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Rolling Out Policy Changes? Software Platform Anatomy Ensures Smooth Updates Across Services

Updated: Jun 24

Category: Rules & Motivations in Flux


Series Title:"Rethinking Requirements: How the ICMG Enterprise Anatomy Model Makes Lending Systems Change-Ready."


Perspectives Covered: Strategy, Business Process, System, Component Specification, Implementation, Operations


Key Variables Impacted: Rule, Data, Function, Event, Network



The Challenge of Updating Prepayment Policies

Prepayment policies in retail lending play a crucial role in balancing customer flexibility with financial stability. Changes to these policies can arise due to regulatory updates, strategic shifts, or market demands. However, implementing prepayment rule changes in real time without disrupting the system is a significant challenge.


Consider a scenario where the finance team decides to introduce a new prepayment penalty structure based on loan tenure and amount. While the change might seem straightforward, it often triggers cascading issues across multiple systems:

  • Inconsistent prepayment penalty calculations across channels

  • Customer-facing interfaces showing outdated prepayment rules

  • Disconnected updates between backend processing and front-end display

  • Compliance reporting reflecting outdated or inaccurate penalty data

  • Increased manual intervention to correct discrepancies


These issues arise because conventional SDLC methods focus on isolated code updates rather than holistic system alignment. The ICMG Enterprise Anatomy Model (Project Edition) offers a structured, multi-perspective approach to ensure seamless prepayment policy updates without causing disruption.


Why Conventional SDLC Approaches Fail

Common Problems:

  1. Hard-coded prepayment rules scattered across multiple systems

  2. UI elements not updated in sync with backend changes

  3. Fragmented data updates leading to inconsistent policy enforcement

  4. Manual overrides to correct discrepancies

  5. Compliance reports reflecting outdated or incorrect data


Root Causes:

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