As finance moves beyond compliance toward real-time decision-making, organizations are rethinking how the function creates business value.

Nikhil Parambath believes finance's biggest transformation is its shift from reporting the past to helping businesses decide what comes next.

Nikhil Parambath, Regional VP Asia at BlackLine, has spent nearly three decades helping organizations across Asia accelerate digital transformation through enterprise technology. With leadership experience spanning Oracle, Salesforce, and BlackLine, he has worked closely with CFOs and finance leaders to modernize financial operations while balancing governance, trust, and business agility.

In an exclusive conversation with Thiruamuthan, Correspondent at Finance Outlook India Magazine, Nikhil shares how finance is shifting from a backward-looking reporting function to a forward-looking business partner. He discusses the growing role of AI and automation, the importance of trusted data, the impact of regulations such as GST and e-invoicing, and why future-ready finance teams must combine technology, governance, and human leadership to drive sustainable business value.

Explore the full conversation below for more insights on finance transformation and AI.

How have you seen the role of finance evolve from a compliance-driven function to a strategic growth enabler within organizations over the years?

What I see right now is actually a very fundamental shift in the finance function. Earlier, finance was largely seen as a scorekeeper — focused on historical compliance, historical data, and working off that data. I would say it was almost like looking in the rear-view mirror to move forward. The function was largely backward-looking, helping the organization understand what had already happened.

Today, the expectation is very different. Finance is expected to be a strategic co-pilot and a business process orchestrator — someone who can predict and mitigate risks before they impact the business.  So the shift has been from simply reporting the past to anticipating what is ahead and proactively helping the business navigate it.

At the same time, there is a practical challenge. You cannot meet these strategic expectations if your most qualified finance professionals are still buried in manual transactional work, especially the traditional month-end close. Finance naturally moves from one reporting period to the next, and if teams spend most of their energy on repetitive processes, they have very little time left for strategic thinking.

What I see successful CFOs doing today is recognizing that technology is the enabler for this forward-looking role. It is no longer just an IT project; it becomes part of the core operating model of the finance function. They typically start by solving data fragmentation challenges. Then they move from manual processes to automation, with the long-term goal of enabling more real-time and continuous finance operations.

When high-volume, repetitive tasks are automated, finance teams gain time to focus on what truly matters: strategic analysis, risk mitigation, and providing commercial insights that help the organization grow while managing risk more proactively.

So for me,

the real evolution is this: finance is no longer only about explaining what happened. It is increasingly about helping the business decide what to do next.

In the Indian market, how do evolving regulations like GST and e-invoicing impact the pace at which CFOs transition to more strategic, value-driven roles?

Another way to look at these initiatives has obviously been driven by a regulatory and government perspective. But while regulations often look like a challenge, I actually see them as a powerful catalyst for modernization.

We've seen this happen repeatedly in India, where government policies have accelerated large-scale transformation. Take UPI, for example. It completely changed the way payments work in the country and pushed the entire ecosystem towards modernization. I see GST and e-invoicing in a very similar way.

Earlier, finance teams had the luxury of looking back, reconciling data at the end of the month, and then deciding how payments needed to be processed. That is no longer a luxury. With e-invoicing and the evolving GST mandates, organizations have to operate as close to real time as possible.

As a result, reconciliation is no longer a month-end exercise; it becomes a continuous, day-to-day activity.

That shift forces a much bigger change within organizations. To keep pace with these regulations, companies have to break down existing silos. You may have invoicing data in one system, collections data in another, and reconciliation happening somewhere else. While they may sometimes sit within the same platform, in my experience, especially in India, they are often spread across multiple systems.

To meet today's regulatory expectations, organizations need a unified, real-time view of their financial data. And that's where I think these mandates have had the biggest impact. Compliance is accelerating the need for connected data, standardized processes, and real-time visibility across finance.

What I see among high-performing finance teams including many of the customers we work with at BlackLine, is that they're using these regulations as an opportunity rather than an obligation. They're automating routine processes and turning compliance from a bottleneck into an enabler of a more integrated, lower-risk, and continuous financial close.

So, for me,

the real value of these regulations isn't just better compliance. It's that they've accelerated the modernization of the finance function in a way that might otherwise have taken years.

What are the most common challenges CFOs face when attempting to modernize finance operations without disrupting core compliance frameworks?

What really holds CFOs back, I think it comes down to navigating the tension between speed and control.

The finance function has always been the custodian of an organization's numbers. Those numbers are scrutinized by regulators, internal and external stakeholders, investors, and the board. So maintaining control has always been non-negotiable. Traditionally, that meant double-checking and even triple-checking information to ensure the numbers were accurate and fully validated.

The challenge is that every additional layer of validation comes at the cost of speed.

So CFOs are constantly balancing two priorities. They want finance to move faster, but they don't want to compromise on control. One of the most common concerns we hear from CFOs at BlackLine is, "If I accelerate my processes, will I lose auditability? Will I introduce more risk in the pursuit of speed?"

When you strip away all the complexity, I think the challenge comes down to one very fundamental question: How do I modernize finance without breaking the trust I've spent years building?

Finance has earned that trust over decades by producing reliable, accurate, and auditable numbers. Given this, when new technologies like AI enter the conversation, it isn't really about adopting AI itself. It's about adopting it in a way that preserves that trust.

That's where I believe

the concept of trusted, auditable AI becomes critical. The objective isn't simply to introduce AI into finance. It's to ensure that the AI can be trusted, that its decisions are explainable, and that it isn't operating as a black box.

Eventually, finance needs automation that understands accounting principles, can identify exceptions, and works within clearly governed boundaries. Unlike many other functions, finance cannot operate on the assumption that something is "mostly correct." Financial integrity demands complete confidence.

