Insurance brokerage uses Catalytic to drive process efficiency, accuracy
Customer Company Size
Mid-size Company
Region
- America
Country
- United States
Product
- Catalytic
Tech Stack
- Automation
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Predictive Replenishment
Services
- System Integration
About The Customer
The customer is a national insurance and financial services firm that facilitates the selection of insurance packages for businesses of all sizes. The company has a footprint across 40 offices in 15 states and serves over 20,000 customers. The firm employs 750 people and is involved in a significant amount of manual work in delivering its services. Proposals include quotes from several different insurance carriers on up to five different types of insurance, including medical, dental, life, and more. Each client proposal is typically a dozen or more pages and uniquely formatted based on the insurance carrier and the specific insurance type.
The Challenge
The insurance and financial services firm was struggling with a manual quote-to-proposal process that was inefficient and negatively impacting revenue. The process involved employees manually reviewing each quote, extracting more than 200 fields of data to create a spreadsheet, and developing a consolidated report presented to the client. Once a plan was selected, the company would have to prepare a customer onboarding booklet with all coverage details. The entire process was tedious, time-consuming, and prone to error. The cost of business with small clients was incredibly high due to the manual nature of the process.
The Solution
The company’s leadership team approached Catalytic to help deploy automation to improve the process. They had five goals in mind: save significant employee time, deliver proposals to clients more quickly, reduce typos and manual errors, build a repository of quote data and use business intelligence and machine learning to make it smarter over time, and establish a success case to expand intelligent automation across the company and its subsidiaries. Catalytic automated five of six steps to reduce the processing time per quote to approximately one minute with more than 95% accuracy.
Operational Impact
Quantitative Benefit
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