
EASE OF USE & PRACTICAL EXAMPLES
Practical application
QUESTIONS & ANSWERS
1. Fundamentals of Artificial Intelligence
Artificial intelligence is software that performs tasks that previously required human thinking – e.g., understanding texts, analyzing data, or suggesting decisions.
Insurers benefit from this because AI can quickly recognize and evaluate large amounts of information and derive meaningful courses of action from it.AI is the umbrella term for intelligent systems.
Machine Learning (ML) refers to models that learn from data.
Large Language Models (LLMs) are AI systems that understand, structure, and interpret language.
LLMs are particularly valuable to insurers because they can professionally understand texts such as claims reports, expert opinions or emails.Because AI is now ready for practical use :
She works quickly and precisely.
She can take on complex specialist tasks.
It drastically reduces costs and processing times.
This opens up enormous potential for savings, particularly in the insurance industry.Classic software follows rigid rules.
AI interprets content, draws conclusions, and adapts to new data.
For insurers, this means:
An AI automatically detects coverage gaps, damages, risks, or necessary documents – without manually predefined rules.


QUESTIONS & ANSWERS
2. Benefits & Potential for Insurers
Up to 40% lower processing costs
Up to 70% shorter lead times
Fewer errors
Improved customer satisfaction
Higher productivity
Claims management (photo, video, text)
Underwriting and risk assessment
Contract amendments (inclusions, exclusions, cancellations)
Customer service / Email/document interpretation
Fraud detection
Building and inventory analysis
Analyze documents
Conduct coverage checks
Estimate damage costs
Suggest action steps
Extract data
Prioritizing processes
Rapid analysis of customer data
Preparation of risk reports
Automated responses
Support with consulting and sales
Efficient document processing
QUESTIONS & ANSWERS
3. Practical Use Cases in the Insurance Industry
AI can:
Analyze damage patterns
Identifying fraud patterns
Check coverage
Provide reserve suggestions
Payout recommendations
Request documents automatically
Risk assessment based on all available data
Building valuations (including 3D scan)
Scoring and risk recommendations
Comparison with reference conditions
The AI reads the request, e.g.:
"Please remove person X from the contract."
→ It recognizes the process, contract type, necessary steps, and data fields.
→ The clerk only needs to confirm.Pre-sorting of emails
Suggested answers
Recognition of the business transaction
Assignment to teams
Document completeness check



QUESTIONS & ANSWERS
4. Start and introduction in the company
Select a small, clear use case
Define data paths
Launch first pilot environment
Measuring results
Scaling
With 9elf26.ai, a pilot project often only takes 4–6 weeks.
Transparency regarding goals
Simple training courses
Clearly define roles
Involving employees in pilot phases
Take concerns seriously (“AI doesn’t replace – it relieves”)
Projects that are too large
Lack of clear goals
No process owner
No testing strategy
Unclear data quality
No – but you need:
Process knowledge
Expert decision-makers
IT contact person
The platform handles the complex AI functions (e.g., 9elf26.ai).

AI for your insurance processes
Central AI platform for property, life, and health insurers
QUESTIONS & ANSWERS
5. Integration into systems & processes
Via APIs or batch processes.
9elf26.ai is compatible with systems such as:Inventory management systems (e.g. V'ger, Guidewire, msg, adesso)
Third-party systems (CRM, claims portals)
Document management systems
For example:
Documents
Emails
Images/Videos
Master data
Conditions
The AI does not require any special formats – PDFs, JPGs, DOCX or structured data are sufficient.
Technical tests
End-to-end tests
Versioning (e.g., every prompt and every model is historized)
Monitoring of results
Quality metrics
The AI recognizes the process → classifies it → suggests measures → automatically executes work steps.
The human confirms or corrects.
Human + AI result in maximum process quality.


QUESTIONS & ANSWERS
6. Security, Regulation & Governance
Yes.
However, insurers must take note:EU AI Act
GDPR
BaFin requirements for traceability
9elf26.ai meets all relevant requirements.
Processing in Europe
No data storage without consent
Pseudonymization
Audit trails
Encryption
Yes.
The platform shows:Which input data was used
Which rules were applied?
What results were produced?
This is essential for regulation and quality.
AI Manager
Quality management
AI usage policy
Monitoring & feedback loops
QUESTIONS & ANSWERS
7. Economic efficiency & strategic importance
Many projects achieve positive effects after just 3–6 months:
Less processing time
Lower administrative costs
Better completion rates
Fewer follow-up questions
Clerks are relieved of routine tasks.
Work is becoming more technical, less administrative.
AI provides decision suggestions, not final decisions.
Faster processes
Higher customer satisfaction
Lower cost base
Access to more automation
Competitive advantages
Yes, in the long term:
Pay-per-use
Prevention instead of reaction
Automated risk scoring models
Faster product development


QUESTIONS & ANSWERS
8. Specifically regarding 9elf26.ai
A fully operational AI platform for insurers, brokers and service providers.
It combines state-of-the-art AI with over 30 years of experience in insurance IT.Claims management
Coverage analysis
Contract processes
Risk assessment
3D building analysis
Inventory lists
Customer communication
Via standardized APIs
Batch process
No changes to core systems are necessary
Rapid piloting
Kick-off and selection of the use case
Data connection
First results in a few days
Technical fine-tuning
Rollout into the organization
Focus on insurance processes
Ready-to-use AI modules
High level of expertise
Direct integration
Transparent Governance
Low costs, fast results
German/European Compliance








