Unlocking cost savings and efficiency with Handl.ai for an SME
Case studies block. Session 2
In this article I present a case study showcasing how Handl.ai, an innovative document processing and automation solution bring significant cost savings to businesses. Through the exploration of a real-world scenario, I evaluate how Handl.ai empowers organisation to streamline their processes, reduce staffing expenses, and enhance scalability, ultimately leading to substantial financial benefits.
In today’s rapidly evolving business landscape, the efficient handling of documents, data, and processes is crucial for staying competitive. Handl.ai emerges as a transformative force, offering cutting-edge solutions in document recognition, facial recognition, and anti-fraud measures. This article delves into a compelling case study illustrating the tangible advantages of incorporating Handl.ai into one’ business operations.
The Challenge:
Imagine a Microfinance organization (MFO) facing the dual challenges of escalating operational costs and a growing volume of applications. To maintain efficiency and profitability, the MFO sought a solution that could address both issues simultaneously. Let’s see how Handl.ai can address this complex conundrum.
The Existing Scenario
Before integrating Handl.ai, the MFO employed eight operators to process a monthly average of 4,300 applications. These operators were collectively drawing a substantial monthly salary of £32,000, which translated to an annual expenditure of £256,000.
The Handl.ai transformation
With Handl.ai’s advanced document processing capabilities, including recognition, facial recognition and comparison, and anti-fraud measures, the MFO was able to streamline its operations significantly. As a result, the staffing requirements were reduced to just three operators. Combining their salaries with the cost of Handl.ai, the MFO’s monthly expenses were reduced to £9,550 from £21,333.
The cost savings
The implementation of Handl.ai led to immediate and substantial cost savings for the MFO. By transitioning from eight operators to three, they reduced their monthly expenditure by £11,780, amounting to a yearly saving of £141,400.
Scaling efficiency
One of the remarkable features of Handl.ai is its scalability. As the MFO saw an increase of 36% in the number of applications, they contemplated the prospect of hiring three additional operators to manage the workload, incurring an additional cost of £8,000 per month.
The Handl.ai advantage
However, by embracing Handl.ai, the MFO maintained operational efficiency without expanding their workforce. With just three operators and Handl.ai in place, they achieved monthly expenses of £516. This not only ensured operational smoothness but also resulted in substantial cost savings of £7,484 per month and £89,808 per year, a remarkable 25.5% reduction.
Enhanced scalability
In this scenario, it’s important to consider the future. If the MFO’s application volume were to increase to 600, the conventional approach would require them to hire an additional operator, incurring an extra £2,666.67 per month.
The Handl.ai solution
Handl.ai offers an efficient alternative. With Handl.ai, the MFO can handle the increased workload without the need for additional staff. Handl.ai’s cost for processing the same volume is only £216 per month, making scalability not only effortless but also cost-effective, with a cost reduction of 12.5 times compared to the traditional approach.
Conclusion
This high level case study illuminates the transformative potential of Handl.ai. By implementing Handl.ai’s cutting-edge document processing and automation solutions, organizations like the MFO experienced significant cost reductions, streamlined operations, and enhanced scalability. As businesses face the constant challenge of optimising their processes, Handl.ai may become a game-changing solution, poised to to drive operational excellence.
Note: The figures and values in this case study are for illustrative purposes and may vary depending on specific business contexts and scenarios.
Next topic: Using Handl.ai’s ML-powered document processing for paperwork automation
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