Treasury Industry Insights Series: Fast-track digital treasury by reaping opportunities in Data-as-a-Service

Treasurers are locked into a data race. As the sheer volume and accessibility of data rockets, its application is changing our way of life and commerce. The horizons of what a digital treasury can achieve are rapidly expanding and the untapped value in usable data presents one the keenest opportunities to elevate the role of treasury in business.?

PWC’s 2021 Treasury Survey ranked inaccurate cash forecasting and visibility, and dealing with operational scale and complexity, as two of the top concerns for treasurers.[1] While real-time cash reporting and forecasting has become essential through the pandemic, it is really only “the tip of the iceberg” of the opportunity for treasury. With Data-as-a-Service, actionable insights to enhance the cash conversion cycle can quickly be realized to improve payment efficiencies, working capital analytics, FX payment optimization, and fraud prevention, among a vast array of other tangible applications.???

“The principal strategic advantage of data is that it enables greater visibility into complex processes'', according to Michael Bosacco, Director of Advisory at Bank of America. “Access to the right data in the right format unites capability with technology and weds resources with workflow awareness”.?

What can be achieved with data and data visualization tools has become paramount to assuring process and cost efficiency throughout transactional information flows. This challenge of getting the right data, from different systems and for different stakeholders, and applying it with the right technology to produce actionable treasury outputs, will only grow. Yet, treasury’s central role in the organization and the fact that the risks it manages impact all areas of the business creates a unique data opportunity for treasurers. By thinking broadly about available data sources and tangible use-cases, treasurers can unlock digital capabilities to speed up and improve decision making as the organizational infrastructure evolves.?

Three key actions treasurers should take to drive a data first culture?

Regardless of how far along the digital journey your treasury is, establishing a “data first” culture is the key to realizing long-term value from data.??

1. Establish a data infrastructure?

To improve the visibility of processes and workflows, begin the data analytics journey by migrating from the outdated “organization wrapped around various systems that house data” to a “data house wrapped around the organization”. This will reduce data quality issues that stem from consolidating across the company and enable efficient data accessibility that results from a proper data ecosystem.?

2. Arrange the levers and metrics that matter?

As treasury moves from consumer of digital tools to provider of data insight solutions, understanding “client” needs is critical to success. This requires engaging with stakeholders to understand what KPIs matter most and, with the right visualization tools and digital skills, drilling through data “noise” to focus reports on actionable insights. In practice this also means having the right tools for near-real time visibility for stakeholders to access and monitor triggers and KPIs.?

3. Migrate from looking back to looking forward?

Shift the mindset from backward facing scorecards to forward looking insights powered by data that support out-front opportunities. As the supporting infrastructure and treasury data skills grow from visualization tools like Tableau and Microsoft BI to data-oriented programming languages like Python, R and Spark, the use-cases evolve from simple business insights, focused on the past, to predictive models that add value through automation, and can quickly be scaled. To achieve this data awareness, skills that facilitate the full data-to-insight process need to become part of the core treasury skillset.?

?

?

Balancing data availability and application?

As treasurers work to embed a data culture, the short-term bottleneck for realizing value from advanced data applications is access to usable, accurate data from within the organization, and the associated technology investment hurdle.?

This is particularly the case with artificial intelligence (AI), like machine learning (ML), where more accurate results are often achieved by simply adding more data. It's easy to get caught up in the vast array of AI applications and possible ML algorithms that are finding maturity in cashflow forecasting, foreign exchange and working capital management. In practice however, limited quality or quantity of data available within the company can hamper efforts and lead to unimpressive results, which can dampen confidence and erode business cases for future investment.?

To fast-track the treasury data journey then requires a balance of access to data and understanding tangible use-cases. This process cannot be siloed, it needs to be connected to external ecosystems and enriched through the right partnerships that can add value by telling you what you don't already know. Regardless of where you are in your internal data journey, mature data applications with third-party data can already add value. For example, the right bank payment data can improve visibility and access to FX payment insights, showcasing corridors where the receiving currency is different from the country’s host currency. This straightforward use-case exposes opportunities to optimize FX payment flows and liquidity, reduce costs and enhance counterparty risk management.?

Your bank’s data as a service -a springboard to opportunities?

McKinsey research proposed that the banking industry has one of the largest opportunities for value creation from data and the application of AI,[2] and already some of the most sophisticated weather models have been created for commodities trading. This is a real opportunity for treasurers who are embracing data as a service given the fact that many more mature data and AI applications use the same transactional data, reducing the initial data engineering burden and allowing you to add value across multiple areas of treasury.?

“In our view the scope of data analytics with just a few key datasets is nearly endless and can quickly generate cash by uncovering process resilience and ultimately sustainable change”, says Joan Gelpi, Global Head of Data and AI, Global Transaction Services, Bank of America. “With this payment data we are able to help clients understand their supply chains in even more depth, which raises the level of insights and conversation with CEOs and CFOs,” he adds.?

To support this, Bank of America is launching a range of sophisticated analytics dashboards to boost the treasury data journey. This incorporates working capital benchmarking, FX payment inefficiencies, fraud reduction flags and paper to electronic payment optimization in a single dynamic, easily understood interface. These tangible action-oriented insights will help many clients to improve cashflow, reduce risk and drive cost savings across the business.?

Expanding process insights complements the existing cashflow forecasting infrastructure available to Bank of America clients, which integrates machine learning into bank transaction data. The CashPro Forecasting platform pulls data from Bank of America accounts as well as 3rd party banks and allows forecasts to be customized across different user-defined categories, with unique transaction mapping rules and a range of machine learning model drivers. With an easy setup that reduces the implementation burden, this tool quickly improves visibility of cash and the accuracy of cashflow forecasts to support liquidity and working capital.?

Speak to your Bank of America relationship manager to understand how our relentless investment in Data-as-a-Service and actionable data insight tools can accelerate your treasury data journey.?

Brittany Marten

Head of Global Industrials Sales

Bank of America

[1] https://www.pwc.com/us/en/services/consulting/fit-for-growth/global-treasury-survey.html?

[2] https://www.mckinsey.com/industries/financial-services/our-insights/ai-bank-of-the-future-can-banks-meet-the-ai-challenge?