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FinTech

A FinTech ISV used AI-powered code intelligence to map multi-level dependencies across its legacy PL/I core banking platform and support its modernization.

  • Legacy Modernization
  • Code Reverse Engineering

Results

FinTech ISV
lines of PL/I code analyzed
>10M
less manual impact-analysis effort
up to 70%

The story

  1. Challenges

    01
    • Legacy PL/I-based core banking systems (>10M lines of code) lacked visibility into multi-level dependencies.
    • Complex codebase with dead code and performance bottlenecks.
  2. Solution

    02
    • Built an AI-powered Code Intelligence Platform with multi-level dependency mapping.
    • Supports 8 complex AI-driven features to aid modernization.
  3. AI Impact

    03
    • Transformed static legacy code into a searchable semantic knowledge graph.
    • Provides a forensic view into code, easing the operational cost of maintenance.
  4. Business Impact

    04
    • Reduced manual impact-analysis effort by up to 70%.
    • Lowered regression defects and production risk.

Built with

Technologies
  • PL/I
  • Semantic knowledge graph

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Next step

See how multi-level dependency mapping and change-impact analysis with CortexIQ would work on your PL/I, COBOL or VB6 code.

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