Ai Revolutionizes German Health Insurance: Challenges, Opportunities, And The Ai Act

German Health Insurers Are Facing Mounting Pressure Despite Stable business Growth And Advanced Automation. A Key challenge Is The Surging Volume Of Interactions, Wich Has Spiked By 50% To 100% For Many Insurers In The Last Three Years. this Surge Coincides With A Reduction In Staff Capacity Due To Aging And Illness,Leading To Backlogs In Customer Service And Performance Management. How Can ai in health insurance help to cope with these challenges?

Concurrently, Customers Expect Service Levels Comparable to Those From Other Industries. This Confluence Of Factors Has Elevated The Importance Of Artificial Intelligence (Ai). the eu Ai Act Sets A Regulatory framework Emphasizing Openness, Security, And Ethical Duty. Though, German Health Insurers Remain Cautious About Ai Implementation.

Unlocking Ai’s Potential In German Health Insurance

The most Obvious Ai Application Lies in Its Ability To Process Structured Data. Unstructured Data, Such As Free-Text Emails, Letters, Reports, Or Proofs, Poses A Notable Automation Challenge. Ai Can Extract Relevant Information, Especially From Language And Image Files. This Extraction Reduces Manual Effort And Facilitates More Precise Routing For Further Processing.

An Ai Assistant Can Support Human Processing In Complex Cases Requiring Human Interaction. the “human-In-The-Loop” Principle Is Already Familiar To Health Insurers. Ai Can Summarize Texts, Provide Expert Knowledge From Internal databases, And Prioritize Inquiries.

Ai-Assisted Processing: Enhancing Efficiency

Ai-Assisted Processing Shifts Employees’ Focus From Transactional Activities To Analytical Tasks. A Common Use case Involves Accessing Information From Tariffs And Regulatory Guidelines. Instead Of Reviewing Original Documents, Specific Questions Can Be Asked, With Relevant Original Positions Referenced As Needed.

Another Use Case Includes Generating Individual Correspondence.Here, Ai Formulates Texts Based On Available Data or inputs From The Clerk. Developing New Employee Skills Is essential For Effectively And Responsibly Using this New Assisted Processing.

Automating Complex Processes With Ai

Ideally, Ai Can Automate Complex Processes And Provide Expert Decision-Making Support. Rule-Based Automation is Already Used For Simple Tasks Such As Taa Decisions Or Performance Statements.

However, Rule-Based Automation Has Limitations For Complex Processes With High Variance And A Small Number Of Cases. for complex Processes, Ai With Higher Professionalism Is Needed. This Ai Should Not Only Process Data But Also understand And Interpret Technical Relationships.

This Is Particularly relevant When Assessing Information Available In Unstructured Formats,Such As Doctor’s Letters,Reports,Or Free-Text Information In Performance Applications. For Example, Ai Can Recognize Diagnoses And Therapy Recommendations From Doctor’s Letters When Examining Rehabilitation Measures.

It Can Also Check Medical necessity according To Insurance Conditions And Current Medical Guidelines.Complex Cases Can Be Progressively Automated By Combining This With An Examination Of Whether A Comparable Measure Was Granted Recently Or Whether There Are Regional Peculiarities In Service Provision.

Ai Advantages: Benefits For Insurers And Insured

Ai Can Enhance Customer Satisfaction, Improve Process Efficiency, And Increase Processing Quality. With More Automated Processing And Fewer Residual Tasks, Customers Receive Quicker Feedback. Conversational Ai Can Also Provide 24/7 Support.

faster And More Accessible Services Can Boost Customer Satisfaction. Process Automation Reduces Process Costs.This Lays The Foundation For Permanent Operational Capability In Application, Contract, And Service Processes, Especially Given The Aging Workforce.

Ai-Based Processing Can Improve Quality in Underwriting, Claims Processing, And Fraud Detection. For Example, It Provides More Time For Content Decisions Thru The Preparation Of Complex Facts; This Supports Risk Assessment And Performance Control. It Also Identifies Manipulated Evidence And Prevents Unjustified Services, Positively Impacting The Insurance Result.

