Through our application of deep technical Robotics Process Automation (RPA) expertise and intense focus in the banking industry, we delivered a holistic, fully automated and high accuracy due diligence solution that moved Mashreq Bank forward, fast.
Modernizing its existing due diligence process allowed the bank to better understand its customers better and manage risks prudently. The bank needed a holistic, data-driven, and standardized due diligence mechanism that automated core processes.
Our robotics technology was used to automate the existing due diligence mechanism of the bank’s factoring customer onboarding process. This resulted in a 78% increase in its throughput of completing the due diligence process for onboarding new customers as well as periodic review of existing customers.
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In an increasingly competitive business landscape, companies need to tap disparate sources of data to conduct informed investigations of debtors. Unfortunately, the time available to perform such analysis is short, and the sensitivity of information handled is high. Given this backdrop, Mashreq wanted to overhaul its manually intensive due diligence mechanism to retain its competitive advantage in the region. The project primarily aimed at eradicating data discrepancies in due diligence scores by implementing a holistic, data-driven, and standardized due diligence process. This will support agents not only in data collection and analysis but also to make faster, insight-backed calls.
So how did a bank of this scale leverage technology to streamline operations and achieve process accuracy?
By using a collaborative and consultative approach to spearhead several key transformations within the bank, we mixed smart technology lab innovations with unique sandbox environments and a team of experts to build the right solution. One that addresses the bank’s business challenge and will capitalize on present and future market opportunities.
To resolve the problem of unstructured data and non-standardized search patterns, we used bots powered by RPA and Machine Learning (ML) algorithms to seamlessly perform complex search patterns across systems to capture debtor information. To accelerate transactional throughput, we processed all debtor information through Kastle, the bank’s factoring product management software.
To do away with the effort-intensive process of manual data collection and analysis, we also integrated the solution with Oracle FLEXCUBE, the bank’s core banking system. This helped the client to automatically and instantly fetch and screen debtors’ financial history. Alongside this, the computation of due diligence scores was automated with the intention to expedite the decision-making process.
We designed and implemented a technology transformation roadmap for Mashreq across its core processes, enabling the bank to:
- Reduce turnaround time for debtor data evaluation by 50%
- Increase daily data processing volume by 78%
- Enhanced process accuracy by 10% with an ML-enabled bot