Case Study

The data doctor: How Genpact’s data engineering skills helped a specialty insurance carrier deliver peace of mind

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WHO WE WORKED WITH

A leading US provider of healthcare liability insurance with over 300,000 clients and $1.5 billion in annual premiums

WHAT THE COMPANY NEEDED

  • More accurate and available data to drive more consistent and efficient claims decision-making
  • Better work allocation between employees to ensure speedier resolution of claims
  • Improved coordination between data teams during the cloud transition project and for ongoing work in the data center of excellence (CoE)

HOW WE HELPED

  • Collaborated with the client to build a data CoE and expert team
  • Implemented and orchestrated the latest technology such as Informatica PowerCenter, PySpark, and Anaconda. Instilled best practices and project and data management to improve workflows
  • Created a robust and scalable enterprise data warehouse (EDW) and organization data service (ODS) with a cloud-based data lake, all governed by best practices and data frameworks

WHAT THE COMPANY GOT

  • A strong, diverse internal team of data experts to manage the transition project and CoE
  • Best-in-market tools with the associated governance and security to resolve claims accurately, quickly, and securely
  • Data architecture embedded with advanced analytics and predictive insights that empower claims, reimbursement, and underwriting teams to work together more efficiently and accurately

​CHALLENGE​

For many health professionals, medical malpractice lawsuits are inevitable. But they can be stressful and career-defining. And because each claim is unique, it’s incredibly important that healthcare liability insurers have the knowledge, ability, and flexibility to address each exposure on its own terms.

Nowadays, providing effective liability insurance and medical malpractice claims resolution means one thing: having a tight grip on a lot of data. Data is the key to a well-priced, well-managed claim. And it’s essential to provide the customized insurance cover and claims resolution today’s rapidly changing healthcare landscape requires.

But the company didn’t have the data or the data architecture it needed to be confident in its claims decisions. It was also struggling with inefficient operating models and processes. It hadn’t established best practices and standards for the technology it was using, and its data lake project had yet to take shape. The client had three main problems: first, it didn’t have the right team, second, it didn’t have the right processes, and third, it was either underutilizing technology or, in some cases, missing it entirely. 

​SOLUTION​

After detailed conversations with the client, including providing access to our subject matter experts during the planning stage, we settled on a threefold solution:

1. Build a team that could handle the transition from legacy technology to cloud-based data, advanced analytics, and automation

2. Define the standards and workflows that would unleash the power of the team and the technology 

3. Provide the client with market-leading technology that could integrate, process, and manage data for enhanced claims outcomes

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And we put this into action by:

1. Building a strong team for the CoE, using a multilevel evaluation and selection process to find talented employees

2. Collaborating with the insurer to design processes and frameworks to govern the technology about to be implemented

3. Building a technology ecosystem with an on-premises EDW and ODS, and a cloud-based data lake with a secure, high-performance data flow between them

4. Building and testing an integrated, robust, scalable, fault-tolerant, high-performance data management and data science workflow system using tools and technology such as Informatica PowerCenter, Python, and Amazon Web Services

IMPACT

Our client now has a strong, expert team that can continuously improve on-the-ground service delivery. Both the team and processes are rigorously governed, and the increased use of automation means that employees’ bandwidth is fully utilized and revenue leakage is minimal. The automation also resulted in improved data quality and risk management processes.

As a result, the insurer has expanded the team’s work into other revenue-generating areas. Now its billing and payment operations are more timely, and cash flow has
improved.

The new technology suite allows the team to leverage ingested data for predictive insights, advanced analytics, and informative data visualizations. The technology we put in place also uses machine learning and artificial intelligence to extract insights from a claims super dataset, so the insurer can leverage the maximum amount of data to solve customers’ problems. The solution helped the insurer achieve an 80% reduction in process runtime, which enabled faster decision-making.

Our solution has improved pricing, smoothed the resolution of claims, enhanced efficiencies, and provided a 360-degree view of customer data. But it’s all ultimately geared toward one goal: customer satisfaction, which is invaluable during the stresses and strains of a medical malpractice lawsuit.

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