16 minute read
Inflation – the dark and stormy cloud
will work out how to decipher why the BNPL structure is so successful and implement that into future credit products.
Credit managers should also consider further supplementing their current credit underwriting processes to ensure they capture all the additional and hidden risks that consumers are facing now. COVID-19 triggered drastic actions from governments and banks in an attempt to bring about some stability in the economy; unprecedented amounts of government support, deferrals of loan repayments, lowest cash rates in history. With the economy now reopening, inflationary and cost pressures will eventually push interest rates up and credit managers and lenders will need to balance their decisions from a risk and growth perspective. Disruption to supply chains and hours worked (because of sick leave) will impact income – and the aftermath of the floods and the current Ukraine-Russia crisis is going to add even more uncertainty.
You joined illion from a major bank two years ago, where you worked as a leader in retail analytics and insights. How different is it being on the other side of the fence?
Having had the opportunity to work on different projects with many different types of organisations over the last two years, I’ve realised everyone is in a similar boat! Everyone deals with data issues, budget considerations, people turnover and process inefficiencies, albeit dealt with slightly differently depending on levels of sophistication and team culture. But on the up side, and putting my “data” hat on, I have found what is in common is the desire of almost all organisations to improve their understanding of their own customer base, especially in the current environment. A lot of the credit managers we work with have found value in coupling their own internal data with the alternate and rich data sources we offer (for example supplement portfolio data with illion Spend Data or illion Commercial Trade Data).
Your LinkedIn profile describes you as ‘passionate about data and the value it can provide the modern world’. How do you think credit managers can utilise the power of data more effectively?
I think many people have realised they collect – or have access to – a lot of data because of their daily operations, but the challenge is how to ensure they’re utilising the data they already have to its fullest potential.
To draw actionable insights and “quick wins” from data, companies need to make sure that the data they collect is stored properly and can be digested easily, allowing for quicker-to-market actions. A lot of inefficiencies arise from the fact that projects need to spend too much time simply putting the data in the right format.
Organisations should self-reflect on the capability they have and whether it is appropriate for their objectives. Working with millions of records mean Excel is probably not the right tool any more. Leaders often ask themselves and their organisation, “do we need to invest in cloud computing”, but a more pertinent question is, “do you know what cloud computing is?” Investing and developing your current workforce and leaders will help you make the right decisions.
Finally, to fully utilise data’s potential requires commitment from the entire organisation, not just a “data” team or technically inclined areas.
Product and Credit Managers need to understand what data they have available, and have the flexibility and governance processes to execute business strategies swiftly. IT functions need to support the organisation with enterprise solutions that are scalable and focus on the strategic/long-term goals.
Marketing and client facing functions need to upskill to communicate insights in a layman-friendly manner.
Organisations that embrace data holistically will see benefits without much resistance – make data one of your organisation’s focus/values!
How important is data accuracy and reliability?
Data reliability is probably more important if an organisation is trying to execute a strategy based on insights drawn from data. There are ways to deal with systematic error that arise from less accurate data, but dealing with random/uncertain errors with respective to business decisions might be a little more difficult (e.g. if my watch is always giving me a reading that is 5 minutes late I could probably arrive at events 5 minutes early, but if my watch randomly stops, it’ll probably ruin my day much quicker!). Having said that, my philosophy on this has somewhat evolved over the past decade and will continue to do so with new advances – and depending on the purpose which I use data for.
One thing is certain though – there is no such thing as Perfect Data. System issues, data definitional inconsistencies, data delays, operational red tape has made that concept into a pipe dream – I think most of my data colleagues will concur!
What do you do when you’re not in the data mine?
Aside from spending time with my family and navigating the challenges that arise from primary school (very glad home schooling is a thing of the past, fingers crossed), I’m a huge tennis fan and really looking forward to how the new cars are going to perform in the upcoming F1 season. As an avid aviation enthusiast, I’m also looking forward to get back in the chopper for some scenic flying, although I think fuel prices skyrocketing will likely ground me for the foreseeable future. And shamelessly, I have enjoyed the large number of LEGO sets that have been released because of COVID-lockdowns. ➤
BARRETT HASSELDINE
As a mathematician, you work at the cutting edge of analytics, machine learning and data science. What does a typical day ‘in the office’ look like for you?
As Head of Modelling, my team builds and maintains all of illion’s analytic products, such as our Consumer and Commercial Credit Ratings. We also deliver research projects that explore a range of analytic challenges like model interpretability, and industry challenges such as the long-term decline of the Australian credit card market.
