Case Study: a leading financial services provider achieves faster, more accurate audits with KANINI predictive analytics solution

Transformed data analytics process to build highly efficient predictive models based on historical relationships between multiple data sets

Kanini worked with a leading financial services provider that needed to transform its data analytics process to build efficient predictive models. The customer's legacy system was too time-consuming and struggled to perform the substantive analytical procedures required to reliably identify outliers and potential misstatements in their records, which was impacting audit accuracy.

The solution implemented by Kanini was a custom analytics application that used regression analysis to model relationships between multiple historical data sets. The tool generated various analytical reports and visualizations, simplifying complex techniques to detect unusual fluctuations and develop statistical projections. As a result, Kanini's solution reduced the time taken for audits by 30% and significantly improved the accuracy of the audit results.