Overview:
WebBank, a leader in the digital lending space, sought a solution to streamline its complaint analysis process, enhance risk identification and reduce unnecessary operational burden.
Traditional manual processes were slow and labor-intensive, making it challenging to uncover trends quickly and ensure consistent data storytelling. With Zanko ComplianceAssist AI, WebBank achieved an 80% improvement in efficiency, setting a new standard for operational excellence.
The Challenge:
WebBank faced several pain points in its complaint analysis process:
Slow Manual Processing: Complaint handling required significant time and effort.
Operational Strain: Teams spent excessive hours sorting through complaint data, increasing operational costs.
Fragmented Data Sources: Fragmented systems made it labor intensive to present coherent, data-driven narratives or analyze trends quickly.
Decreased Accuracy: Relying on human labeling had the potential to cause inconsistencies in accurate labeling.
Root Causes:
Manual Processes: Traditional complaint-handling methods struggled to scale with WebBank’s growing data volume without adding additional resources and expense.
Data Fragmentation: Varying data formats across multiple sources made trend identification inefficient.
The Solution:
Spring Lab’s Zanko ComplianceAssist AI
Spring Labs collaborated closely with WebBank to deploy Zanko ComplianceAssist AI, tailoring the solution to align seamlessly with existing processes while driving substantial operational efficiencies. The integration process involved the following:
Customized AI Integration: Spring Labs adapted Zanko to fit WebBank’s workflows, ensuring smooth adoption by working iteratively with WebBank’s team.
Risk Identification: Zanko enabled WebBank to detect potential risks faster by analyzing large datasets with precision.
Data-Driven Storytelling: WebBank used Zanko’s generative AI capabilities to present compelling well-substantiated narratives and uncover trends faster than ever.
Proof of Concept (POC)
Spring Labs ran a POC phase to ensure the product met WebBank's needs. Through demos and regular feedback sessions, they iterated on the solution to optimize alignment with operational requirements.
Testing to Prove ROI
Spring Labs conducted a thorough ROI Assessment with the Compliance team at WebBank, focusing on different operational units, including Risk Management and Customer Complaints Handling. These sessions were structured to reflect real-world workflows frequently completed by WebBank analysts, allowing for an accurate assessment of both efficiency gains and accuracy enhancements.
The team worked with approximately 12 months of historical complaints data to showcase the tool's value using real-life complaints.
During the testing phase, Compliance Analysts worked hand in hand with the SpringLabs team to examine how much faster the workflows could be. For half of the time, they used Zanko ComplianceAssist AI to input complaint data and receive real-time, AI-generated insights. The other half required them to rely solely on manual methods—accessing spreadsheets, internal knowledge bases, and regulatory portals to gather and analyze information.
Working a complaint could be defined as going through the raw complaint, summarizing the complaint, categorizing the complaint, assigning risk scores and taking proper steps to resolve the complaint, and putting together reports on all complaints data.
Quantitative Results:
The results showed strong accuracy gains depending on the size of the team and the types of complaints and the complexity of the policy.
In terms of categorizing the improvements:
* is defined as results based on human evaluation of the outcomes
Speed of working a complaint:
These results demonstrated how Zanko ComplianceAssist AI significantly reduced the time needed to analyze complaints, empowering analysts to focus on more strategic, high-value tasks. The tool’s ability to automate categorization and detect trends across fragmented data allowed WebBank to optimize its operations, driving better performance and faster risk mitigation.
WebBank achieved transformational results:
80% Reduction in Complaint Analysis Time: AI-powered automation drastically accelerated processing times compared to manual efforts.
Proactive Risk Identification: The platform unearthed actionable insights that would have taken much longer to discover with traditional methods.
Enhanced Operational Efficiency: Teams reallocated time from repetitive tasks to higher-value activities like risk mitigation and client management.
Scalability without additional FTE costs: The platform was able to replace the work of 1-2 FTEs at current scale and created a scenario where additional FTEs are not needed with growth.
Feedback and Support
WebBank praised the customized approach Spring Labs took during the implementation process, ensuring the platform aligned perfectly with their needs. However, they also highlighted areas for improvement where they expressed interest in revisiting early discussions around data collection and standardization, which had been de-scoped from the initial implementation.
Quote from WebBank Leadership:
“The actual product is transformative. The risks it helps us identify and the insights it enables us to uncover have generated significant enthusiasm throughout the organization. Going from Beta to Production, the product kept getting better and consistently exceeded expectations and has delivered increasingly impactful results.”
— Jim Jackson, SVP Strategic Partner Oversight, WebBank
Customization and Ongoing Support
Iterative Adjustments: Spring Labs collaborated closely with WebBank, continuously fine-tuning the platform based on user feedback.
Smooth Integration: The focus on aligning with WebBank’s processes ensured minimal disruption during onboarding.
Ongoing Partnership: Spring Labs remains engaged with WebBank as the platform evolves, working towards a full rollout of Zanko as a core component of complaint management.
Anticipated Impact
WebBank anticipates even more significant impacts as they continue to refine their use of Zanko ComplianceAssist AI:
Increased Customer Satisfaction: Faster complaint resolution times are likely to contribute to higher satisfaction levels for customers.
Risk Mitigation: Proactive identification of risks are expected to reduce regulatory risk exposure.
Cost Efficiency: AI-driven automation will lower operational costs by reducing manual workload.
Conclusion:
WebBank’s partnership with Spring Labs and the adoption of Zanko ComplianceAssist AI has already proven transformative. With complaint analysis times reduced by more than 80% and the improved ability to present data-driven narratives, WebBank is poised to make Zanko an essential part of its operations. The successful POC has generated enthusiasm within the organization, positioning the AI-powered platform as a cornerstone of future processes.
