This case study illustrates how WNS leveraged its Artificial Intelligence (AI)-led platform to intelligently automate and accelerate data extraction for a leading insurer that provides coverage for vehicles, properties, general liability, additional interests and more.

As we know…

The insurance sector is evolving, with customers now holding more sway than before. Companies must re-think how they provide their services to customers, incorporating greater flexibility to accommodate changes in information and plans.

Although Mid-term Adjustments (MTA) in insurance plans have become commonplace, the process generates significant paperwork. The challenge is further exacerbated when the process is manual and involves numerous change requests.

Thus, automation in insurance has become critical. Implementing an automated and scalable workflow system that can extract and contextualize data using intelligent algorithms will help insurers improve efficiency, accuracy and Turnaround Time (TAT).

The challenge for the client was….

It processed over 100,000 MTAs annually, necessitating a colossal volume of administrative work, complex workflow management, coordination and multiple applications. The process involved manual information updating, laborious underwriting procedures and change communication with customers.

While an extended TAT negatively impacted customer experience, manual data extraction led to inefficiencies, errors and steep operational costs.

As a co-creation partner…

WNS Triange – our data, analytics and AI practice – identified workflow management as the primary challenge and proposed an AI / Machine Learning (ML) solution to digitize and expedite the MTA process.

Leaning on Triange NxT, a core pillar of WNS Triange, we deployed our AI-led data contextualization platform, SKENSE, to automate data extraction. We leveraged sophisticated AI / ML models with computer vision to extract and contextualize details from the ACORD 175 and Policy Change Request (PCR) forms.

Skense AI Led Automated Data Extraction

Driving Intelligent Automation in Insurance with SKENSE

Key aspects of this intelligent automation solution included:

Automated ingestion of email-based data

Automated ingestion of email-based data

Intelligent data classification and cataloging

Intelligent data classification and cataloging

Proprietary AI algorithm

Proprietary AI algorithm to contextualize information, and create structured and harmonized data sets

Final output integrated

Final output integrated with the client application (through application programming interfaces) for further downstream processing to reduce revenue leakage

Embedding SKENSE in the MTA process enabled…

  • Increased accuracy in downstream processing, leading to a decrease in revenue leakage
  • Customized and predictable workflows aligned with insurance standards
  • A scalable system adept at handling more requests and coverages


requests (daily) digitized for various insurance coverages


fields (on average) extracted per request


data accuracy, resulting in a significant reduction in customer complaints and improved customer experience


improvement in TAT

About WNS Triange:

WNS Triange (formerly WNS Research and Analytics practice) powers business growth and innovation for 120+ global companies with data, analytics and Artificial Intelligence (AI). Driven by a specialized team of over 4000 analysts, data scientists and domain experts, WNS Triange helps translate data into actionable insights for impactful decision-making. Built on the pillars of consulting (Triange Consult), future-ready platforms (Triange Nxt), and domain and technology (Triange CoE), WNS Triange seamlessly blends strategy, industry-specific nuances, AI and Machine Learning (ML) operations, and intelligent cloud platforms.

Driving a futuristic edge are WNS Triange’s modular cloud-based platforms and solutions leveraging advanced AI and ML to provide end-to-end integration and processing of data to actionable insights. WNS Triange leverages the combined strength of WNS’ domain expertise, co-creation labs, strategic partnerships and outcome-based engagement models.

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