Accelerating Loan Approvals with a Smarter Approach
Overview
A vision for smarter consumer lending
Consumer lending is the backbone of retail banking. However, for one of Europe’s leading banks, the process had become a challenge instead of an enabler. Customers applying for personal loans, overdrafts and cash advances encountered frustrating delays, inconsistent document requirements and high dropout rates.
Behind the scenes, back-office teams struggled with overwhelming manual workloads and rising operational costs made the system unsustainable. The bank recognized the urgency of a transformation. They needed a fast, efficient and frictionless lending process. Partnering with HCLTech, they set out to redefine how customers apply for and receive loans.
The Challenge
Where challenges slowed progress
Our client’s lending process had three major roadblocks that disrupted both customer experience and increased operational inefficiencies:
- Customer drop-offs: Applicants were abandoning their loan applications due to inconsistent and unclear document submission requests, which delayed loan disbursements and created frustration.
- Back-office overload: The bank’s Customer Loyalty Team (CLT) spent excessive time manually reviewing the documents, slowing down approvals and increasing operational bottlenecks.
To turn this around, we needed to automate, optimize and simplify the entire lending process to reduce customer friction and operational inefficiencies.
The Solution
A smarter approach to ending
HCLTech introduced a structured and automated framework to eliminate inefficiencies and improve the end-to-end lending journey.
- Automated loan approvals: By implementing Straight-Through Processing (STP), we eliminated the need for customers to upload documents manually, significantly reducing dropout rates. Integrations with external data sources automatically retrieved the required information, ensuring faster loan decisions.
- Optimized back-office operations: Manual workloads were streamlined, allowing the CLT to focus on high-value tasks like offer processing and customer engagement instead of repetitive document validation. Faster approvals translated into improved customer satisfaction.
- Cost-efficient process architecture: We restructured the bank’s case management system, introducing a parent-child case relationship in Pega. This simplified case handling, reduced redundancy and cut costs significantly.
The Impact
Results that speak for themselves
The transformation led to a significant improvement in both operational efficiency and customer satisfaction:
- 67% of loans processed automatically: Before implementation, only 26% of retail loan applications were processed via STP. With automation in place, this surged to 67%, creating a faster and more reliable lending experience.
- 50% reduction in case volume: Our new case management approach reduced Pega cases by 50% within a month of going live, leading to operational savings of €150,000 per quarter.
The bank now operates with a more efficient, scalable and customer-friendly lending system, setting a new benchmark in the industry.
Beyond the Numbers
This transformation has laid the foundation for a more agile and efficient consumer lending model. By eliminating manual interventions and optimizing workflows, the bank has not only accelerated loan approvals but has also increased customer satisfaction and confidence in the process. With automation driving efficiencies, the bank has also created a scalable framework capable of supporting future growth and focusing on high-impact activities like personalized customer engagement and the development of new financial products.
Celebrating Success
At HCLTech, we take pride in driving change that delivers real business value. By combining intelligent automation, process optimization and deep industry expertise, we helped our client achieve a faster, smarter and more cost-effective lending model. The journey doesn’t end here—we turned complexity into simplicity and created a lending experience that works smarter, faster and better.