Navigating The Eu Ai Act: Risks And Opportunities

The Use Of ai By Health Insurers Is Generally Permitted, With A Focus On The Risk Classification Of Ai Applications. The Key Is Identifying High-Risk And Forbidden Applications. High-Risk Applications Can Still Be Used Under Stricter Requirements.

Applications With Low Professionalism, Like Ai For Data Extraction, Are Expected To Be Uncritical Under The Ai Act. however, Applications Where Ai makes Professional Decisions Or Strongly Influences Decisions Are Heavily Influenced. Such Applications Will likely Be Classified As High-Risk, Posing A Major Implementation Challenge For Health Insurers.

Many Health Insurers Already Have Processes For These High-Risk Applications, But They Must Adapt To The Specific Requirements Of The Ai Act. the Examination Requested In The Ai Act By An Employee, For Example, With A Reduction In Performance, Is Already Common practise.

Synergies In Implementing Existing Regulations, Such As Vait And Dora, Can Be Leveraged. Transparency And Documentation Obligations Can Be adjusted To Ensure Simultaneous Compliance With The Ai Act.

Building competencies For Ai Compliance

Ultimately, Health Insurers Must Develop Competencies In Dealing With The Ai Act. Gaining Experience With The Technology And The Ai Act Is Crucial By Starting implementation Now.

Agentic Ai: The next Level Of Ai Solutions

While The Ai Act Defines The Legal Framework For Ai Use And Challenges Health Insurers To Conform High-Risk applications, The Advancement of Ai Technologies Like Agentic Ai Offers New Opportunities.

This Next Stage Of Ai Promises Greater Autonomy And Efficiency. It Could Also Help Meet The Ai Act’s Requirements Through Innovative Approaches.

Ai Agents Are Autonomous Software Components That Plan, Make Decisions, And Act Independently Based On Field Information. They Use Specially Developed Or Pre-Existing Tools Within Defined Limits. The Concept Of Agentic Ai Is Rapidly Evolving, Replacing Classic Ai As Well As Rule-Based Routing And Automation In Certain Areas.

Unlike Traditional Ai, Agent-Based Ai Systems Act Autonomously, Solve Complex Problems, Seek Human Feedback When Necessary, Learn From Internal And External Knowledge sources, And Continuously Optimize Their processes.

Orchestration: Combining Ai Agents For Enhanced Automation

Various Ai Agents Can Be Combined Using An Orchestration Solution To Achieve A Higher Degree Of Automation And Solve More Complex Tasks. For example, One Ai Agent Can Read A Customer’s Letter, While Another Transfers The Extracted Information Directly Into The Corresponding System.

Strategic Focus And Resources For Responsible Ai Use

the Ai Act Presents An Additional Challenge In Using Ai In Health Insurance. however, This Should Not Be An Obstacle, given Ai’s Potential For Greater Customer Satisfaction, efficiency, And Processing Quality. Health Insurers Should Promptly Gain Experience And Leverage Synergies With Existing Regulations.

It Is Crucial To Learn Actively In Which Context And Scope Ai Can Be Sensibly Used, And To Train Employees Accordingly. Insurers Must Plan Sufficient Capacities And Skills, And Define The Right Processes To Implement Ai’s Potential Responsibly.

Effective And Responsible Ai Use Requires The Right Person Who Understands Work Processes And Has Enough Time To Perform Their Tasks Conscientiously. The agentic Ai Approach Is Especially Exciting Because It Expands Ai Application Areas And Is Crucial For Responsible Use.

The Specific Tasks Of Individual Agents Reduce Overall Complexity, Allowing Insurers To Analyze Solutions And Identified Problems Faster And More Specifically. At The Same Time, Recognizing Potential Negative Effects On Peopel Early And Mitigating Them Effectively Remains Essential.

This Ensures The Responsible Use Of Ai, Which Considers Both Opportunities And Risks.

How Do You See Ai Transforming The Health Insurance Industry? What Ethical Considerations Should Be Prioritized?

Share Your Thoughts And Questions In the Comments Below!