As insurers look to prioritise efficiency and automation, Ushur’s Data Transformation Engine is helping insurers automate data problems and deliver remarkable improvements in business metrics.
The exchange of information across sectors like FMCG, Shipping, Finance, and Insurance is typically performed using columnar data files. A universal and familiar mechanism for data sharing, the row-column format, is also optimised for digital processing. Much of the financial decision-making and estimation is based on data stored in these files, commonly referred to as CSVs (comma separated values). Over time, Microsoft Excel has risen to become the industry standard for visually processing CSVs, offering advanced user functionalities like embedded tables and logically partitioned ‘Sheets’.
Excel/CSV files are widely employed in many business discussions, most prominently in the dialogue between insurance brokers and insurance carriers. The Request for Proposal (RFP) phase, in particular, utilises CSV files for information exchange. Insurance brokers in the US range from part-time individuals to large organisations employing hundreds. When these brokers engage with potential companies for their insurance needs, they employ their unique styles and lexicon to relay gathered information.
One of the main challenges in automation lies in the complexity created by the variance in data representation. For instance, a column indicating “Date of Birth” could appear as “DOB”, “Birth date”, “Employee dob”, etc. Combine this with approximately 100 columns of data for each customer, and the complexity of the task becomes apparent.
According to Ushur, efficiency and automation are top priorities for insurance carriers in 2023. As carriers automate aspects of their backend and quote processes, handling discontinuity in data format and structure becomes increasingly challenging, often requiring manual intervention. It is estimated that in many instances, cleaning and structuring data for appropriate persistence in Systems of Record (SORs) can take between 1 and 5 days.
This is where Ushur’s Data Transformation Engine comes into play, making an immediate impact by introducing automation to a problem traditionally dominated by manual operations. This results in a high degree of efficiency by significantly reducing the time taken to process the entire workflow. Read the full post from Ushur here.
Ushur’s solution recognises hundreds of variances in incoming file data spread across rows and columns, intelligently classifying each data column into an appropriate category. It normalises variations in incoming Excel/CSV files, presenting data that customers’ Systems of Record can readily ingest automatically.
Key implications of the Ushur solution include converting hundreds of variant documents into a single, simple format and significantly reducing the time for manual processing. Currently, manual processing of this nature takes around 1-5 days. With automation, Ushur is processing 200+ cases per day with an average execution time of 3 minutes. The solution also allows for easy integration into the customer’s database/systems and provides a straightforward method to add more automation steps as the customer begins to see the value in such transformation.
Ushur’s columnar data transformation engine is a component of the patented Ushur Document Intelligence Services Architecture (DISA) and is incorporated within Ushur Intelligent Document Automation™ (IDA). DISA applications have led to remarkable improvements in business metrics for our customers. For instance, one of Ushur’s clients was able to reduce manual labour from 30-36 hours to about 3 minutes. In numerous instances, there was no human intervention, freeing up agents to focus on more meaningful interactions rather than back office tasks. Best of all, the ability to create new rules quickly via the Ushur no-code flowbuilder enables Ushur to provide ROI to customers in days.
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