Market intelligence analytics consulting for a niche insurance domain space in U.S

Case Synopsis

TIISAA stands for Title Insurance Intermediaries Search and Analytics Application. It is the name of the analytics consulting application that was developed by Zivanta Analytics for Servicelink, a premier provider of title insurance services in US. It aimed at assisting Servicelink to increase the market share of title insurance premiums in NY, TX, CA, PA and few other major states. Zivanta tied up with Servicelink as a strategic partner to devise a robust market entry strategy for the latter. The market entry strategy would be based on a market intelligence suite that will be designed and developed taking into account diverse economic and market forces.

About the Client

Servicelink is a major subsidiary of Fidelity National Financial, one of the most prominent players in the title insurance sector and largest provider of commercial and residential mortgage diversified services in United States. Servicelink has been providing loan transaction services to the mortgage industry for more than 47 years under its parent company being Fidelity.

The Challenge

This was basically a market entry consulting project. The entire study was to identify where Fidelity stand in the title insurance market state-wise. The client’s objective was to get an understanding of the states to focus on as well as the ones which are dead horses. In other words Fidelity wanted to derive an idea of their position across US states in terms of competition. The study also aimed at identifying the potential markets for title insurance in relation to population and housing growth for implementing expansion plans in the emerging areas of US.

The Approach

The entire project was tied up from 2 perspectives: Macro and Micro. Given below is a high level overview of the work that went into Macro and Micro analysis for Servicelink using TIISAA:

Steps Performed in Macro Analysis (overview)

• We initially started with an industry research whitepaper on the Title Insurance industry.
• We then identified 4 top market leaders and downloaded all the historical financial statements with their market share information. Compiled a presentation to understand market movements, market trends and a company’s operational performance.
• We went further to calculate the title insurance premium growth rate and the market share of the top 4 major players and clustered all others together by using a metric called Herfindahl Index (HHI). The FHHI (Fidelity HHI) was also calculated for each state, and the bubble chart and HHI index of Fidel ity gave a good depiction of where Fidelity lies in terms of competition.
  After that we gathered U.S Census data to study and analyze the population growth, housing and mi gration trends.
• We again repeated the Herfindahl Index analysis based on population against housing and migration and developed heatmaps could directly conclude the extent of monopoly or oligopoly of a certain market in the U.S

Steps Performed in Micro Analysis (overview)

• Downloaded Corelogic data across different parameters, all underwriters and agencies to drill down our macro analysis to a more granular level and then aggregate trends from the micro variables.
• All the above historical loan level data was used to make dashboards using UI tools like Tableau and da tabases like PostgreSQL.
• We then tied up with listing partners like Realtor, Zillow, Trulia etc., to cull property listing data. This data
• helped us identify the top performing brokers at the most granular level like county, or even a zip.
  As a final step in this module, we packaged business intelligence tying up the brokers and title agencies, identifying all the challenges and opportunities so that we arrive at actionable recommendations for our client

The Outcome

The final outcome, apart from the phase-wise milestones was a presentation outlining Business Strategic Options and Recommendations in each option. The options also contained the pros and cons to be taken into consideration. The option sets were data backed, validated and a robust outcome from an extensive