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Company: Penn Mutual
Industry: FinanceInsurance
Functional Use Case: Data Store, Analytics

The Challenge

Being an almost 170-year-old company, it is not easy for Penn Mutual to change years of IT infrastructure to meet the needs coming from their Lines of Business. Penn Mutual has numerous types of data, distributed throughout legacy systems and databases, including mainframes, relational databases (RDBMS), and other storage areas making it difficult to gain a holistic view of data let alone analyze the data to make informed business decisions. Moreover, because of data duplication, Penn Mutual ran into informational trust issues with data, causing inconsistency depending on where it was accessed from.

In 2010, Penn Mutual’s Information Management and Technology Division, the IT arm of the business, started a project called “Core Services.” They aimed to merge all data domains spread throughout the company into a single source by marrying their service-oriented architecture and master data management capabilities into a comprehensive system.

Penn Mutual started with a traditional RDBMS approach for the persistence layer of their Core Service but soon realized that it could not meet their requirements for application performance or scalability with the existing RDBMS footprint without a large cost commitment.

The Solution

The team decided to turn to NoSQL databases to address their needs. “We evaluated other NoSQL products, but the fact that large scale organizations were using DataStax Enterprise successfully gave us the confidence that Apache Cassandra could handle our performance and scalability requirements”, said Mark Dash, Assistant Vice President of Information Technology at Penn Mutual. After some research, the team was even more attracted to Cassandra’s ability to ensure linear scalability to any size, high performance, and system reliability.

In addition, the integrated enterprise search via Apache Solr™ allows them to offer traditional data access services and ad-hoc queries to create more data discovery type applications.

Penn Mutual stores their data information in a 6-node Cassandra ring. They use Solr API to search data, which improves their ability to find information and pull reports.

The Results

Penn Mutual can now move forward with a much more flexible technical backbone and greater opportunities to perform analytics with years of historical data consolidating into the Core Service.

With all data centralized in Cassandra, Penn Mutual is in a position to offer internal users and even external partners and clients access to information from authoritative services when needed through web applications, mobile processes, and so on.

Today, areas of the business are evolving and innovating at Penn Mutual. For example, agents will have access to comprehensive information about policies and clients coupled with faceted and ad-hoc searching across their entire book of business. Additionally, Penn Mutual is also rolling out new applications, relying on the massive volume of data stored in Cassandra to help their team provide optimal service and improve customer satisfaction.

“[The solution] has allowed us to break the complexities of our legacy systems, empowering us to leverage data to innovate and make more informed decisions so we can provide a truly personalized and premium experience to our customers.”

Stack Includes: Apache Cassandra, Apache Solr, Apache Spark, Datastax Enterprise

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