The financial services industry is undergoing a seismic digital transformation. At the forefront of this shift is Mohammad Asif Ali, a Technical Lead at PNC Financial Services Group, whose expertise in artificial intelligence (AI), machine learning (ML), and intelligent process automation (IPA) is pioneering a new era of automation and innovation in banking and beyond.
With over a decade of experience building scalable fintech solutions, Ali’s work has contributed to the evolution of underwriting, compliance, and demand deposit account (DDA) automation through innovative research and real-world deployment. His recently published peer-reviewed research has gained attention across both academic and professional circles for proposing new AI-native approaches to risk evaluation and process automation.
Agentic AI: Reinventing the Future of Financial Underwriting
Ali’s 2025 scholarly article “Efficient Underwriting Using Agentic AI” introduces a revolutionary AI-driven framework that uses large language models (LLMs), retrieval-augmented generation (RAG), and robotic process automation to automate the financial underwriting process. These technologies work together to automate the traditionally manual and often inconsistent underwriting process.
“Traditional underwriting methods are often rigid and inconsistent. Agentic AI is built to be adaptive, context-aware, and auditable,” Ali writes in his publication.
This new system significantly reduces human bias and accelerates decision-making by allowing AI agents to autonomously process and evaluate applicant data, compliance rules, and historical patterns. With real-time cognitive feedback loops and machine learning-based document understanding, Agentic AI minimizes errors, speeds up approvals, and ensures consistent risk modeling.
IPA and the Rise of Hyperautomation in Banking
Ali’s earlier work, “Leveraging Robotic Process Automation for Business Optimization (2024)”, laid the groundwork for applying intelligent process automation (IPA) across industries. The research outlines a scalable and secure architecture combining RPA, AI, and ML to improve enterprise agility and customer experience.
Key findings from Ali’s work include:
- 70% faster turnaround for high-volume operations (e.g., account onboarding, loan processing)
- 50% cost savings through automated regulatory workflows
- Enhanced employee productivity and retention by eliminating repetitive tasks
Ali’s philosophy emphasizes human-AI synergy — where intelligent agents assist, rather than replace, decision-makers. This principle is increasingly visible in high-stakes environments like finance and healthcare.
From Research to Real-World Impact
Mr. Ali has spearheaded mission-critical automation initiatives, including:
- Automation of PPP loan processing during the COVID-19 pandemic
- Intelligent Process Automation of PPP Loan Forgiveness for the SBA
- Robotic automation for commercial loan resolution after the Silicon Valley Bank collapse
- Provisional patent filing for Agentic AI underwriting system
These contributions demonstrate his ability to convert theory into scalable enterprise impact. His blend of technical depth and strategic acumen continues to shape digital innovation efforts across the organization’s broader transformation roadmap..
What Makes Agentic AI Unique?
Unlike conventional RPA systems, Agentic AI supports continuous learning, multi-domain integration, and real-time regulatory reasoning. Its architecture is designed for:
- Dynamic environments: interpreting unstructured market, customer, and geopolitical data
- Cross-industry inference: leveraging insights from finance, healthcare, and logistics
- Regulatory intelligence: adhering to evolving financial and privacy laws
Ali envisions intelligent agents that don’t just execute — but reason. This makes Agentic AI a powerful tool for advisory-driven banking models and regulatory-aware automation.
In Conversation with a Visionary in Intelligent Automation and Agentic AI:
How Intelligent Process Automation Optimizes Business Processes?
Most industries depend on various business processes to sustain their operations and productivity, including banking, finance, government, healthcare, retail, and insurance. They rely on intelligent and efficient business processes to process transactions, evaluate loans, and detect and prevent fraud. That is why business process management is expected to reach a value of $15 billion by the end of 2025.
Intelligent process automation (IPA) utilizes the advancements in RPA, AI, and machine learning technologies to optimize complex business processes through automation. It enables digital computer systems to learn, understand, and adapt cognitive characteristics that allow them to make more accurate, data-driven decisions, thereby improving operational efficiency and scalability.
This technology represents the comprehensive digital transformation of the finance industry. These newly optimized processes will simultaneously decrease manual labor and improve customer service. The best part is that the new technology can flawlessly integrate with existing IT systems without hindering operational performance and productivity.
IPA will soon become a necessity for most organizations over the next decade. The first businesses to adopt IPA into their organizations will have a competitive advantage in their respective industries. IPA enables companies to automate routine tasks and end-to-end processes, leading to more employee satisfaction in the workplace. Employees can devote more of their time, energy, and skill set on activities that are more valuable to their companies.
How will these Agentic AI technologies transform traditional banking operations?
Traditional banking operations are heavily reliant on human bankers and officers to supervise them. However, like all human beings, they can make mistakes that could compromise the decision-making processes of loan approvals, creditworthiness, customer service, and regulatory compliance.
Agentic AI systems provide accurate, real-time intelligence based on highly sophisticated predictive models and compliance rules. More personalized options can also be added to the equation to better serve clients’ needs. The result is more efficient, adaptive, and customer-oriented decisions that create a more advisory relationship with clients rather than a merely transactional one.
How is Agentic AI ideal for dynamic environments?
Agentic AI continually learns to optimize its output capabilities. It does not just rely on traditional AI concepts of performing specific tasks in specialized fields, such as image recognition and data analysis. Instead, it can provide real-time contextual understanding of complex concepts and tasks to make good decisions. That is exactly what is needed for the decision-making processes of modern dynamic environments.
For example, most financial systems are considerably complex and nonlinear. In other words, they are constantly bombarded with massive amounts of new, unstructured data about various aspects of their organizations or financial markets. This data may involve information regarding the latest market fluctuations, consumer trends, geopolitical developments, and cyber threats.
Financial professionals are expected to make high-stakes decisions every second to serve their organizations and customers better. Since that is impossible for humans to do alone, they need an advanced technology like Agentic AI to do it for them. Agentic AI is a robotic financial agent that can decipher massive amounts of data from various categories and make informed decisions based on them, even if the data is not entirely complete.
What is the benefit of Agentic AI’s cross-disciplinary integration?
Cross-disciplinary integration is at the heart of the Agentic AI technology. Organizations no longer need to rely on single AI systems designed for a specific industry. Now, they can leverage the cross-disciplinary integration associated with Agentic AI to operate across multiple domains, including finance, education, law, healthcare, and logistics.
Imagine how much better the decision-making will be when the AI system can take domain-specific knowledge from one industry and apply it to the decision-making process for other industries where it may be relevant. For example, a financial institution could utilize Agentic AI to gain a deeper understanding of healthcare data when evaluating the risks associated with a commercial loan for a medical supply company. The AI will also review the regulatory concepts of the banking and healthcare industries to create more robust and collaborative risk assessments.
Learn More
Ali’s pioneering work spans scholarly research, applied innovation, and large-scale financial systems modernization. For readers seeking a deeper understanding of his publications and ongoing contributions to the field of intelligent automation:
- http://article.sapub.org/10.5923.j.se.20251201.01.html
- http://article.sapub.org/10.5923.j.se.20241102.03.html
- LinkedIn Profile: https://www.linkedin.com/in/mohammad-asif-ali-68b13b19/
This article was published by TechBullion editorial staff to highlight significant advancements in intelligent automation and Agentic AI.
