Modernizing finance: Transforming financial functions with data and AI

Modernizing finance: Transforming financial functions with data and AI

Leveraging cloud and AI-based solutions to modernize finance functions is a trending idea among many corporate finance teams. It has grown in popularity as more and more organizations transition to the cloud. The finance office, often considered one of the slowest adopters of technology and resistant to change, is undergoing a paradigm shift as pressure to reduce costs and improve capabilities is forcing transformation.

Transforming finance functions, however, presents several challenges compared to implementing analytics and modern cloud capabilities in other departments. For example, a marketing department making personalized offers can accept being wrong a percentage of the time. It’s not ideal, but it is ok if the data isn’t perfect (so long as any use is not violating GDPR, etc.). This is not the case with finance, where the slightest error can lead to costly fines and auditing. Data must be laser-precise, immutable, and preserved when the books are closed. 

The requirement for such precision leads to an interesting problem for corporate finance teams. Modernization is needed, but attempting to modernize all areas of finance at once can appear to be a futile endeavor. This is because the methodical approaches required to implement solutions can be slower than the pace of technological innovation, meaning the solutions could be outdated by the time they go live. As such, organizations need to leverage a different modernization process to increase the success rate of finance projects.

Enter modular capability development 

There are many opportunities within the finance team’s responsibility set. Whether it be FP&A (Financial Planning & Analysis), Tax, Treasury, or others, each has powerful scenarios where tools like machine learning and automation are perfect fits. By building the required data foundations in small form factors to support narrower use cases, finance teams can start with low-risk areas like ML forecasting. By leveraging this strategy, teams can easily benchmark predictions until end users are comfortable. This focuses data modernization efforts on achievable outcomes and allows the underlying modernization efforts to remain agile as technology evolves.

Example modern finance solutions


While one team develops solutions like ML forecasting from a data science perspective, another works hard to develop, analyze, and audit the data underneath. They will build and monitor pipelines that ensure that data and ML models are correct and reconciled, triggering alerts if anything goes awry.

The organization then adds the next module. A new module lights up new capabilities and can bring in more systems, data, technologies, and people to the process. The process repeats until it fully transforms one or more core functions while creating lighthouse wins to accelerate adoption and innovation.

The value is real, and it is spectacular 

Often losing out to revenue and customer-focused efforts, internal improvement is often left behind and, up to now, has been content in that position. However, this doesn’t mean that modernizing the finance office can’t dramatically impact an organization’s bottom line.

Savvy CFOs push innovation and see incredible outcomes. However, the massive backlog of modernization can be daunting, even for technology leaders with leading analytics capabilities. Neal Analytics has leveraged the modular approach with some of the world’s largest technology and social media companies to implement new capabilities without “boiling the ocean” to borrow an overused idiom. By deploying ML forecasting capabilities that reduce forecasting cycles from weeks to less than a day or identifying risk in contracts that may warrant additional human effort to review, organizations can quickly realize value and build confidence in ROI projections.

These successful efforts led to several other modules and significant data advancement. Our customers can now identify revenue opportunities with better market intelligence, reduce the risk of human error, and more efficiently forecast headcount and operating expenses. This is all done by leveraging AI to predict outcomes, risk, or analyze lengthy but important documents like legal documents, tax documents, contracts, etc., significantly reducing manual cycles required. Auditing efforts are optimized because modern finance offices can categorize data by risk level, readily available, accurate, and well documented.

Given the above examples and that many finance departments are decades behind technologically and are still rooted in Excel, modernizing finance remains a prime opportunity to reduce costs and improve efficiency, significantly impacting the bottom line.

Building in the right direction 

Neal Analytics is an expert in this space. We have developed world-first capabilities inside some of the industry-leading finance departments and honed our approaches to deliver these same capabilities to any corporation with a significant finance arm. We have honed our learnings into accelerators that can quickly and reliably deliver value. Many customers are skeptical that they can enable the same capabilities as our clients, but our clients have no unique finance capability that other finance departments cannot implement.

That said, in a general sense, they are many years ahead of other corporate finance teams. To advance quickly and make up ground, we encourage customers to start simple and work back from the functions they feel will create the most value. Beginning with a mindset of implementing a new tool, platform, or service rather than first determining which specific challenges need to be solved leads to the negative ROI projects that drag on and don’t show value along the way.

Neal typically advises organizations to pick a function that they can modernize, quickly identify the top solutions needed to support it, and then quickly get started by building just what you need to support each solution. If sequenced intelligently, organizations can scale the value of their new capabilities as they continue to modernize finance functions.

Getting started

Neal Analytics offers a few ways to begin this journey. For finance teams that have an urgent need to modernize everything, Neal offers an integrated modernization engagement that starts with discovery and prioritization with the CFO and their key reports. We then set a strategy and build an initial roadmap around the top priority modules. Once the roadmap is approved, Neal will execute the plan with a disciplined agile delivery approach.

For teams already on their journey and who have some solid foundational components in place, we offer a variety of proven capability modules we can implement and customize for each business’s unique needs.

Finally, we offer a simple assessment engagement with clear deliverables and outcomes for customers who want us to assess their capabilities and propose a path forward but may not want to commit to transformation.