INCREASING THE PROFITABILITY OF WORKING CAPITAL PROGRAMMES

Synopsis
Improvements in working capital management will enable all organisations to create value and enhance the way they operate. According to PWC, there is €1.2tr of excess working capital tied up on balance sheets.  Those who release the blockages which hide this capital will be able to boost growth and create more potential for investment.

Evaluating and structuring the programmes designed to release working capital can be a complex process and may involve many parties with different priorities. Technology can mitigate the operational risk associated with manual analysis and structuring, as well as improving visibility and unlocking potential. However, industry experience and a refined process to support the technology is every bit as important.

This paper discusses the problems and solutions involved in launching new working capital programmes, and how to reduce risk and secure better outcomes for all parties through a combination of technology and a detailed systematic process.

Challenges in working capital programmes

Anyone involved in working capital finance programmes will almost certainly have experienced the frustrations of trying to see things clearly enough early enough.  This is necessary to support effective structuring for ongoing management, and to avoid the risk presented by poor practice. In the early stages, many issues can trap decision-makers in an endless loop of inertia, indecision and over-analysis. When the programme is incepted, disjointed processes, the inability of debtors to see the behaviour, and changes in the risk profile are commonly cited as some of the main challenges faced in this sector. For example:

• Portfolio evaluation – with working capital finance programmes, it is clearly vital to gain a full understanding of the portfolio’s profile and performance. Discrepancies in methodology between the various parties, as well as different manual or technology-based analysis tools, can lead to confusion at this important stage. The result could be that a programme that doesn’t fit the client’s needs.
• Behavioural analysis – traditional analysis methods may provide a reasonable view of the basic behaviours that underpin the risk profile of the portfolio at any point in time. However, the subtleties that can precede material changes in the portfolio, or even fraudulent behaviours, can be nearly impossible to spot. Changes in patterns of payments, size or frequency of invoices, or even when and how invoices are settled, can be indicators of potential problems.
• Programme Compliance – it’s relatively simple to ensure that the invoices to be funded are in line with the defined eligibility structure on day one. However, details such as the order of the rules to be applied can make a material difference to the outcome. Testing is required and the analysis of the structure prior to funding can be very time-consuming. Initial testing is generally done with a single snapshot of data, and it is very difficult, if not impossible, to test for all scenarios. This means that non-performance and unanticipated risk to the programme may go unnoticed.
• Reporting and alerting – one of the key challenges of the effective running of a funding programme is the need for consistent, effective reporting and alerting:
  • Much reporting of performance is still done via weekly or even monthly feeds of data. With such long periods between reports, negative changes to programme performance can often be impossible to remedy by the time they are identified.
  • Traditional reporting methods often rely on analysts keeping a close eye on the data and reporting their findings to risk committees and other stakeholders. This manual process can mean subtle, behavioural changes that can be precursor to fraud or significant changes in risk can extremely difficult to identify in sufficient time to act.  
  • With multiple parties to a transaction, reporting requirements can lead to misunderstandings and discrepancies in the way that the portfolio performance is seen.

Systematic analysis and technology

Recently, many column inches in the trade press have been devoted to the coming together of finance and technology. The world of finance certainly operates more efficiently when using new technology solutions, with more accurate results and a better experience for users. However, if technological innovation is based on a disjointed process, you are simply automating a bad process which will yield inaccurate results.

To unlock the potential in working capital programmes you need to be able to:

• evaluate the potential of a programme to enable all parties involved to make quick go/no-go decisions
• deliver effective analysis of the portfolio to allow all parties to move quickly through structuring, armed with all the right information rather than a mass of unrelated information
• protect the programme through the systematic application of rules so that only assets eligible for the programme are included
• grow the programme with the confidence that precise insight and control is provided to all parties, who can then invest and grow the programme with confidence

Aronova’s answer to these problems

For over 15 years we’ve been producing technology to work with invoice data for funding and insurance and have distilled our extensive experience into a highly refined process that we call “Evaluate, Deliver, Protect, Grow”. Our technology is designed around this process. We can control the challenges and organisational complexity of bringing so many parties together. Aronova’s experience of structuring complex programmes enables us to foresee problems and provide critical guidance on the deployment of technology. We achieve this as follows:

Evaluate
A simple Excel upload of standard invoice data can provide near-instant analysis of the profile, risk and performance of the portfolio. We run automatic data validation algorithms to spot both data and behavioural anomalies, and our strategic partnership with Dun & Bradstreet enables us to match the underlying obligors or suppliers to a DUNS number. This enables us to confirm the exact legal entities in the programme in addition to their associated group structures. This gives all parties a single, clear view with the ability to make quick go/no-go decisions with confidence

Deliver
After the initial evaluation, we automate the process of adding a feed of data into our system to support the structuring of the programme and ensure that any changes in the data are monitored. Our flexible multi-pool eligibility structure is then deployed with the criteria for the programme in place to allow for effective modelling. The result is that the funding can be optimised to both meet the requirements of the borrower while effectively protecting all parties. 

Protect
With the programme now up and running, the effective management and monitoring of the portfolio is critical. Firstly we continue to apply all the eligibility criteria to every new piece of data that we receive to ensure it complies with the programme requirements. We also deploy tried and tested behavioural algorithms to identify changes in the portfolio’s profile. These algorithms identify any fraudulent or behavioural changes which could present a risk.

Grow
Our process and technology effectively checks all new data, making sure that only assets that meet the requirements of the programme are passed for funding. All parties are alerted if any issue is identified long before it becomes a problem. The result is that the programme can be scaled without incurring additional risk or needing to take on additional staff to manage the extra required analysis.

Aronova Multi-Pool Technology

You can read more about how we have helped to grow multi-pool programmes here.

And you can learn more about creating an industry-specific approach to the Evaluate, Deliver, Protect, Grow model by selecting your industry below.

Funding providers
Banks
Asset Managers
Funds
Insurers
Private Equity