Other than the regular morning stand-up with my team, every day is a combination of thinking about how we can improve our current scores, supporting clients to achieve their business aims, and thinking about what new analytical products the market needs – and which ones we have the capability to deliver.
You have worked in credit analytics for most of your career. Has your field changed much over the past ten years – and what’s the next big thing credit managers can expect?
There have been huge changes over the past decade, especially from a tech perspective. SAS was the coding language of choice, which has slowly been replaced by Python. Analysis used to be performed using an analyst’s local computer, whereas now it is more commonly server or cloud-based using much greater compute power and GPUs. These advances have enabled credit analysts to not only build their own models but also to implement their own models, which can reduce implementation time/cost/complexity. The evolving tech stack has also allowed use of nonlinear modelling techniques such as XGBoost and Deep Learning to become more commonplace, replacing linear models in some low-risk use-cases. Most credit providers are not yet comfortable to use these models to derive high-impact decisions, but I expect this will change over the coming decade.
Over the past decade, many credit providers have digitised their application flows and shifted away from human-entered information, preferring to take friction out of the application flow by relying more on 3rd party data sources. This change reduces human-based data capture, delivers 24-7 availability, and is often trusted more than unvalidated, human-entered information for example from a credit application form. A specific example of 3rd party data which I see as the next big wave of innovation in credit scoring is digitally sourced bank statement data. It is starting to blossom now and I expect this trend will only grow as Open Banking becomes commonplace.
Barrett Hasseldine
You and your team spend your days thinking how you can support credit professionals achieve their business aims; what are some of the ways you do this?
The illion Transaction Risk Score is a great example. It was an idea born from credit professionals’ desire to glean insights from the rich data generated through online banking.
Credit professionals knew that the types of transactions that consumers were involved in could give insight into their character and capacity to pay. Utilising data and analytics, we bring this wealth of insight into a score like any other credit score, but it is entirely based on the information contained within a customer’s online banking data.
As an example of how a transaction score differs to a bureau score, a bureau score factors in whether a person has made their credit card repayments over the past 2yrs. A transaction score will look at the most recent 3-6 months of transaction data to analyse the dollar amount of each credit card repayment, how large it was relative to income, what portion of the credit card limit is utilised, whether the repayments were made via Direct Debit or not, and what the consumer has been spending their money on.
Credit bureau data is limited in scope but is highly curated and available over a multi-year time horizon; it is great for understanding a customer’s long-term credit risk. Transaction data is full of rich insights but is high-volume, messy, and based on a few recent months of data. As such, combining bureau and transaction scores delivers the optimal outcome of understanding both long-term risk trends and a ‘finger on the pulse’ of a customer’s current financial situation. Transaction scoring however comes with a steep learning curve of how to build and implement such a score in real-time. The illion Transaction Risk Score helps credit providers to start getting value from transaction scoring without the risk and cost of a multi-year IT project.
What do you and your family do when you’re not on the tools?
My brain gets a great workout during office-hours, so when I’m not working I enjoy hitting the gym to give the rest of my body a work-out too. I also love to visit Morning Peninsula with my wife and kids to go bushwalking and rock-pooling.
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Smart practices to help you optimise your credit control and strengthen cash flow
By Adrian Floate MICM*
Adrian Floate MICM
When you’re running a large operation with hundreds of invoices processed each month, the resources required to manage your payments grow quickly, especially when ageing receivables become a problem. While customers may not pay their invoices for various reasons, it happens too often, causing a range of challenges and increased risk. Over the last two years, 60 per cent of businesses experienced increased debt management costs, and 54 per cent of companies say that B2B credit sales result in late payments.
Not only is debtor management time-consuming and burdensome for accounts receivable teams, but late payments also restrict cash flow and increase non-payment risk. Fintech solutions provide companies with the infrastructure to manage this risk by optimising and strengthening each financial touchpoint from credit assessment and customer onboarding to issuing invoices and collecting payment.
Automate your accounts receivable and implement e-invoicing
For finance teams addressing debtor and cash flow issues, automating your accounts receivable systems and processes is an excellent place to start. According to the Australian Taxation Office (ATO), it costs a business over $30 to process a paper invoice, $28 for a PDF invoice shared via email, and just under $10 to process an e-invoice. By switching to e-invoicing, businesses can save an average of $20 per invoice processed. For companies processing 500 invoices per month, this equates to an annual saving of roughly $120,000.
The time and cost efficiencies
realised through e-invoicing are among the many benefits businesses and their customers will enjoy. When these innovative invoicing processes are implemented using a connected solution that manages the end-toend payment process, it becomes easier for customers to pay on time. This is mainly due to an improved payment experience, primarily delivered through the availability of more, and flexible, payment options. Further, an improved payment experience can be the difference between closing a transaction in days instead of months, proving invaluable to companies, especially after the last two years of uncertainty.
