LEADING AUTO INSURANCE COMPANY: XTIVIA MASTER DATA MANAGEMENT

ORGANIZATION

The client is a leading property & casualty insurance provider specializing in auto insurance programs. The client specializes in personal automobile insurance with a focus on non-standard auto policies, which accounts for more than 90 percent of premiums. The client also writes standard and preferred personal auto insurance, monoline commercial auto insurance and classic collector automobile insurance. The client has a presence in 44 states and has a network of more than 12,000 independent agents.

BUSINESS CHALLENGE

Our client is the 2nd largest provider of non-standard automobile insurance in the nation. Around 2,000–5,000 policies are written every day with more than 95 percent of the policies written by the agents. The information provided during a new business quote request was not matched with current and past customer history, resulting in rewriting policies for past high-risk customers or losing past low-risk customers. This has resulted in increased cost and reduced profits. The business wanted XTIVIA to help them:
  • Reduce loss by identifying high-risk returning customers.
  • Reduce loss by identifying non-paying returning customers.
  • Increase margins by identifying low-risk returning customers.
  • Increase customer retention by identifying current customers shopping for policies.
  • Improve marketing process effectiveness and then increase conversion rates by driving the right offer to the right people at the right time.
  • Empower the business to look at the customer 360 degrees, analyze customer trends, and then to perform predictive analytics.

PROJECT CHALLENGE

The client’s policyholder information was scattered across several legacy systems. The only centralized view was available in the Enterprise Data Warehouse, which offered neither real-time data nor a complete 360-degree view of the policyholder. There was a duplication of data across multiple systems resulting in unreliable data due to inconsistencies and poor data quality. The customer-matching rules are complex making it difficult to match the requesting customer information with any one or more legacy systems data. The new Policy Rating Engine did not have access to the customer 360-degree view of past and current policyholders in real-time. This lack of visibility forced the business to ignore the historical view of the policyholders while rating the policy, resulting in new policy quotes to high-risk and non-paying returning customers. Additionally, while providing quotes to third-party raters, the rating engine could not match the requested information with past and current policyholder information. The result was unidentified current low-risk customers that were shopping for new policies with third-party raters, which resulted in the loss of good customers.

The root challenges were:

  • Poor Data Quality of the policyholder information.
  • Complex match and merge rules for identifying customers.
  • Lack of real-time identification of high-risk policyholders while providing quotes through thirdparty rating exchanges.
  • Lack of centralized and holistic view of the current and past customers.

The Client required a consistent, efficient, automated, and easily maintainable solution that would identify a customer with a high degree of confidence, in real-time, and provide the 360-degree view of that customer to the requesting business process.

SOLUTION

XTIVIA implemented a Customer Master Data Management (MDM) solution with a 360-degree view of the policyholders/customers. XTIVIA used its MDM Project Execution Accelerator for identifying the:

  • Key team members.
  • Defining the scope.
  • Documenting Data quality, integration, and governance requirements.
  • Identifying Project deliverables.
  • Defining Solution KPIs.

We first developed a multi-phase roadmap for incremental value delivery of the MDM solution. This Roadmap catered to the delivery of MDM value to multiple use-cases over a 12 month period. XTIVIA’s MDM Solution involved establishing a Data Governance Office (DGO), Data Governance Processes, multi-domain modeling of the policyholder, sourcing data from multiple systems, matching and merging the duplicate customer information, cleansing the data, establishing a centralized clean MDM data source, and synchronizing the cleansed data with all interested source systems. XTIVIA also implemented SOAP and RESTful services for real-time access to the Policy Holder information. The customer data model was specific to our client’s needs and included several aggregate and derived values that helped to better understand the policyholder.

SUCCESS POINTS

  • The first customer success point involved building the core foundation of the Customer Master that will benefit the real-time rating engine in identifying returning customers. This allowed us to enhance the rating algorithms to incorporate the customer history in the rating engine.
  • The second customer success point involved contacting the low-risk policyholders who are shopping for new policies. This proactive customer contact resulted in increased customer retention.
  • The third customer success point involved integrating the IVR system with their Customer MDM to predict the reasons why customers called the service department. Predicting the reason and offering proactive dynamic options (e.g., providing a grace period for payments to low-risk customers as an IVR option) to the callers allowed us to reduce the load on the customer service representatives. This resulted in a workload shift of the customer service representatives toward new customer calling rather than spending their time on issues that could be taken care of by IVR. This allowed our customer to grow their sales and revenue.

RESULTS

Using XTIVIA’s various resources and services, we were able to provide the client with:

  • Provided long-term MDM solution for the customer to use and build on as their need for additional data management arises in the future.
  • Reduced high-risk returning customers.
  • Increased low-risk returning customers by providing effective policy rates.
  • Increased customer retention by proactive outreach to shopping customers.
  • Increased the staff that catered to new business development by reducing service desk workload.
  • Increased customer satisfaction through proactive menu options through IVR to calling customers.

SUMMARY

XTIVIA helped our Client by:

  • Documenting the requirements of Customer Master and business scenarios that will benefit from the Customer Master.
  • Identifying and establishing the Data Quality and Data Governance process.
  • Performing analytics on existing data to identify possible data quality issues.
  • Solving customer data quality issues.
  • Identifying the existing process gaps and challenges that their business currently faces with analytics.
  • Proposing and implementing the Master Data Management architecture and solution.
  • Implementing the Integration of high-quality data with all consumer systems based on the ESB and SOA.
  • Implementing the Integration with the EDW for the analytics on the customer data.

KEY COMPONENTS

TECHNOLOGIES & SOLUTIONS USED

XTIVIA Master Data Management (XMDM)

TIBCO MDM

TIBCO BusinessWorks

TIBCO Patterns

TIBCO EMS

TIBCO Spotfire

Java, HTML5, AngularJS

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