That's why many CFOs remain cautious when AI lacks transparency. If they can't understand how a decision was made, they risk undermining the very trust that finance is responsible for protecting.

What they are really looking for is deterministic AI with clear, auditable logic, where compliance is built into the workflow rather than added as an afterthought. When governance, controls, and explainability are part of the technology from the start, CFOs can embrace modernization with confidence—without compromising the trust they've spent a lifetime building.

A leadership principle he values: Mentoring and developing young talent is one of the most rewarding responsibilities of leadership.

With increasing pressure on CFOs to drive profitability and resilience, how important is automation and AI in finance in reducing manual workloads and unlocking strategic decision-making?

I would say they are absolutely essential. There is really no ambiguity about it. AI is no longer just about improving efficiency. The technology has matured, and while every technology goes through its own hype cycle, there's no doubting the value AI brings.

At the same time, I believe the real value today is not in applying AI to isolated tasks. It's all about using AI to manage complex, multi-step finance workflows while operating within the right governance and control framework.

At BlackLine, we describe this as Agentic Financial Operations, and it is built around three core pillars.

• The first is being distinctly accurate. Everything starts with clean, reliable data because AI is only as good as the information it works with.
• The second is being exceptionally efficient. That means creating end-to-end automated workflows where governance and controls are built into the process rather than added later. Automation without control doesn't create confidence.
• The third, and perhaps the most important, is being financially intelligent. Once you have trusted data and connected workflows, AI can deliver meaningful insights that help finance move from reporting the past to shaping future decisions.

Ultimately, that's what allows finance to become genuinely forward-looking.

The outcome of all this is what we call insight velocity—the speed at which finance can provide trusted, audit-ready information to the business. If I can deliver those insights a week before month-end instead of after closing the books, that's a week of better decisions for the business. If I can do it in near real time, the value becomes even greater.

One thing I strongly believe is that if decision-makers are still relying on last month's numbers, they're already behind.

That's why I don't see latency in finance as just an operational inconvenience anymore. It's increasingly becoming a business risk. So, when CFOs think about driving profitability and resilience, AI isn't simply about reducing manual work. It's about enabling faster, more informed decisions that help the business stay ahead in an increasingly competitive environment.

How can CFOs effectively measure and demonstrate the ROI of finance transformation initiatives, such as automation, AI, and continuous accounting to secure ongoing executive and board-level support?

There is no single metric for measuring the ROI of finance transformation. Every organization is at a different stage of growth, operates in different industries, and faces different business priorities.

I believe CFOs should measure ROI across three levels:

• First is operational impact, reducing financial close timelines, automating reconciliations, minimizing spreadsheet dependency, and freeing finance teams from manual work.
• Second is business impact, improving cash collection, reducing write-offs and errors, lowering audit costs, and strengthening the bottom line.
• Finally, there is strategic value, which is what boards care about most. It's about demonstrating how finance transformation enables faster decisions, better risk management, stronger governance, and greater business agility.

Ultimately, the real ROI isn't just cost savings; it's showing how better financial operations improve control, accelerate decision-making, and help the business grow with greater confidence.

As finance becomes more data-driven, what role do data governance, security, and cross-functional integration (e.g., with IT and operations) play in enabling CFOs to turn real-time insights into competitive advantage?

Ultimately, if CFOs are expected to become business orchestrators, they simply can't operate in silos. Today's finance leaders need to work closely with IT, operations, and every function that either generates financial data or influences business outcomes. Collaboration is no longer optional; it's foundational force.

At the same time, none of this works without a strong data strategy. I've often said that data has to be distinctly accurate because it forms the bedrock of every financial decision. If the underlying data isn't trusted, the insights won't be trusted either, and organizations eventually fall back on guesswork instead of informed decision-making.

We're seeing many organizations struggle with disconnected systems where invoicing, collections, and reconciliations all sit in different places. Without a single, governed view of data, real-time insights are difficult to achieve. As finance adopts more AI and automation, the need for strong financial controls becomes even greater. That's why I believe competitive advantage comes from building a single, trusted source of truth through tighter integration across finance, IT, and operations.

5 Leadership Lessons from Nikhil:

• Leadership is earned, not assigned. Titles make you a manager, but your team decides whether you are truly a leader.
• Listen before you lead. The best leaders keep an open mind, understand different perspectives, and never stop learning from others.
• Practice empathy every day. Putting yourself in someone else's shoes is the foundation of meaningful coaching, mentorship, and support.
• Trust is your greatest leadership currency. It takes time to build, but once earned, it becomes the foundation for influence and lasting relationships.
• Focus on people before performance. Great leadership is ultimately about helping others grow, succeed, and bring out their best.

Looking ahead, how do you see the finance function evolving over the next 5–10 years, particularly in terms of its role in driving enterprise-wide digital transformation and business strategy?

It's always difficult to predict the future. The future of finance will be built around a digital workforce. I often relate this to my own early career as an engineer. If you walked into a shop floor in the 1990s, it was full of people. Today, much of that work is automated, with people supervising intelligent systems rather than performing repetitive tasks themselves. I believe finance is heading in the same direction.

Over the next 5–10 years, we'll see humans working alongside AI agents, each with clearly defined roles. Routine and manual activities will increasingly be automated, allowing finance professionals to focus on interpreting insights, managing exceptions, identifying risks, and guiding business decisions.

That shift also means organizations must invest in retraining and reskilling. AI literacy will become just as important as financial expertise because professionals will need to know how to apply AI in the context of their business, not just use the technology. The CFOs who prepare their teams for this transition today will be the ones best positioned to drive enterprise-wide transformation and long-term competitive advantage.