Advancing SME finance through same-day lending decisions | HCLTech

Advancing SME finance through same-day lending decisions

HCLTech delivered Pega-enabled, superior loan origination solution
5 min read
5 min read

Our client is one of the leading banks in the Asia-Pacific region. They introduced several beneficial initiatives for small businesses, such as revamped lending systems, instant lending decisions and waiver of business banking fees/charges. They roped in HCLTech as a strategic partner for their lending transformation program that would foolproof the credit appraisal system and make it auditable in line with the Australian Prudential Regulation Authority (APRA) stress test requirements.

The Challenge

Legacy processes creating data quality and manual processing challenges

Our client faced a regulatory mandate to automate the entire credit workflow to maintain their Institutional Review Board (IRB) accreditation. However, the reality on the ground presented significant challenges. During credit appraisal, the bank encountered delays in decision-making stemming from a lack of integrated information. Insufficient high-quality data restricted the scope for data-driven credit decisions, leaving the bank without a single source of truth for reporting and analytics. Additionally, the existing manual loan process was prone to human error, while user-dependent Loss Given Default (LGD)/ Exposure at default (EAD) calculations posed regulatory challenges due to a lack of auditability, thereby creating operational risks.

The Challenge

The Objective

Deploying a future-proof banking system

Compliance mandates necessitated our client's transition to digital front-office and back-office processes. The primary objective was to enable easy access to electronic signing for policyholders. Additionally, automating the generation of agent commission statements was crucial. The manual process involved significant complexity and effort, requiring 10-12 hours daily across six different processes, leading to frequent human errors. Collaborating with us, our client aimed to achieve these goals and transition to a next-generation business platform.

Advancing SME finance through same-day lending decisions

The Solution

Implementing next-gen banking solution

We developed a scalable Pega solution on the with two primary components:

  • The first component involved implementing robust Pega workflow solutions to redefine the target state architecture for LGD calculation, replacing End User Computer application tools (EUC tools) and manual calculations
  • Utilizing the Pega Decision Engine, the solution fully automated secured lending margin (SLM) and LGD calculation processes, eliminating the potential for human error
  • The Pega platform's intricate calculation logic enabled LGD calculation with over 80 business rules and scenarios, with real-time integration retrieving facility, Probability of Default (PD) and counterparty details
  • The solution seamlessly integrated customers, facilities, collateral and calculation data to determine LGD from BRE (Business Rules Engine)
  • Automation extended to collateral allocation rules and enhanced collateral data quality through the Collateral Management System (CMS)
  • Reporting and analytics processes were automated, reducing reliance on CSV files for storage and manual report generation
  • Process automation improved data validation and system rule adherence for LGD accuracy and reporting
The Solution
  • Business rule automation demonstrated lineage of non-retail LGD values and established a common rules engine across institutional, corporate and private banking divisions for LGD calculation
  • Automation also streamlined LGD and credit exposure policy calculation processes
  • The Pega-based LGD UI application, tailored for institutional banking and market business unit (IB&M), centralized customers, collaterals, facilities and ratings, enhancing collateral mapping through rest APIs to elevate data quality
  • This framework upheld event-driven decision capabilities while retaining manual LGD value overrides
  • Data-focused enhancements included automating data feeds for credit notes and augmenting data availability in the analytics platform for model validation and reporting

The Impact

Gaining from process efficiency and error reduction

  • HCLTech implemented an integrated platform, creating a unified view of customers, facilities, PD ratings, LGD and EAD values for loan origination
  • Automation of LGD calculation and reporting significantly reduced operational risks and facilitated regulatory compliance
  • Process efficiency was enhanced as rekeying and manual data entry were significantly reduced through automation
  • LGD assessments and reporting also benefited from automation, resulting in a marked reduction in rework and manual adjustments
  • The introduction of automated interaction between LGD-related systems drove wholesale enhancements to process efficiency, fostering adoption across the organization
The Challenge