By Kyle McNabb, SVP of product marketing
Ineffective accounts payable (A/P) processes are costing UK—and global—businesses considerably. According to the US’ Institute of Finance & Management (IOFM) each payment costs an organisation twice as much to process in an organisation with less effective A/P functions than it does in best-in-class companies.
With a dogged focus on cutting wasteful spend in many organisations, A/P should not be overlooked. Automation is one way leading organisations are finding points of savings in A/P, as doing so can significantly improve effectiveness and efficiency, reduce human errors and missed payments and ultimately boosts satisfaction ratings thanks to faster payment processing.
When done right, automation is also embraced by A/P staff, as it allows them to cut down the time spent on manual processing and instead gives them more bandwidth to focus on managing exceptions, developing relationships with suppliers and taking on new tasks.
Deploying the right software solution is a first step in a successful A/P automation project, but that effort must also take into account best practices in order to realise the greatest results.
Centralisation and organisation are key to any effective accounting process. But in many organisations, the data leveraged by A/P comes from disparate sources. The company’s enterprise resource planning (ERP) system usually serves as the main source, but there are countless others. Consider, for example, the systems that reside with sales staff, external vendors, customers or other points along the supply chain, such as transportation carriers and manufacturing and warehouse facilities.
If the information needed to streamline the management of exceptions is not centralised—with data from different source systems connected via unique identifiers such as vendor ID, account code and customer name—then it cannot be leveraged seamlessly to automate payment processing.
Furthermore, a lot of content is available only as paper, PDF, image, etc. That content must be scanned to have critical data elements—such as the date, account number or amount—electronically captured and metadata created. Then, and only then, the content can be indexed and stored in a repository and database. From there, the invoice and associated supporting content can be linked and processed via workflow.
Some automated A/P solutions can integrate myriad information and content formats with their data repository. It’s important to confirm the solution you select can, in fact, cover formats such as Microsoft Word and Excel, PDF, email, video, scanned capture documents—and uses a variety of standardised methods to exchange information in electronic formats (e.g., XML, JSON and EDI). They should also intelligently index, archive and organise this content so that users can easily find and access necessary information. An effective automated A/P platform also includes auditing and reconciliation capabilities, which alert users to errors such as duplicate, short or delayed payments.
Centralisation entails storing all critical accounting documents related to A/P in a single place. However, in even the most streamlined enterprises, these documents still touch several different systems. Some documents are stored in an ERP system or a content-collaboration platform, but other crucial information often resides on paper, in sales contracts, on inspection certificates or elsewhere. Disparate systems that function independently and without effective integration only prolong accounting processes.
To be most effective, the payables software solution must be able to communicate with all core systems that house relevant documents. If it can’t, records can become “lost in the loop” and put the organisation at risk. To prevent this, any A/P automation solution should integrate with the company’s content services platform (CSP) and ERP systems. Integrating systems and federating content across them leads to substantially reduced processing times.
A/P-related systems aren’t the only software in the company that contains information relevant to A/P processes. Marketing, customer service, operations, manufacturing and legal, among other major departments, have some bottom-line impact on business operations.
Because A/P staff spend most of their time dealing with transactions that are not PO-based or with PO exceptions like mistakes in amount, quantity, price, payment terms, etc., having this information is critical to their effectiveness. And although this information exists in other departments, it is rarely made readily available to A/P to use when resolving exceptions.
Automated A/P solutions can centralise enterprise content beyond the documentation that is typically considered central to payables processes. When evaluating solutions, assess if the system uses standards-based REST APIs, low-code web-hook enabled content-centric workflows and content federation to access content stored in repositories used in other parts of the organisation. This approach will improve transparency and yield improved cost savings within A/P and the broader supply chain.
Reaping the Rewards
When a company is able to tighten its A/P processes, the entire business reaps the rewards. It eliminates the processing delays that result in inaccurate reporting, poor financial visibility, delayed business decisions, costly reruns and wasted money. It also allows money to flow into and out of an organisation faster. According to IOFM, organisations that apply A/P automation best practices can pay their non-PO invoices on time 96% of the time, compared to only 13% of those that are less automated.
The key to enabling that is to capture, manage, federate and audit content across the entire organisation and ensure systems work in concert across different departments and applications. Only with that centralisation, integration and unification can a company make more-informed business decisions and improve cash flow for the near and long term.
RISK VS REWARD: IS AI TAKING OVER?
Xavier Fernandes, Analytics Director at Metapraxis
A study by Oxford University academics into “The Future of Employment” in 2013 prompted apocalyptic headlines which stated that in the future 40% of jobs will be automated thanks to advancing technology.
The researchers subsequently claimed that the truth was in fact a little more prosaic; rather than facing complete automation, the research found that 40% of jobs faced some aspect of automation in their activity. So with new ‘AI processes a likely reality for almost half us, what does that mean for our current roles and should we be worried?
The fourth revolution?
The first industrial revolution saw machines replacing muscle, both human and animal. The second and third saw electrical power, mass production and computerisation revolutionise the job market. Now, with daily headlines of AI as an employment superpower, there is some concern that AI is bringing a fourth revolution, and with it, unknown circumstances.
This ‘fourth industrial revolution’ is defined by replacing brain power with machines. Our thinking capacity is what inherently sets us apart from other species, so it’s not surprising that any encroachment on it triggers some existential angst.
