By Gabe McGloin, Head of International Merchant Sales & Business Development, Verifi
Chargebacks have existed since the early days of distance selling – the predecessor of e-commerce. Mail-in catalogues and Avon ladies were some of the earliest ways consumers could purchase products and wait for them to arrive at their door. Chargebacks have been a part of this cycle since just after the Consumer Credit Act of 1974. From missed deliveries to damaged goods, people will push for their money back when the customer promise is broken. And chargebacks afford customers this protection. However, modern technology may have tipped the scales too far toward the customer, at the expense of merchants.
Retail has evolved dramatically from those early days. We live in an omnichannel universe where buying and selling happens across diverse platforms and in many different ways. However, chargebacks have remained mostly unchanged from the distance selling era. They are the last remaining dinosaur of old payments processing to survive into the 21st century.
Chargebacks are now causing merchants more trouble than ever. The ease of online and card payments has made challenging a transaction or demanding the refund of a payment second nature for consumers, with merchants bearing the burden of proving the transaction valid. Yet, it doesn’t have to be this way. By collaborating and sharing data, merchants and issuers can resolve many disputes before they turn into a full-blown chargeback.
Nipping it in the bud
Chargebacks represent a growing black hole for merchants, costing them $19 billion each year. Once a chargeback gets underway, there’s little that can stop it. Merchants must comply, completing all processes and admin required – which represents 60% of the amount they lose in operational costs alone. The best way to manage chargebacks is to stop them before they begin.
Chargebacks are an accepted part of the payments ecosystem, but they’re far from being the only recourse. A transaction disagreement can begin at many different points of the customer journey. If a customer calls the issuer to inquire about a purchase they don’t recognize, this presents an opportune time to solve the problem. The issuer can quickly review the transaction details to confirm a valid sale or prevent an attempt at friendly fraud, and avoid the dispute.
At the beginning of the post-transaction life cycle, communication and collaboration are essential to prevent pre-disputes from escalating. With the right information supplied to the right party at the right time, chargebacks can be avoided.
However, the reality is that many transaction disagreements continue to progress and become chargebacks, due in large part to a simple lack of collaboration. This is especially true in situations where the process begins as a result of customer confusion rather than a grievance – such as a forgotten transaction or poor descriptors on a credit card statement. It’s here, usually, that the issuer is lacking the detailed transaction data and is obliged to initiate a chargeback. It’s at this moment that the administrative burden of chargeback representment begins for the merchant.
A smarter approach to dispute resolution
It doesn’t have to be this way. The problem in many cases can be solved at the pre-dispute stage, stopping the chargeback from being officially filed. This is the point at which the customer first contacts their issuer to raise a question or concern with a transaction.
From here, disputes can go one of two ways. One, disputes can be avoided if the issuer can detect friendly fraud or provide the customer sufficient clarity to validate the transaction. Or two, the customer wishes to move forward with filing the chargeback, and the merchant is left to decide whether to accept liability for the chargeback or represent it.
Fortunately, existing technology can make avoiding the lengthy process of a chargeback easier. Pre-dispute solutions currently in the market can prevent and resolve disputes before they escalate to costly chargebacks. Such systems automatically share merchant transaction details with issuers and their customers as soon as a payment is queried. If a consumer calls their bank to question an unrecognised purchase, then the representative can quickly review the transaction details to confirm a valid sale, thereby avoiding an unnecessary chargeback.
When the dispute isn’t caused by a misunderstanding, merchants and issuers can still work together to accelerate resolution and avoid a chargeback. Through logic-driven programming, rules can be set to initiate a full, automated refund if certain parameters are met. Another solution actually provides a window of time where the merchant can review the transaction data and reason for the dispute before deciding to resolve it or not. Regardless, the operational impact of a chargeback can be avoided, and all parties enjoy a quick resolution.
Quick visibility of transaction details can prevent unnecessary disputes. However, it’s important to stress that these resolutions depend on the free flow of data between issuers and merchants. Both parties suffer during the chargeback process, so the impetus is there – all that’s needed is for issuers and merchants to implement existing communication channels for the exchange of detailed transaction data.
