The foundations of DevOps enable rapid software development and deployment by a variety of organizations. Continuous integration, continuous delivery, infrastructure as code, and configuration as code are now mature concepts. However, DevOps techniques remain largely unexplored in the context of cloud-native financial automation. By investigating financial automation using these techniques, a framework for integrating financial automation throughout the BANK Financial Evolution through Reinvention program, especially into credit risk-related workstreams, is derived. To support such integration, continuous delivery techniques for regulated environments, leveraging the cloud-native architecture of the Program’s ecosystem, are presented. Cloud-native architectural patterns related to supporting automated financial processes are also proposed, making use of the concepts of microservices, service meshes, serverless computing, and data mesh. Furthermore, Agentic Artificial Intelligence (Agentic AI) concepts are applied to financial automation, especially in relation to agentic roles and the levels of autonomy of Agentic AI. Finally, an exploration of generative intelligence’s role in supporting and facilitating the work of human agents who undertake financial automation is undertaken by considering the automation of a variety of workflows including report generation, the creation and maintenance of compliance documentation, and providing audit trails to help support compliance and validation activities.
Emily A. Carter· International Journal of Mod...· 0 citations
Enterprises are transforming to embrace Artificial Intelligence (AI) and accelerate business outcomes. The application of AI technology needs to occur in a controlled environment, with appropriate risk management in place to ensure longevity of the systems. Hence the desired outcome is to adopt an AI governance framework mapped to an enterprise service delivery solution that supports the detection and remediation of trust, safety, security and compliance risks relating to the AI operations across its lifecycle, as well as in the data used to train, develop and run the AI models. Therewith, a Cloud-Native, Security-centric and Compliant AI-Driven Automation Framework for ServiceNow is articulated. The framework allows for various AI services to be developed, operated and maintained safely, securely and in a controlled responsive manner aligned to AI Governance principles throughout the lifecycle. The framework operates within a Cloud-Native model with all applications comprising SaaS/IaaS/PaaS being developed and deployed under the principles of zero-trust with least-privilege identity and access management considerations. The completed framework provides the foundation for continuously improving the Security-Centric and Compliance controls.
Emily A. Carter· American International Journ...· 0 citations
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