Evolve to reap the rewards
While many businesses still don’t fully understand the capabilities of AI, those who fear its development are, instead of embracing it, missing all the benefits that it can bring to the workplace. Businesses that utilise AI appropriately are seeing vast improvements across their entire value chain; better customer experience, reduced costs, and more insightful analysis to support management decisions.
AI is particularly useful for supporting tasks with repetitive activity, for example, performing financial checks and assessing large sets of data within financial services firms. AI performs particularly well within this context, spotting outliers before a human expert would notice them, allowing impending problems to be flagged and avoiding costly mistakes.
There is also an increasing focus on maximising customer lifetime value through the use of AI. Being able to predict existing customers’ needs as well as track trends in their financial circumstances is supercharging the old cross-selling approach with testable, predictable outcomes.
With potential benefits like these on offer, management teams of innovative financial services are increasingly relying on AI to help them with some of the heavy-lifting of analysis. Using advanced data capabilities and learned behaviours, AI analyses market trends to provide predictions of future performance. This insight is invaluable and allows management teams to change direction and correct any problems accordingly. This offers a huge advantage over those that have not adopted such tools.
Supporting the workplace
Algorithms and AI are typically ‘smart’ at doing one, tightly-constrained task, but they can be less helpful with many of the activities that humans find straightforward. In most white-collar jobs, automation tends to replace certain tasks in the job, rather than the role in its entirety, as the need for human intelligence is still highly necessary. In particular, we still need human input to first challenge, and then synthesise, this information before taking action. Employees should therefore work with the business to proactively identify what areas of their role could be automated, so that they can focus on the areas that add real value to the business’ commercial goals.
Challenging AI is certainly still important. We know that algorithms can be much better than humans on certain, bounded tasks. However, many algorithms rely on existing data sets to build their understanding. As a result, when a business unit has ‘symptoms’ that fall outside of that body of knowledge, the algorithm may suggest the wrong course of action with costly results.
Indeed, even with plenty of data, algorithms will reflect any biases the data set contains. We’re seeing this with some legal sentencing algorithms where there is evidence that they are treating disadvantaged people more harshly. Getting the answers to why and how far we should trust our algorithms should therefore become an everyday part of any job affected by AI.
Rather than depending entirely on AI for all decisions, workers should be taking all these new, AI-generated insights and using them to complement the human decision-making process. No manager of a complex business ever has enough time to sieve through all the analysis available, but with AI driven algorithms able to flag up any issues and indicate where action needs to be taken, we may find that we have some AI ’colleagues’ who will cover our backs and suggest innovative options. Yes, there will be times when the algorithms get it wrong, but as long as we’re watching out for those, the future is bright.
HOW TECHNOLOGY IS FUTUREPROOFING STOCK MARKET TRADING
Tony Shaw, Executive Director, London Office and Head Sales UK & Ireland at the Swiss Stock Exchange
Markets are shifting, there’s no doubt. Amid all the disruption and volatility from the past year, the Swiss Stock Exchange asked traders about what they expected in 2020 and beyond in our industry survey. The findings point to a rise in digital to help traders content with external forces.
First and foremost, traders are enthusiastic about what digital assets can offer.
Two thirds of traders polled said they’d had a marked rise in interest from their clients for digital assets and crypto-products. Given the interest, traders are increasingly bullish about the potential of these products – so much so that 80% have predicted an increase in overall demand in the long term. Market users believe these assets will help generate cost synergies and streamlining trading and settlement processes by creating efficiencies and ultimately reducing costs.
Our 2019 results reflect what traders have told us when it comes to digital assets and products. Last year, we saw significantly higher trading volumes from products with crypto currencies as underlyings. Overall volumes grew by +8.5% over 2018, but the increase in crypto products alone was +17%, reaching CHF 518.2 million ($534.54 m). There was a year-on-year increase in the number of transactions, as well (+21%): 19,636 trades in total.
The potential digital assets hold is clear – evidenced by the building of the SIX Digital Exchange (SDX), a fully integrated issuance, trading, settlement and custody infrastructure for digital assets.
According to traders, artificial intelligence (AI) is expected to bring further benefits to market operations.
Two thirds of our survey respondents anticipate AI will create more opportunities for the traditional equities business, while a similar number expect it to reduce the cost of trading. Innovation in AI is already – and will continue to be – a key driver in making our industry more effective at withstanding future risks and challenges both within and beyond the market itself.
In Europe, there is growing momentum behind calls for shorter trading hours – this trend was reflected in our survey as well.
Industry groups such as the Investment Association are advocating for stock market trading hours to be cut from 8.5 to 6.5 hours to open the industry to working parents and women who cannot commit to such long workdays. We found traders were largely supportive of this, with many saying that it could even facilitate operational benefits. The roll of AI is clear here in improving efficiency while minimising time wastage: 36% of traders said the introduction of shorter trading hours would prompt greater market liquidity.
Beyond the market itself, geopolitics continue to shape wider market sentiment.
It comes as no surprise that four fifths of traders said their strategies have been – to some extent – influenced by Donald Trump’s tweets. Interestingly, only 39% of those polled viewed Brexit as an influencing factor in trading activity, while three quarters believe the US election will drive trading activity in 2020 and 65% acknowledged trade wars would also have an impact.
More broadly, traders are split on the state of the global economy – 58% are bracing for a global recession while 42% predict stable macro-economic conditions over the next three years. What seems clear is that whatever happens in the wider economy, traders are making headway with new technologies that can improve their strategy, efficiency, and overall market health.
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