Reducing loan data errors and improving operational efficiency

Client:

The client is a major UK-based bank. 

Challenge:

The client’s loan operations team was overwhelmed by inaccurate loan agreement data in the bank’s mainframe system. These errors, stemming from data inconsistencies caused by team attrition, were affecting the accuracy of loan processing and posing significant financial risk.  

The loan agreements, which dictated the terms and conditions of each loan, fed crucial data for all loan lifecycle events and cash flows. Even minor errors could lead to substantial financial losses, and the team lacked the capacity to manage the large volume of errors. A solution was urgently needed to clean up the data and prevent further operational delays. 

Solution:

eClerx collaborated with the client to conduct a full-scale data quality check. The approach bypassed the existing data in the mainframe by recreating the information directly from the original loan agreements. eClerx implemented its proprietary DocIntel platform, combined with its loan subject matter expertise, to accurately capture data and identify discrepancies.  

First, eClerx established a secure environment for the project, ensuring all data transfers were secure and compliant with the bank’s requirements. Next, the DocIntel platform was deployed to automate the data capture process from the loan agreements, which was then followed by manual enrichment to ensure that any gaps left by automation were accurately filled in. 

To ensure alignment with the bank’s internal processes, eClerx collaborated extensively with the client’s operations team to create a detailed data capture rulebook that accounted for all possible exceptions. A three-layer review process was implemented to guarantee data accuracy, including a final review by subject matter experts to ensure that the captured data adhered to the agreed-upon rules.  

Finally, the newly captured data was reconciled with the bank’s mainframe system, allowing the team to identify and rectify discrepancies between the two data sets. 

Impact:

The results of the data quality check were transformative: 

• Reviewed 4,500 loans, capturing 140 data points per loan. 

• Achieved a 99.99% accuracy rate in data capture. 

• Identified 9,500 discrepancies, but by filtering out 98% of potential errors. 

• eClerx reduced the workload for the client’s team to only 2% of the data needing manual review. 

The data cleansing exercise provided the client with reliable, accurate data, allowing them to confidently manage their loan operations. The streamlined process significantly reduced the risk of financial instability and operational delays, enabling the client’s team to focus on resolving a manageable number of discrepancies.  

The collaboration between eClerx and the client demonstrated the power of combining advanced technology with deep domain expertise to deliver efficient, impactful solutions.