Implementing an Effective Composable Architecture for a Retail Lender

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February 2024

3 min read
Implementing an Effective Composable Architecture for a Retail Lender

Problem Statement

Context

Our client is a well-known UK brand that amongst a few businesses also provide retail lending products including personal and car loans. Our client faced challenges with their outdated legacy application. These challenges hindered their growth, innovation, and ability to offer a differentiated customer experience. These challenges meant that they were unable to meet their business objectives of customer acquisition and achieving straight-though lending decision processes.

Challenges
  • Our client intended to offer affordable, flexible, simple lending products to their customers, but felt technology was a hindrance in achieving their growth targets.
  • There was too much friction in the end-end journey with too many manual interventions.
  • Technology to support making incremental changes to the proposition based on customer feedback
  • Ability to innovate and facilitate ‘plug-and-play' architecture

Solution

DLT Apps were involved in defining the target architecture driven with Domain Driven Design that facilitated:

1An architecture that was loosely coupled based on composable architecture to enable our client switch retail lending service providers as required
2Insource loan application decisions within the business to enable consistency and transparency
3Enable reliable releases of application code to facilitate innovation and listening to customer feedback
4Implement a leading cloud infrastructure architecture with necessary security controls in line with cloud architecture best practices

End-to-End Automation

  • Modular Integration: Decomposed the lending process into individual domains, such as application quotes, lending, credit checks, and loan disbursal, to facilitate end-to-end automation.
  • Dynamic Workflows: Employed adaptable workflows that automatically routed applications based on predefined criteria that enabled minimising manual interventions.
  • Real-time Analytics: Integrated real-time analytics modules to provide insights into loan processing times, approval rates, and other critical metrics, allowing for continuous process refinement.

Differentiated User Interface (UI)

  • Adaptable UI Components: Leveraged composablearchitecture's ability to swiftly integrate new UI components, facilitating a tailored user experience based on customer feedback and market trends.
  • Responsive Design: Ensured the interface adapted seamlessly across devices, providing a consistent experience for both mobile and desktop users.
  • Personalised User Journey: Integrated AI-driven modules that analysed user behaviour to present personalised loan offers and recommendations.

Enhanced Retail Lending KPIs

  • Rapid Iteration: The modular nature allowed for quick implementation of changes, ensuring that the business could adapt and refine strategies based on real-time KPI analysis.
  • Data-Driven Decisioning: Utilised AI and machine learning components to refine loan underwriting processes, resulting in better risk assessment and increased loan approval rates.
  • Customer Experience Modules: Incorporated feedback and support modules, directly improving customer satisfaction KPIs by ensuring grievances were promptly addressed and feedback was acted upon.

Technologies

aws
AWSsecurityHub
Kubernetes
Java
Go
Gitlab
AmazonDynamoDB
NewRelic
KinesisFirehose
React
Figma
Atlassian

Impact

  1. Embracing modern composable architecture transformed our client within the retail lending business to enable an architecture that can respond to customer needs.
  2. By addressing the core challenges that they faced, the new system enabled operational efficiency, providing a superior user experience, and driving significant growth in key performance metrics.
  3. Our strategy not only bolstered current business outcomes but positioned the company for sustained future growth in the competitive retail lending landscape.

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