.
AI minimizes biases that stem from subjective judgment or misinterpretation of data. When designed and trained on unbiased datasets, AI systems focus on objective, data-driven predictions, ensuring fair and equitable evaluations.
Achieve regulatory compliance and enhance fraud detection
Integrating AI with process orchestration will enable you to proactively track regulatory changes and compliance by simplifying the management and updates of underwriting guidelines and policies.
You can also use AI to help you identify unusual patterns and subsequently flag them as potential fraud, which helps to safeguard your organization against the risks associated with fraudulent activities. An example of this type of flagging can be seen below.

Transparency and Accountability
With a clearly defined process, you can use this information to justify any decisions that are made to insurers and regulators. This transparency helps build trust and ensures adherence to regulatory standards aimed at fairness. A true process orchestration solution with integrated AI can assist organizations to address regulations like the EU AI Act through this transparency and auditability of your process.
While AI can significantly improve fairness, it requires careful design and oversight to avoid perpetuating biases present in the training data. Ethical guidelines and rigorous testing are essential to ensure fairness in healthcare insurance underwriting.
How Camunda can help
Camunda has a platform that allows organizations to integrate AI throughout your process by providing connectors to run certain models, and options like Camunda Copilot that uses generative AI to help simplify complex process modeling tasks. With Camunda Robotic Process Automation (RPA), you can automate repetitive tasks to streamline your underwriting process. You can also access legacy systems, such as your policy administration system, using RPA.
In fact, you can use Camunda RPA in combination with your own RPA tools in your process today because of our composable architecture. In addition, this architectural approach allows users to integrate and utilize AI models and connectors where they add the most value leaving room to exchange them, if needed, in the future. This composability extends your solution to auditability and governance while remaining flexible for future requirements. This approach can significantly reduce your time to market (TTM).
With Camunda Intelligent Document Processing (IDP), you can simplify and automate how your documents are handled, minimizing manual errors and reducing operational costs typically associated with human-driven tasks. It enables you to extract actionable intelligence and insights from your documents, uncovering valuable information to enhance workflows, streamline processes, and support strategic decision-making.
You can also gain insights into your processes with Camunda Optimize. With Optimize, you can establish and monitor your key performance indicators (KPIs) and evaluate process consistency and bottlenecks.
Camunda provides an open and scalable platform to address your underwriting process.
What’s next?
Together, AI and process orchestration enable health insurers to optimize their underwriting processes, improving speed, accuracy, and efficiency while enhancing customer experience and profitability.
But, you don’t have to stop with the underwriting process. There is so much more you can achieve if you integrate AI and process orchestration into your organization. You can include process and AI into policy renewals, the appeals process, claims processing, policy changes like live events, and more.
Start the discussion at forum.camunda.io