Reducing Labor Costs and Improving Accuracy: MRH Trowe Automates Insurance Data Processing with AI
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4,000
hours of labor saved annually
Seconds
to process each document instead of minutes
€135,416
labor costs saved annually
Challenge
MRH Trowe was facing inefficiencies in processing insurance policy data due to manual extraction from PDFs. This process was time-consuming, required specialized training, and was prone to human error.
MRH Trowe was facing inefficiencies in processing insurance policy data due to manual extraction from PDFs. This process was time-consuming, required specialized training, and was prone to human error.
Solution
By implementing Matillion and Snowflake’s Document AI feature, MRH Trowe automated data extraction, saving 5 minutes per document for 25-50,000 documents, resulting in 2-5,000 person-hours saved per year.
By implementing Matillion and Snowflake’s Document AI feature, MRH Trowe automated data extraction, saving 5 minutes per document for 25-50,000 documents, resulting in 2-5,000 person-hours saved per year.
Results
Automating this tedious process freed up highly trained account managers to focus on more strategic tasks, enhancing overall efficiency and reducing labor costs. By significantly reducing manual effort, this automation allowed account managers to dedicate more time to spend with customers, increasing sales and ensuring higher levels of customer satisfaction.
Automating this tedious process freed up highly trained account managers to focus on more strategic tasks, enhancing overall efficiency and reducing labor costs. By significantly reducing manual effort, this automation allowed account managers to dedicate more time to spend with customers, increasing sales and ensuring higher levels of customer satisfaction.
With this solution, we’re pioneering a unified data model for all insurance divisions, enhancing data quality through effective quality gates.Malte Polley Team Leader, Data Analytics and AI,| MRH Trowe
Challenge: Manual Data Extraction and Processing Inefficiencies
MRH Trowe, a German-based insurance broker, still exchanges data through paper-based documents, as they are not required to provide APIs or a system for document exchange. This meant that employees had to extract data from letters manually, input it into Excel, format it for database entry, and finally process it through CRM tools. Processing a batch of documents from the same insurance company takes anywhere from 2 to 10 minutes per document, with the process being easier when dealing with uniform documentation. However, when handling documents from multiple insurers, variations in format made the task even more time-consuming and complex. MRH Trowe processes around 50,000 of these documents annually. This method was inefficient, costly due to training requirements, and error-prone.
MRH Trowe, a German-based insurance broker, still exchanges data through paper-based documents, as they are not required to provide APIs or a system for document exchange. This meant that employees had to extract data from letters manually, input it into Excel, format it for database entry, and finally process it through CRM tools. Processing a batch of documents from the same insurance company takes anywhere from 2 to 10 minutes per document, with the process being easier when dealing with uniform documentation. However, when handling documents from multiple insurers, variations in format made the task even more time-consuming and complex. MRH Trowe processes around 50,000 of these documents annually. This method was inefficient, costly due to training requirements, and error-prone.
Solution: Automated Data Extraction with Matillion and Snowflake
To address these inefficiencies, MRH Trowe leveraged Matillion and Snowflake’s Document AI feature. In a test case with 60 insurance policies, the pipeline completed the task in just 50 seconds, dramatically reducing the time per document. Additionally, the solution enabled MRH Trowe to implement a more generic approach to processing insurance documents, not limited to just car insurance policies. This is the first time the company has been able to adopt a generic data model across different insurance divisions. By integrating quality gates, they also improved overall data quality, reducing errors and enhancing the reliability of the data. This solution not only automated data extraction but also allowed the company to streamline processes and improve data accuracy, creating efficiencies across the board.
To address these inefficiencies, MRH Trowe leveraged Matillion and Snowflake’s Document AI feature. In a test case with 60 insurance policies, the pipeline completed the task in just 50 seconds, dramatically reducing the time per document. Additionally, the solution enabled MRH Trowe to implement a more generic approach to processing insurance documents, not limited to just car insurance policies. This is the first time the company has been able to adopt a generic data model across different insurance divisions. By integrating quality gates, they also improved overall data quality, reducing errors and enhancing the reliability of the data. This solution not only automated data extraction but also allowed the company to streamline processes and improve data accuracy, creating efficiencies across the board.
Results: Increased Efficiency and Cost Savings
Automating the data extraction process eliminated the need for skilled account managers to perform low-value administration tasks, allowing them to focus on higher-impact work. This not only enhanced productivity but also resulted in significant labor cost savings. With an average hourly wage of €32.50, reducing the manual effort by 5 minutes per document, across 50,000 documents per year, translated to a total of 4,166.67 hours saved. This resulted in €135,416.67 in labor cost savings annually.
Automating the data extraction process eliminated the need for skilled account managers to perform low-value administration tasks, allowing them to focus on higher-impact work. This not only enhanced productivity but also resulted in significant labor cost savings. With an average hourly wage of €32.50, reducing the manual effort by 5 minutes per document, across 50,000 documents per year, translated to a total of 4,166.67 hours saved. This resulted in €135,416.67 in labor cost savings annually.
What's next for MRH Trowe?
MRH Trowe is in discussions to expand this automation approach to other areas within the business, identifying additional opportunities to drive efficiency and cost savings through AI-driven data processing.
MRH Trowe is in discussions to expand this automation approach to other areas within the business, identifying additional opportunities to drive efficiency and cost savings through AI-driven data processing.
About MRH Trowe
MRH Trowe is an independent insurance broker and risk management firm serving clients across various industries. The company offers a range of services, including insurance brokerage, employee benefits, pensions, finance, risk management, and fleet damage control. By providing tailored solutions, MRH Trowe helps businesses and individuals manage risks, protect assets and liabilities, and achieve their financial objectives.
MRH Trowe is an independent insurance broker and risk management firm serving clients across various industries. The company offers a range of services, including insurance brokerage, employee benefits, pensions, finance, risk management, and fleet damage control. By providing tailored solutions, MRH Trowe helps businesses and individuals manage risks, protect assets and liabilities, and achieve their financial objectives.
About Matillion
Matillion is the data pipeline platform for data teams to build and manage pipelines faster for AI and analytics - at scale. Matillion empowers data teams with no-code and AI capabilities to be wildly more productive in building pipelines, integrating data wherever it lives and delivering data that’s ready for AI and analytics, while harnessing the processing power and scale of their cloud data platforms and cloud provider.
Matillion is the data pipeline platform for data teams to build and manage pipelines faster for AI and analytics - at scale. Matillion empowers data teams with no-code and AI capabilities to be wildly more productive in building pipelines, integrating data wherever it lives and delivering data that’s ready for AI and analytics, while harnessing the processing power and scale of their cloud data platforms and cloud provider.