How to Get Started with Treasury Technologies
What you’ll learn
- Learn the steps to select the most suitable technology.
- Understand the benefits reaped from using the right technology.
The current scenario in treasury
Most companies still use age-old methods in their treasury department. Spreadsheet has been the most widely used tool for cash forecasting for a long time and still continues to be so. However, it has certain limitations:
- It is error-prone and consumes a lot of time
- It becomes challenging to gather the right datasets and consolidate them manually.
Due to the limitations, the cash forecasts generated are inaccurate and unreliable. This leads to poor borrowing and investing decisions.
Given the available treasury technology such as AI, RPA, and Machine Learning, treasury should consider automation to improve team productivity.
How to choose the most suitable technology?
These are the steps to choose the best-fit technology:
1. Understand the strategic value of treasury
- Plan a strategic vision for the treasury.
- Align the strategic vision with the company’s goals and requirements.
- Identify tasks that need to be automated, freeing up employees’ bandwidth to focus on strategic activities.
2. Identify all the stakeholders
- Identify the stakeholders involved in the implementation process and ask the stakeholders for their wish list.
- Understand their requirements and what can be offered to them.
3. Determine the system requirements clearly
- Understand the requirements on a high level, such as:
- Time savings
- ROI
- Seamless integration with banks, ERPs and TMS
- Automated data gathering
- Automated cash forecasting
- Increased forecast accuracy
- Hedging capabilities.
- Prioritize the requirements based on their importance.
- Evaluate the technology options based on their ability to meet the prioritized requirements.
4. Draft a general timeline for execution
- Keep the end in mind and create a reasonable timeline.
- Determine if procurement involvement is required to help with the selection or negotiation.
- Determine if the IT team’s involvement is required to validate technologies.
- Identify the people involved in budget approval.
Benefits from technology
- Accurate cash forecasting: Instead of relying on instincts, treasury can generate accurate cash flow forecasts using machine learning to make better decisions.
- Proactive liquidity planning: Treasurers can plan proactively for cash crunch and market fluctuations with granular visibility of cash flows across regions, currencies, and entities.
- Proactive risk management: Fraudulent activities can be detected and prevented using automated systems.
- Role enhancement: Treasurers can make strategic, confident, and timely decisions based on real-time information instead of spending their valuable time on manual tasks. This helps them to be a high-value employee at the office of the CFO.
The main goal of treasury technology should be to eliminate manual efforts, support confident decision-making, and generate ROI.
To gather more insights on how to get started on choosing the best-fit treasury technology, watch this webinar on buying and implementing technology for treasury professionals.
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HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.
