Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: DIALOG Improving Customer Experience in Health Insurance
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > CRM > DIALOG Improving Customer Experience in Health Insurance
Business IntelligenceCRMData MiningPredictive Analytics

DIALOG Improving Customer Experience in Health Insurance

JamesTaylor
JamesTaylor
6 Min Read
SHARE

(Guest post by James Taylor of Decision Management Solutions)

Gerhard Hausmann presented on Barmenia and their use of business rules to improve customer experience. Barmenia is a private health / life insurance company in Germany with more than 2M contracts and 1.5Bn Euros in premiums. Been in business since 1904 and still have contracts that date back to the last century. In Germany there is a mix of public and private health insurance – 70M people have public insurance and 8.5M are privately insured with another 20M having some additional private health insurance. Barmenia, like many companies, is facing challenges from an ageing population. For health insurance this is a particular challenge as older people are more expensive.

Barmenia is graded by a German quality organization and consistently gets A+ (6th time in a row) in part thanks to the system supporting 48 hour claims processing that is accurate and competent. Barmenia has been adding decision support in claims processing starting 2003 with a database of reimbursement information and moving to using ILOG rules in 2007 for auditing complex dental invoices, naturopath invoices and case assignment. They took a decision-sup…


Gerhard Hausmann presented on Barmenia and their use of business rules to improve customer experience. Barmenia is a private health / life insurance company in Germany with more than 2M contracts and 1.5Bn Euros in premiums. Been in business since 1904 and still have contracts that date back to the last century. In Germany there is a mix of public and private health insurance – 70M people have public insurance and 8.5M are privately insured with another 20M having some additional private health insurance. Barmenia, like many companies, is facing challenges from an ageing population. For health insurance this is a particular challenge as older people are more expensive.

More Read

Hospitality Technology (Or Lack Thereof) – What is the Insight ROI?
RulesFest 2011 – Kenny Shi: Scalability in a Real-Time Decision Platform
The Billboard Problem: Why Intelligent Ads Only Live Online, for Now
Winning the first game in a baseball series: a harbinger, or not?
Dear IT: A Letter from Your Business Users

Barmenia is graded by a German quality organization and consistently gets A+ (6th time in a row) in part thanks to the system supporting 48 hour claims processing that is accurate and competent. Barmenia has been adding decision support in claims processing starting 2003 with a database of reimbursement information and moving to using ILOG rules in 2007 for auditing complex dental invoices, naturopath invoices and case assignment. They took a decision-support approach because they feel they have good experts. They decided on a custom rules approach to get short logic release cycles and to avoid the need for the large integration projects that come with out of the box implementations.

They use a few thousand rules in some decision tables, a few hundred regular rules to and many patterns to manage the rules for dental invoices – pricing, eligibility, allocation etc. They scan invoices and route them through an ESB. Simple ones are verified and decisions are automated using ILOG. More complex ones are routed to the case management system (again using ILOG rules-based assignment) with embedded instructions (generated from more ILOG rules). These are displayed to experts using an environment that combines the invoices, master data and decision support. Because they are still using a mainframe application they use a mixed interface that displays a mainframe screen with claims information related to several invoices, a display of an invoice and a decision support screen.

Managing complexity in rules is a focus area for them. Rules become complex when multiple objects with multiple properties must be considered. An example rule with 9 conditions requires 500 test cases. The handling of exceptional cases is a particular indicator of complexity. To manage this they use ruleflows to put default rules (simpler, cover lots of cases) first then create a series of exception steps with each exception step handling a few rules for a group of exceptions. This prevents the complexity from overwhelming rule editing. They use the Business Action Language to make the rules accessible to business users and they put business experts into the QA process, having them create and run tests for their rules. Regression tests are handled by IT with experts conducting random tests on the new version.

Benefts:

  • BRMS uses lots of facts, more than a person would, and so the system decides slightly better than the experts used to.
  • Supports those who handle cases so that less experienced handlers (trainees for instance) helping them close out potentially complex claims. More claims can be hanlded by the usual teams.
  • Increased agility – they were able to add the rules for detecting simple cases and QA the rules in just 4 weeks.
  • Resources are allocated more efficiently with claims being  routed to case handlers or to experts appropriately. Fewer are routed to experts (less than 40%), improving response time.

They plan to extend the system to handle underwriting as well as invoices from more kinds of providers.


Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Hidden AI, a risk?
Hidden AI, Real Risk: A Governance Roadmap For Mid-Market Organizations
Artificial Intelligence Exclusive Infographic
unusual trading activity
Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
Analytics Exclusive Infographic
Ai agents
AI Agent Trends Shaping Data-Driven Businesses
Artificial Intelligence Exclusive Infographic
Why Businesses Are Using Data to Rethink Office Operations
Why Businesses Are Using Data to Rethink Office Operations
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Splunk: Big Data Machine for Operational Intelligence

10 Min Read

What is Your Market Research Identity?

5 Min Read
big data is impacting trading
Big DataBusiness IntelligenceExclusive

How Big Data Technology Impacts Investments and Trading

5 Min Read

Getting to Enterprise Application 2.0

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?