The challenge

The treasury team has been actively orchestrating a digital transformation across the organisation. The embrace of emerging technologies in data analytics and machine learning has optimised treasury decision-making processes, unlocking efficiencies in time, cost and risk management, and elevating the team’s standing within the broader organisation through more value-add insights to the existing financial goal setting processes.

Due to the lag in cash flow visibility and lack of a robust forecasting process, Arcosa relies heavily on daily cash flow analysis and forecasting to effectively manage vendor and supplier relationships, optimise liquidity and ensure smooth operations across all its entities. However, its complex and highly regulated operations have resulted in a siloed and unstructured data environment. In the absence of automated ERP/TMS solutions, this disjointed data environment presented challenges in achieving adequate and timely visibility into cash flow patterns and, subsequently, the team’s ability to reliably predict future cash flow trends.

To complete daily cash flow and forecasting reports the treasury team had to manually aggregate and normalise datasets sourced from across the business. This extremely time-consuming process often resulted in the reports being out of date by the time they were completed, potentially exposing the organisation to preventable costs and risky counterparties.

Furthermore, this legacy process presented challenges in measuring the firm’s performance against top-down financial goals and providing senior leadership with the visibility needed to improve goal setting. The ability to challenge monthly, quarterly and annual cash flow goals, and understand variances between those forecasts and actual cash flows, is vitally important to both the company’s short-term health and its long-term strategy for growth.

The solution

Arcosa recognised the importance of adopting next-generation technologies to address its challenges.

The company turned to J.P. Morgan, its core banking partner, and through co-creation workshops the bank was able to respond with cutting-edge analytics solutions underpinned by big data and driven by artificial intelligence – cash flow intelligence (CFI). This is a cash flow analytics and forecasting workbench that elevates human decision-making abilities with powerful AI derived insights. Leveraging this solution, Arcosa has been able to automate visibility into its cash flows and produce machine learning based forecasts on demand. By easily tracking the progress and variance of the forecasts, CFI gives Arcosa’s treasury team the right information at the right time allowing them to anticipate and pre-empt cash shortfalls before they happen.

The one-click forecasting function means the treasury team can quickly evaluate the FP&A forecast to spot any unreasonable projections before they result in funding issues or lost interest revenue. The solution has enabled a shift in the treasury team’s daily operations away from compiling and organising data and towards deriving actionable insights that elevate its standing within the broader organisation and set it up for success in an increasingly demanding ecosystem.

Best practice and innovation

The treasury team at Arcosa has been able to self-serve core data insights and reporting needs by streamlining, modernising and automating many mission-critical analytics and forecasting activities.

Specifically, the team can confidently navigate an “ocean” of multi-bank data which can include feeds from third-party bank account flows worldwide. Deriving analytics by business line, or by counterparty, and across various historical periods can now occur within CFI in a matter of seconds. The convergence of human intuition via logic tags and advanced AI pattern recognition allows Arcosa to create meaningful cash flow categorisations to isolate and analyse important events and trends and improve forecasting accuracy by teasing out patterns in the data that can be challenging for the human eye to identify. Cash flow categorisations are not dependent on ERP loaded data but can be created leveraging bank features to create sources or uses of cash flows. For example, Arcosa leverages VRNs and lockboxes to create account receivable cash flows by business line all depositing into one bank account minimising risk and cost.

Key benefits

• Cost savings.

• Headcount savings.

• Process efficiencies.

• Increased automation.

• Risk mitigated.

• Improved visibility.

• Errors reduced.

• Manual intervention reduced.

• Increased system connectivity.

• Future-proof solution.

• Exceptional implementation (budget/time).

• Improved key performance indicator (KPI) metrics.

“It is a great honour to receive this award and be recognised amongst our peers as an innovator. For this solution, Arcosa approached J.P. Morgan with an idea to visualise a sea of data in the banking platform as to not add layers (systems/BI tools) between Arcosa and its banking data. J.P. Morgan rolled up their sleeves, partnered with Arcosa and created Cash Flow Intelligence (CFI); a cutting-edge analytics solution underpinned by big data and driven by artificial intelligence.”

Frank Woodley, Director of Treasury Operations and Assistant Treasurer