In a survey of businesses across Australia and New Zealand, 85 per cent of respondents said accepting and making card payments for B2B transactions improved spend control and visibility, reduced payment processing times, and delivered cost savings compared to traditional payment and purchase order processes, such as manual electronic funds transfers. For customers who haven’t been invoiced yet or who consistently pay on time, implementing smart technology is about making the payment process smoother. And for problem debtors, it’s about providing accounts receivable teams with the tools they need to efficiently collect late payments and address the broader problems that late payments create.
E-invoicing and digital payments solutions simplify the collections process and reduce the invoice-to-pay lifecycle, which improves cash flow, strengthens data integrity, and improves systems and processes across organisations. According to Deloitte, it takes businesses around 30 days to complete a payment, and 47 per cent of suppliers are paid late. By realising efficiencies and improving cash flow with these solutions, businesses enjoy better collaboration with their trading partners along with having the tools and data to strengthen credit risk management frameworks and processes.
Reduce bad debt and tighten credit risk management with automation
Automated payment solutions are bringing the convenience and technological advances seen ➤
in B2C payments in recent years to the B2B space. These advances have seen consumers access credit for goods and services through credit card payments or buy now, pay later (BNPL) services. It’s been helpful for consumers to have this option available. However, the scale at which these advances can help companies demonstrates the seismic impact this technology will have on cash flow across the supply chain while equipping decision-makers with the data they need for stronger credit management.
Drilling down into each element of a business’s finances, such as your credit risk management processes, plays an important role in proactive and effective financial management. A recent survey by McKinsey & Company found that 43 per cent of CFOs identified streamlining their budgeting processes to react faster and more efficiently as a top priority. With an integrated receivables platform, credit managers can automate their credit risk management to achieve lower instances of bad debt, decrease blocked orders with AI-based predictions, and reduce customer onboarding times.
By automating accounts receivable processes, businesses can set rules to automatically notify their credit managers and accounts receivable team when an account needs attention. This can include notifications when an account is late or their credit risk is too high. Credit managers can also feed this data into their assessment systems allowing for faster, automated rejections and approvals while efficiently managing credit risk.
The reduction in manual processes and efficiency realised through automation can transform a business’s credit management function providing it with the systems, processes and tools to manage risk proactively. For instance, automated credit management systems can thoroughly analyse a business’s financial data to provide an accurate credit limit upon onboarding and proactive updates based on real-time risk alerts. And with 53 per cent of companies still intending to offer trade credit for B2B transactions as a shortterm financing tool for customers, having tight credit management processes is critical. Further, by integrating these automation features with a business’s existing ERP and CRM software, the customer onboarding process reduces from days to hours in some instances.
Streamline and improve data reliability with ledger-to-ledger integration
In the inevitable event of chasing up late payments, data integrity and ledger-to-ledger integration provide businesses with a head start by giving both parties a single source of truth from one integrated system. Ledger-to-ledger integration connects the ledgers of each company, allowing for automatic real-time account reporting and reconciliation. For example, when a customer pays their invoice, the payment is automatically recorded in their accounting systems, the supplier’s accounting system, and other systems integrated with the payment platform. Both parties in the transaction benefit from a reduction in manual data entry while streamlining other tasks such as account reconciliation and reporting.
For those problem debtors with a large balance owing, an integrated accounts receivable management system means businesses and their customers can collaborate on a repayment plan in real-time. The customer simply logs into the pay-byinstalment interface, and they can choose how and when they pay. For example, both parties may agree on fortnightly payments until the invoice is paid in full. The customer can schedule payments to be automatically debited from a bank account or credit card. These automated repayments eliminate the need for further manual follow-up.
Strengthen your financial management with one intuitive AI cloud-based solution
When hundreds of payments are moving through your business each month, the resources required to ensure accounts receivable processes are efficiently managed and can grow substantially. Therefore, it’s critical that organisations have the systems, processes and tools they need to manage cash flow and risk proactively.
With smart solutions in place, you can take the guesswork and inefficiency out of manual accounts receivable management. Whether your business is new to automating its systems or is well on the path of its digital transformation journey, implementing intuitive AI cloudbased solutions that deliver benefits across the business breaks down the silos that restrict cash flow and slow productivity. It’s a streamlined solution to complex problems that will help your business maintain a competitive advantage throughout all stages of the business lifecycle.
*Adrian Floate MICM CEO at Spenda E: adrian.floate@spenda.com.au T: 0412 377 877