When connected to a common, existing dispute resolution network, issuers and merchants can work together, sharing transaction data and resolution parameters to head off disputes at the pre-dispute stage. This collaboration can result in one of three outcomes: One, the customer will understand the transaction was valid and is happy to not move forward with the chargeback. Two, the customer will be presented with such compelling evidence that they rethink proceeding with friendly fraud. Or three, if the customer does move forward with the chargeback, then the merchant can simply refund the customer to avoid the negative impacts of a chargeback whether or not the transaction is true fraud or not. All three solutions require collaboration, but ultimately work out better for all stakeholders in the transaction.
Chargebacks are not heading for extinction any time soon, but pre-dispute solutions can help prevent many from ever existing. These pre-emptive measures are available currently and enable merchants and issuers to work together to create a path towards resolution. By using pre-dispute solutions merchants can not only protect themselves but also preserve the customer relationship and secure the future of their business.
MASTER YOUR DATA: TACKLING CUSTOMER RETENTION CHALLENGES IN FINANCIAL SERVICES
Helena Schwenk, Market Intelligence Manager at Exasol
Customer retention has always been crucial to financial institutions (FSIs), with the majority (80%) of senior FSI decision-makers in our recent survey affirming customer loyalty as a key priority.
However, the truly unprecedented and unforeseen events of 2020 have created a fluctuating backdrop of behavioural shifts and economic constraints that has amplified the value of robust customer relationships. In this increasingly digital-first world, where face-to-face interactions — often the best way of building trust with customers — have been further reduced by the impact of the pandemic, FSIs are left hunting for new avenues and ideas. As McKinsey testifies, nowhere is this more important than in retail banking.
As more customer interactions shift online, the market is flooded with new digital products and services from digital disrupters whose agile and diverse digital sales and marketing strategies, amplify the challenge of digital transformation for more traditional legacy FSIs.
We’ve become used to the new challenger banks disrupting and transforming the retail banking sector but interestingly the pandemic has actually seen a renewed consumer interest in traditional brands. I recently hosted a podcast on the topic of data leadership in financial services. One of the key takeaways from that discussion is the way the pandemic has heightened customer’s focus on trust and confidence, which has seemed to favour traditional banks and created customer loyalty consequences for challenger banks.
To find competitive advantage and move their digital business forward, FSIs of all types must unlock the true potential of their data. Thanks to its large number of customer touchpoints, the financial services industry generates an especially high volume of data. Handled well this data is enormously empowering. But high data intensity and the prevalence of data silos, means that poor attempts to manage and use data often create more problems than they solve.
Mastering financial services data to drive customer loyalty ultimately requires FSIs to focus on data analytics as a means to better connect their data and uncover the valuable insights needed to improve business operations, develop new products and services and, crucially, enhance their customer experience.
The challenges of customer loyalty
According to Bain & Co, the value of customer loyalty is exponential. Increasing customer retention by as little as 5% can boost profits by up to 95%. That said, no attempt to reinforce customer relationships is ever easy.
More than half (54%) of respondents in our survey believe customers have higher expectations around their experience when interacting with FSI organisations. This makes loyalty increasingly difficult to earn and maintain. Strict regulations such as PSD2 and GDPR also impact FSIs ability to develop and improve customer loyalty initiatives according to 41% of respondents.
These loyalty challenges if not successfully addressed have consequences: the impact on lost opportunities for customer engagement and advocacy; lost revenue generating opportunities; and higher levels of customer churn are significant. This last point is particularly pertinent considering that, according to Invesp, the cost of acquiring a customer is five times more expensive than selling to an existing one.
Therefore, one of the key areas where data and analytics can benefit customer loyalty initiatives is by giving a deeper understanding of customer lifetime value and allowing organisations to interpret and measure the loyalty of customers and predict customers’ future behaviour. Data analytics also allows FSI to actively identify clients at risk of attrition by using behavioural analytics to generate personalised customer action plans – which they can then choose to implement, tailored to the client’s specific needs.
