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Process Management: Automation disciplines to become integrative
AI - fused with BPA and RPA - is opening a new chapter in insurer automation technology. Robotic Process Automation (RPA) is just one promising starting point for insurance processes such as claims handling. Various automation, analysis and interpretation disciplines can be integrated across RPA. Alongside Business Process Automation (BPA), integrative solutions fused with Artificial Intelligence (AI) significantly improve efficiency and competitiveness.
Business Process Automation: More Complex Transactions with Diverse Systems
Automation platforms and bots reliably take over processes such as data entry during peak loads in an automotive division's year-end business – 24/7 if required. Insurance companies uniquely use software robots for data migration. Risk carriers use platforms and bots repeatedly over the long term for automated testing.
But is that all?
The initial situation for process added values is complex. For example, if a bot has to make front-end inputs at dynamic interfaces, in the worst case it cannot find the required input fields to populate an Excel table. This is often the case when IDs or classes have changed. Then the input process quickly becomes tedious and the responsible software developers have to "smooth out" the bot again and again so that it remains functional.
After all, certain technical situations in business process automation require a sustained positive cost-benefit ratio and thus smarter approaches. This is when Business Process Automation comes into its own. BPA is not only intended for more complex solutions; the discipline also automates multiphase transactions on several participating business systems.
However, RPA also has its limitations: Someone has to program the bot using no-code or low-code applications such as UiPath, Pega, BluePrism, iRPA from SAP (SAP Build PA) or Automation Anywhere. Depending on the tool selection and automation project, users should have a certain level of programming knowledge. In particular, they should have a thorough understanding of the technical processes in the insurance business - such as claims recognition, assessment and settlement. A basic understanding alone is not enough.
Martin Schmalfuß is Principal Developer for Robotic Process Automation at IKOR, a technology consultancy focused on the insurance industry. Laura Spieß works as a Senior Consultant for Process Optimization at the company's sister ADWEKO, a technology consultancy in the banking and finance sector. Both companies operate under the umbrella of the X1F Group.
There's more to consider: When a Python script or interface replaces the bot
At what point does the complexity increase to such an extent that it makes sense to build an interface instead of a bot? In other words, what does "the perfect solution" mean in the sense of insurance companies and entire organizations? When does a bot actually provide the best solution for individual tasks and activities (see article "Robotic Process Automation: Where RPA makes sense - and where it doesn't" in issue 17 of the Themendossiers)? When - depending on the use case - is a Python script faster and more effective than a bot?
BPA addresses demanding challenges. The discipline helps to interlink complex workflows that run through different systems and departments and to optimize these process chains. Python scripts or specific interfaces can replace bots in this process, opening up a broader range of automation options. Here, BPA stands for a comprehensive solution so that companies can make their operational processes more efficient and end-to-end integrated. This in turn supports and enables long-term business goals.
How BPA and RPA create synergies
Thanks to the combination of robotic and business process automation, insurers are not only expanding their range of opportunities and development possibilities. They are also reducing the error-proneness of their processes. Complex business and insurance processes can be integrated seamlessly. RPA is thus used as part of BPA solutions, while BPA monitors and controls the entire process flow.
However, comprehensive automation can only be achieved through an integrative approach. This has a beneficial effect on overall performance and competitiveness. The strategic implementation of RPA and BPA not only reduces costs, it also enables insurance companies to improve the quality of their services. After all, process optimization relieves employees of repetitive tasks and thus creates space for more creative and strategic tasks.
Example processes | How BPA and RPA can be used in the insurance business
Business Process Automation (BPA)
- Automated data collection of claims information from online forms
- Support for document review and processing
- Integration of data into the internal insurance system
- Support for employee decisions by providing relevant information
- Process lifecycle includes requirements gathering, approval, execution, monitoring, and reporting
- Standardization and automation reduce compliance risks: Consistent execution and adherence to internal policies or external regulations
Robotic Process Automation (RPA)
- Perform data matching and processing tasks
- Automated communication with the policyholder for notification of decisions and claim closures
- Increased efficiency: RPA reduces the error rate, shortens processing time and relieves employees of routine tasks
- Scalability during seasonal peak loads (e.g., car insurance): Bots can be scaled when workload is high (additional robots, no additional infrastructure or training required)
Cognitive RPA: Artificial intelligence takes RPA to the next level
Because RPA accesses unstructured data pots and the robotic discipline thus reaches its limits, an integrative approach also helps here: Artificial intelligence (AI), which deals with unstructured data, offers new possibilities in conjunction with RPA: By using AI methods such as Natural Language Processing (NLP, natural language understanding) and Optical Character Recognition (OCR, text recognition), RPA not only analyzes texts. It also extracts information captures and process data automatically and more efficiently.
This also applies to unstructured data from various sources - such as documents, emails or websites. A cognitive RPA created with the help of artificial intelligence interprets content from text documents in an automated yet human-like manner. Cognitive RPA is also capable of analyzing natural language to make intelligent decisions based on it.
The bottom line is more demanding automation tasks that previously required human intervention will now be handled by intelligent systems. Instead of aborting processes in the traditional way, "smart" and AI "pimped" bots also react to changing framework conditions. As a result, fewer manual interventions are required. Efficiency increases, employees are relieved and can concentrate on more demanding, strategic tasks.
With the combination of BPA and RPA, insurance companies become more agile and innovative in their processes; they adapt more flexibly to constantly changing market and customer requirements. The strengths of BPA lie in the precise and efficient handling of end-to-end integrated and thus complex process chains. In this way, smooth interactions between different automation solutions succeed, which can raise the potentials even further. In particular, new scaling possibilities arise for dynamic business processes enabling optimizations in such a way that competitiveness increases.
The article appeared in „Versicherungsforen Themendossier 21/2023“ in November 2023 (PDF in German).