Advancing Financial Operations Part 1: An new Route Forward in the era of AI

Blog
November 16, 2023
Advancing Financial Operations Part 1: An new Route Forward in the era of AI

This is the beginning of a multi-part series called Advancing Finance Operations, where we share best practices, insights, and learnings as we seek to advance the corporate finance function in the era of AI, which is reshaping the landscape both now and in the future.

The Evolution of Finance Operations and Treasury Management: Transitioning from a Back-office Function to a Strategic Capability

First, a brief refresh on the history: In the US, corporate finance became popularized in the 1960s because banks were not allowed to operate across state lines, a policy that resulted in over 15,000+ banks. Each city had its own bank node in an analog network that played a critical operational role for businesses to collect receivables and deploy capital for local operations. It was the responsibility of the corporate treasurer to manage liquidity and risk so operations would not be stifled across all of these banks, which was a process that required significant operational overhead. The greatest challenge for most companies and treasurers at the time was not being able to access capital markets. With availability reserved to only a few of the largest corporations, business expansion was stifled and their growth was capped.

Bank of America in the 1960s

Fast forward to 2023: Many companies are migrating their business workflows and capital markets from analog to digital, which has had a significant impact on productivity while also improving access to markets and liquidity. Although great strides have been made in modernizing these systems, businesses are still burdened by antiquated legacy systems, such as mainframes, legacy ERP systems, ACH, wire transfer, checks, etc. Today, the challenges are concentrated in scaling global operations, with 1 in 2 finance teams in the US struggling to integrate finance and business systems. This makes it significantly challenging for organizations to get a clear picture of their financial health and risk in an increasingly digital economy. We’re also experiencing one of the fastest rate hike campaigns by The Federal Reserve since the 1980s (a 5.5% interest increase since March 2022), which has exposed many corporate balance sheets to increased risk and has broken models that have been used in an era of zero interest rates over the last decade. With global scale, increased cost of capital, and sudden changes in central bank policy, treasury operations need trustworthy data in real-time, with tools to boost efficiency and risk visibility so they can navigate through increasing economic uncertainty caused by periods of high inflation, interest rates swings, regulatory shifts, and multiple geopolitical conflicts. Luckily, we are at an inflection point with several innovations that could be a key catalyst to supercharge treasury workflows for the next decade. 

The Future of Treasury Management: AI-Embedded Finance Operations

With the rise of large language models (LLMs) and natural language processing (NLP), we can now query vast amounts of data using semantic search while automating manual data tasks that currently take up 32% of a finance team's time. LLMs and machine learning (ML) can assist many workflows like trending analysis, reconciling transactions, modeling scenarios, and helping to craft the perfect message to get an overdue invoice paid. By reducing the operational burden and toil, treasury operations can focus more on strategic finance and improve their cash flow return on investment (CFROI). This approach does require a rethink of treasury workflows with AI embedded or an LLM in the loop. An AI-embedded approach to treasury doesn’t replace the human finance professional; rather, it empowers them to play an even more strategic role in the organization.

Financial Operations with AI/LLM in the loop
Although experimental, early adopters are already seeing exponential improvements and significant benefits with AI embedded finance operations:
  • Improved finance and cash efficiency ratios
  • Improved cash flow return on investment (CFROI)
  • Lower first month collection default rate
  • Higher working capital turnover ratios
  • Improved risk visibility across FX, investments, and debt
  • Improved forecast accuracy with machine precision and lower error rates
  • 35% boost in junior or new employee productivity

We encourage business leaders of organizations doing business internationally with revenues exceeding $10 million annual to begin a shift towards AI-embedded workflows. Not only will these capabilities be required to keep up with today's demands, they also will be mandatory for success amidst heightened financial uncertainties in the coming years.

Want to learn more? Send us a note or schedule a demo to learn more about how Route is transforming treasury operations. 

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