Signs of maturity
Overall, there are encouraging signs of maturity in terms of FSIs adoption of data analytics compared to other industry sectors. Our survey found 97% of FSIs using predictive analytics to help them drive better customer insights and loyalty initiatives, with three fifths (62%) using it as a key part of these programs.
However, the data shows UK FSIs lagging behind their US counterparts. In the US 93% of FSI’s departments have embraced data analytics, with over half of these (51%) encompassing the entire workforce; however, in the UK only 37% of the workforce is fully embracing data analytics.
Clearly there’s much room for improvement when it comes to fostering a data-driven
culture in FSI organisations. Research by McKinsey also supports this trend. It found that despite more than half of the banks it surveyed having analytics is a strategic theme, the majority struggle to connect the high-level analytics strategy to a targeted selection and prioritisation of use cases, and to implement them in an orchestrated way. This is understandable. As FSIs step up their sophistication in data analytics, the skills and demands required mean that some struggle or are challenged to leverage them effectively.
The biggest challenge FSI organizations face when implementing data/analytics into customer loyalty initiatives is most commonly their inability to use advanced analytic methods for their desired analyses and activities and/or a lack of access to external and more detailed customer data. By adopting better analytics tools and a more progressive data strategy and culture FSIs can access data that was previously unattainable.
If 2020’s pandemic has made one thing clear, it’s that business conditions can flip very quickly, meaning the infrastructure to support fast decision-making needs to be more responsive than ever. Adapting and innovating to provide products and services that customers need during these uncertain times, using insights to de-risk and accelerate offerings helps to secure their loyalty now and beyond.
Revolut’s data revolution
Revolut is a disruptor bank that’s showcasing the growth potential of a truly data-driven organisation. As one of the biggest players in the crowded fintech ecosystem it has approximately 13 million global users, meaning it has large datasets from several sources. In order to achieve incredible granular personalisation for its customers it needed to reduce the time it took to analyse all this data.
In fact, Revolut’s data volumes had increased 20-fold in the space of one year, which coincided with the need to maintain circa. 800 dashboards and 100,000 SQL queries every day across the business. Action needed to be taken to support its need for a flexible, hybrid cloud environment data analytics platform.
With an in-memory data analytics database as a central data repository, time is now saved across multiple business departments with queries and reports completed in seconds rather than hours. As a result, Revolut has experienced query rates that are 100 times faster than its previous solution – greatly improving decision making processes.
Analysing large datasets spanning several sources drives customer experiences and satisfaction. The business can now define tens of thousands of micro-segmentations in its customer base with the ability to explore payments data, debit card statements, customer demographics, mobile transfers and transaction and point of sale. It’s also seeing an increase in sales and customer retention as this has led to ‘next product to purchase’ models being built according to this unique insight.
Importantly, it’s not just data scientists that have access to the central data repository either, but everyone in the organisation. Key performance indicators (KPIs) for each team are constructed on this data too, meaning every employee has an understanding of the company’s goals, performance and progress, and can see industry trends and insights based on the data, which they can act upon.
With customers able to choose between tech giants, mobile-only banks and well-known financial institutions that have been around for well over a century, data has an incredibly important role in how all of these organisations can attract and retain customers and strengthen their loyalty through great user experiences, tailored products and innovative services.
Financial services organisations can gain competitive advantage during these challenging times with a progressive data strategy that operationalises and governs data, and empowers users to make fast, informed decisions.
The path to success is the same for challenger or legacy banks – provide services in a clear, timely and satisfying way for customers.
Underpinning this has to be the right analytics database that can support your needs, regardless of whether you store your data in the cloud, on-premise or in a hybrid environment. This is central to knowing your customers better and predicting and detecting customer trends to improve experiences. In turn, this will increase customer loyalty.
DIGITAL FINANCE: UNLOCKING NEW CAPITAL IN DISRUPTED MARKETS
Krishnan Raghunathan, Head of Finance & Accounting Services at WNS, explores how a digitally transformed finance department can give enterprises the ability they need to improve cash flow and revenue through better use of data and improved analytics-driven visibility.
