Controllers and financial professionals face unique problems when it comes to performing a Cash Flow Analysis for their institutions.
Limited access to quick banking insights coupled with outdated modes of reporting not only hinder access to up-to-date, real-time data, they are also time-consuming.
With so much manual work to be done, from reporting to fabricating insight-finding models, conducting an effective cash flow analysis can seem daunting.
Add the impact of COVID-19 restrictions on workplace attendance, and we now have a scenario where employees are physically forced to work from home and are struggling to keep up. In many cases, the workplace has become obsolete, as employees are finding themselves working from home on a permanent basis operating in an environment with limited access to real-time insights from stakeholders, systems, and more.
Without access to real-time, live information, business decisions are hindered, reporting and analysis of financials lag, and findings can only be produced as quickly as someone can manually type them.
Data may be irrelevant by the time it is done being collected and analyzed; an accurate cash flow analysis can be difficult to produce. Read more to see how seven new technologies are helping controllers today to manage their workload and conduct effective cash flow analysis.
Cash flow analysis is, simply put, the study of how a business generates and spends money.
Operation costs, financing activities, and investing activities are analyzed and evaluated. The cash flowing in and the cash flowing out are closely examined, and ultimately form the basis of a thorough cash flow analysis.
Companies have many moving parts, and an effective cash flow analysis solution will enable access to financial data for everyone. This empowers businesses to control their existing financial data.
Here are seven technologies that are being used today to help power cash flow analysis:
Artificial Intelligence (AI) is currently being used in account reconciliation and cash flow forecasting. Because AI mimics human thought and behavior, it has become an invaluable problem-solving tool for cash flow analysis.
Robotic Process Automation (RPA) employs software to automate repetitive, routine tasks normally performed by knowledge-based workers, typically supporting areas such as account consolidation or account reconciliation.
Automating such tasks not only saves time and money, but it also reduces the potential for human error. Best of all, RPA frees up time for staff to perform activities of higher value, such as risk management, hedging or liquidity structuring.
Machine Learning (ML) is a data analysis method that automates analytical model building.
A branch of artificial intelligence, ML is based on the idea that systems can learn from data, identify patterns and trends, and then make decisions based on these findings.
For financial professionals, this becomes relevant for cash flow forecasting, hedging, and the analysis of large quantities of data.
Open Banking is the practice of sharing financial information electronically, securely, and only if approved by the customer. It works under the assumption that banks will provide data access to third-party providers, however, in the US, some banks do not voluntarily make data available. This has no impact on open banking, though.
Written by third-party providers, Application Programming Interfaces (APIs) are software programs that access financial data to develop new apps and services. Ultimately, this leads to new and improved products for treasury users.
Blockchain or Distributed Ledger technology is poised to deliver treasury improvements in the areas of reconciliation, virtual accounts, and compliance.
While not yet perfected, the industry remains hopeful in the final product.
With Software as a Service (Saas), applications, software, and any data created by a treasury team are stored in the Cloud on their provider’s server and shared back and forth over the internet.
Organizations pay a fee for this service, which includes access to the application, data, security, and customized performance terms.
SaaS eliminates the need for internal IT management and allows treasury teams the ability to log on via the internet from anywhere in the world, at any time.
Flexibility and cost-effectiveness make SaaS an appealing solution.
Data Analytics is the process of inspecting, cleansing, transforming, and modeling data for multiple sources to discover useful information, inform conclusions, and drive decision making.
As a result of the 2020 pandemic, controllers and treasurers have evolved into an advisory position, serving a broader organization. Professionals are being pushed to take on new roles while also maintaining their daily routine tasks. And in most cases, they don’t have access to additional funding or resources to call upon, namely, the man/woman power to answer everyone’s questions.
As cash flow managers become more strategic and their responsibilities around analysis and decision-making more specialized, it can be difficult for a team to evolve into advisory roles over their company without better automation of existing manual processes like reporting and bookkeeping. According to Capgemini, many corporates have taken initiatives toward fully automating a variety of individual processes, while seven in 10 finance professionals say they recognize the potential for full automation by 2022.
For controllers, clear cash flow analysis processes enable them to manage and maintain corporate payment structures, bank account management, dashboards and reporting, forecasting, and treasury risk management.
Here’s a list of the main benefits automated treasury functions like cash flow analysis can provide:
Ultimately, cash flow analysis provides critical information, allowing controllers and financial professionals to do their jobs better.
If you’re a controller and are interested in automating Cash Flow Analysis or Cash Forecasting, download the full guide to learn more.