The data-driven CFO: Revolutionising finance with process intelligence

Amidst economic headwinds, CFOs are grappling with a familiar trio of foes: creaking legacy systems, fragmented data ecosystems, and a dearth of analytical talent. Yet, as volatility demands sharper foresight, forward-thinking CFOs are pivoting from firefighting to reinvention. The prize? Transforming raw data into decisive action—and here, process intelligence is proving transformative.

By embedding AI and automation into financial workflows, leaders are untangling inefficiencies that have long throttled agility. Consider the humble invoice: a process riddled with hidden complexities, from payment timing to duplicate errors. When optimised, it becomes a lever for cashflow precision; when neglected, a drag on productivity. Process intelligence illuminates these nuances, enabling real-time analytics, automated controls, and leaner operations. The result? Faster decisions, cost savings, and resilience—critical in uncertain times.

According to a recent McKinsey Survey, eighty percent of executives now view process optimisation as pivotal to value creation, and rightly so. Streamlined workflows not only boost margins and revenue but also free teams from mundane tasks, redirecting talent toward strategic imperatives. For CFOs, this shift is existential: shedding the bean-counter mantle to emerge as architects of enterprise-wide resilience. In an era of continuous disruption, process intelligence isn’t just a tool—it’s the new CFO playbook.

At the recent CFO100 Conference in Mumbai, we dissected how process intelligence is rewriting the rules of corporate survival in a session in partnership with Celonis. We were joined by three industry stalwarts, Mandar Dixit, Financial Controller – Auto Sector, Mahindra Group; Yogesh Udhoji, CFO, Muthoot Housing Finance Company; and Kaushik Mitra, Vice President – India Business, Celonis. The discussion was expertly moderated by our Director & Chief Operating Officer, Ms. Seema Menon.

The automotive vanguard: From assembly lines to AI

Mandar epitomised the proactive ethos of India’s automotive sector, which faces a dual mandate: transitioning to electric vehicles (EVs) while future-proofing finance operations. “We’re automating the mundane to graduate toward predictive decision-making,” Dixit explained during the panel. The firm’s AI-driven warranty management and EV battery analytics underscored a broader shift—integrating “digital twins” of processes to simulate outcomes, from supply chain snarls to demand fluctuations.

Central to this was the Mahindra Data Platform, a unified architecture enabling real-time data access across 100+ global entities. “Data on demand isn’t a luxury; it’s hygiene,” Dixit noted. Such agility, he argued, was critical as the sector navigates tariff wars and ICE-to-EV pivots.

BFSI’s catch-up game: Customer-centricity over ROI

In contrast, Yogesh Udhoji admitted the BFSI sector’s tech adoption remained reactive. “We’re playing catch-up, not driving innovation,” he conceded, citing manual processes and promoter hesitancy. Yet pressure had mounted, he noted, as customers demanded instant loan disbursements and seamless service. The solution? Prioritise customer experience over rigid ROI metrics—a “founder’s mentality” gamble to stay relevant.

Kaushik Mitra highlighted a stark divide: while fintechs deploy AI-driven credit models, traditional banks often lack “process intelligence layers” to unify disparate systems. “Without a digital twin of workflows, CFOs can’t diagnose inefficiencies—or leverage AI meaningfully,” he argued.

Process intelligence: The X-ray for corporate ills

Process intelligence, Mitra elaborated, acts as an organisational X-ray. By mapping processes like procure-to-pay or order-to-cash, firms create living models to pinpoint bottlenecks. He cited a global beverage company that had slashed order cancellations from 30% to 4% by tracing root causes to inventory gaps. Similarly, a hotel chain used process analytics to mitigate COVID-era revenue crashes, rerouting resources in days, not months.

The synergy with AI is transformative. “AI lacks context, but paired with process logic, it’s revolutionary,” Mitra said. For example, embedding AI in payroll systems at a million-employee e-commerce firm had reduced query resolution times from weeks to minutes, boosting morale and retention.

Talent wars: Tech as a recruitment arsenal

Dixit raised a critical point: tech adoption isn’t just operational—it’s existential for talent. “A top-tier MBA grad won’t stay if they’re stuck reconciling ledgers,” he said. Gen Z demands tools mirroring consumer tech—QR codes over business cards, chatbots over spreadsheets. Firms lagging here, he warned, face a “brain drain” to agile competitors.

Measuring success beyond the balance sheet

ROI remained contentious. While Dixit advocated a “portfolio approach” (backing some loss-leading pilots to enable innovation), Mitra stressed quantifiable wins: carbon footprint reductions via smarter logistics, or error-free audits through blockchain. Yet softer metrics—employee satisfaction, customer loyalty—were equally vital. “The board will invest if they see value, even if it’s not immediately monetary,” Mitra asserted.

The path ahead

The question isn’t whether to adopt process intelligence, but how swiftly. In a world where disruptions are the norm, CFOs must champion tech not as a cost centre, but as the bedrock of resilience—and the price of admission for tomorrow’s talent.

The message was clear: In the calculus of modern finance, process intelligence isn’t a leap of faith—it’s the only viable path forward.