How agentic AI is rewiring BFSI workflows

Time of India

2 days ago

The use of Artificial Intelligence (AI) in the financial sector has been growing significantly over the past 24 months, but as we move forward, the applications are moving towards more automated, intuitive enablement across the board. After Generative AI, Agentic AI is leading this revolution with the ability to make autonomous decisions and carry out complex tasks without constant human guidance. Unlike traditional AI which reacts to human- fed input, agentic AI decides autonomously what action to take, plans multi-step workflows, and adapts in real time.Why Agentic AI Matters: The shift we discussed is a fundamental upgrade to BFSI's operational core. Traditional AI has excelled at analyzing data or identifying patterns. Agentic AI, however, takes a fundamentally different approach. It generates collections of independent AI agents that collaborate through sophisticated reasoning and planning mechanisms to resolve multi-step problems, with large language models serving as their "decision-makers". In simple words it is designed to work more like humans by handling tasks independently.
Consider a compliance check scenario. Where a traditional system may trigger a transaction to be reviewed by a person, an Agentic AI system could not only initiate it but separately gather additional context from adjacent accounts and external data sources, analyze the risk in real-time, and clear the transaction automatically or escalate it with a complete summary. All without waiting for a human to initiate the manual check that follows.
Agentic AI in Action:
Agentic AI has a deep impact and has the potential to drive change across an extensive range of BFSI processes, from customer-facing processes to sophisticated back-office procedures. The following examples reflect how this technology is rewiring processes in some of the most important areas:
Streamlining Lending Decisions: Agentic AI is beginning to fundamentally accelerate the loan application journey. Lengthy manual reviews and sequential checks keep applicants waiting. Emerging Agentic systems are showing the capacity to autonomously orchestrate the complex process of gathering data from diverse sources, performing rapid, intelligent analysis, and making decisions or recommendations. This rewires lending from a bottlenecked process into a swift and significantly faster experience for both the institution and the customer.
Dynamic Underwriting: Particularly relevant in the insurance sector, Agentic AI is poised to transform underwriting from a static, point-in-time assessment to a dynamic continuous process. These systems autonomously gather and analyze real-time data, beyond traditional application forms allowing for more accurate risk assessment throughout the policy lifecycle. This leads to faster policy issuance, more precise pricing, and the capability to offer highly personalized coverage that can adapt to changing circumstances, fundamentally reshaping how risk is evaluated and managed.
Enhancing
Fraud Detection
and Security: Agentic AI is driving a shift in fraud detection from reactive to proactive. By learning from real-time transactional data and behavioral trends in real time, such systems can identify minor inconsistencies and anticipate changing threats. After detection, they can trigger immediate, multi-step security actions like blocking suspicious transactions or freezing accounts faster than human intervention can, significantly reducing fraud losses.
The Road Ahead: Risks, Ethics, and Governance:
As Agentic AI becomes deeply embedded in core BFSI workflows, its inherent risks and ethical implications need to be addressed. Autonomous systems power poses challenges such as preventing algorithmic bias that could lead to unfair outcomes. Second, ensuring transparency and accountability for decisions made by Agentic AI, because it can be difficult to understand exactly why AI made a specific decision- this is known as the 'black box issue'. It is important for regulatory rules and customer trust. Successfully charting this course requires robust governance, including clear internal policies, continuous monitoring, and essential human oversight, all supported by proactive regulatory frameworks.
To conclude, this technology holds significant promise for advancing financial inclusion, particularly in emerging economies. By enabling FinTech and traditional banking infrastructure that face limitations. By providing cost-effective means for the financial institutes to reach previously underserved communities, Agentic AI can open doors to essential financial services, pointing towards a more inclusive and digitally advanced future for the global financial system.