Application Modernization with GenAI: SAS to Python

Management Summary

A leading global insurance group modernized a core SAS 9.4 application in its accounting department. HMS developed an AWS-based target architecture and implemented the migration from SAS to Python. A GenAI-powered approach supported the semi-automated code migration.

Project summary

#finance

Weltweit führender Versicherungskonzern

Branche: Versicherung
Projektstart: 01/2023
Schwerpunkt: Modernisierung & Migration
Use Case: Legacy System Modernization

Projektziel

Modernisierung einer zentralen Rechnungswesen-Anwendung und Reduktion des bestehenden SAS-Footprints

Wichtigste Kernfunktionen

Assessment- und Designphase für Zielarchitektur und Migrationsvorgehen
AWS-basierte Modernisierung mit Angular-Frontend und Python-Integration
Prüfung einer teilautomatisierten SAS-zu-Python-Migration mit GenAI

Tech Stack

sas python gpt models angular infrastructure as code

In this project, we were able to demonstrate that GenAI effectively supports the SAS-to-Python migration when translation, testing, and quality assurance work together consistently.
Roland Mannshardt
Senior Project Lead

The Starting Point

The existing SAS application landscape had grown over the years and supported core accounting processes. As part of the IT strategy, the on-premises SAS 9.4 technology was to be phased out gradually. For the first phase of modernization, a central application was selected to test the feasibility, target architecture, and transferability of the approach. The challenge was to integrate business requirements, the existing codebase, cloud architecture, and regulatory requirements from the financial sector into a controlled migration process.

The HMS Solution

Modernizing the SAS Application on AWS

HMS worked with the customer’s IT department and business unit to develop the target vision for the modernization and carried out the migration within the defined scope.

Assessment and Design

To begin with, HMS analyzed the existing application, the technical framework, and the requirements for the target architecture. This phase formed the basis for migration planning, architectural decisions, and the implementation framework.

Cloud-Based Target Architecture

The new architecture utilized the enterprise-wide cloud platform based on AWS. Infrastructure as Code supported reproducible deployment and ensured that the implementation was compatible with existing IT requirements.

Front-End and Python Integration

Angular was used for the web front end. Python was integrated as a target technology to ensure that former SAS users could continue to work effectively in the new environment.

GenAI-Assisted Migration

HMS investigated the semi-automated migration of customer-specific SAS code to Python. The approach combined GenAI support with subject-matter review and technical quality assurance.

Customer Benefits

GenAI-powered SAS-to-Python migration on AWS

The semi-automated conversion of SAS code to Python reduced recurring manual work. Business validation and technical quality assurance remained integral parts of the migration process.

More efficient

Migration with Less Manual Effort

SAS code is converted to Python using a semi-automated process. This reduces repetitive migration work and eases the burden on the teams involved.

Safer

BaFin requirements have been incorporated into the target architecture

The new AWS architecture is designed so that regulatory requirements are incorporated into the technical implementation from the very beginning.

More maintainable

Lower Risk Thanks to a Modern Target Environment

The new AWS architecture was designed so that regulatory requirements were incorporated into the technical implementation from the very beginning.

Outstanding Approach to SAS Migration

The HMS approach to semi-automated SAS migration was recognized in the group-wide GenAI competition. This underscores the practical value of the approach: GenAI supports migration in areas where recurring code transfers would otherwise require a significant amount of manual work.

1st Place in the Group-Wide GenAI Competition

Our Strengths, Your Benefits

Migration in Regulated BI Environments

HMS combines architecture, software engineering, and an understanding of regulated enterprise environments. In this project, this combination was evident in the planning, testing, and implementation of a controlled modernization.

What You Can Expect from HMS

Architecture and implementation from a single source
: HMS supported the project from assessment and design through to implementation.
Interoperability with existing IT requirements
: The target architecture was developed based on the company-wide cloud platform.
Pragmatic use of GenAI:
Code migration was not automated in isolation, but rather embedded within a verifiable migration process.

Karsten Wohlgefahrt

Principal Sales Manager

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Next Steps and Further Study

Agent-Based Migration with Code2X

Learn how Code2X combines code analysis, architectural guidelines, agent workflows, and automated validation into a controlled transformation process.

Learn more about Code2X