Businesses everywhere are scrambling to recover lost revenues and protect cash flow. But as countries globally grapple with a dreaded second wave of the pandemic, imposing far more stringent localised lockdowns and new restrictions, it is set to be the hardest winter in living memory for many sectors.
The likelihood of winter peaks, so often the saviour of sectors such as travel and hospitality, benefitting businesses is diminishing rapidly. While many have pivoted to a greater or lesser degree, few have been able to offset the impact of falling revenues on cash flow. Even retail, riding an e-commerce boom in many regions, is finding itself in choppy waters, with 17 percent of consumers switching brands due to the economic pressures and changing priorities caused by the pandemic.
As one McKinsey article notes, “With some companies losing up to 75 percent of their revenues in a single quarter, cash isn’t just king – it’s now critical for survival”. Where then do businesses find new sources of cash to sustain their operations through the coming months?
Tapping Overlooked Cash Opportunities
For many, the answer could depend on whether they have digitally transformed their finance department. Why? Because many organisations are sitting on unidentified opportunities, funds that could be vital in shoring up businesses over the next few months or plugging the gap between operating costs and government bailouts. Yet those that have been slow to start their digital transformation journey are at a disadvantage;. At the same time, it is possible to identify these hidden seams in an analogue organisation, the process is time-consuming, manually intensive and, without the right digital tools, prone to human error.
Where deploying digital tools helps is by bringing speed, automation and reliable data to the fore. Connecting them with digital finance and accounting systems can give businesses clear insights into how money is being spent, where wastage is occurring, and where opportunities for optimisation exist.
It might be something as simple as automating the accuracy checking, issuing and chasing of invoices and late payments. This could reduce errors and invoice disputes and ultimately lead to faster payments. Accuracy and organisation are also important in billing – better records enable faster billing for work completed, and in turn, should deliver quicker payments.
It could also be around having the ability to review the supply chain and procurement data and identify where a supplier is subsidising a larger customer’s product line through drawn-out payment terms, or where a variety of vendors are on different terms across the business. Using that data and overall knowledge of the business to negotiate better terms that work for both supplier and customer can create new opportunities. It could even be to identify late-paying customers, determine the reason for late payments, and use that intelligence to develop products or financing solutions that continue to support those customers (and improve loyalty) without increasing the burden on the balance sheet.
Generating Reliable Insights for Faster Decision-making
To do any of these manually would take months, generating data slowly that would quickly go out of date. But digital finance departments have evidence they can trust to inform business decision-making. That’s because old, manual processes built around Order-to-Cash lack the flexibility and agility that businesses require in today’s markets. The fact is that even before the global pandemic crisis, the pace of digitisation across all sectors was demanding new approaches to finance and book balance.
The opportunities are significant – from cognitive credit and improved forecasting accuracy to enhanced customer analytics. All use similar tools, based on artificial intelligence and quality, trusted data. Cognitive credit can be deployed to quickly make decisions on whether to advance or restrict credit, based on individual company positions and available data. Doing so enables businesses to either capitalise on opportunities (for instance, agreeing credit for a supplier that has run out but is a supportive and integral partner) or avoid risk (in the cases where a business might be in administration).
With more accurate forecasts, businesses can better manage their currency purchases and deposits, selling currency that is not required or buying more where predictions identify an upcoming demand.
It is the same with customer analytics – with a greater understanding of customer needs, businesses can make decisions based on the right mix of the product (and how it meets demand) and supply chain suitability (such as production costs and location in relation to customers).
In many ways, the events of the past year have accelerated the process. In doing so, the problem is the pandemic has also accelerated the speed at which failure to act can lead to obsolescence. Therefore, it is vital that businesses, and more particularly their finance and accounting departments, kick start their digital transformation. This will enable them to deploy the tools and analytics that is needed to capture data, generate insights and drive fast, accurate decision-making to uncover previously untapped sources of cash and reverse revenue degradation.
The Importance of Digitally Enabled Finance Teams
Forward-thinking CFOs have already begun the process of digitising their departments, but for those that have been slow to start, now is the time to push forward. It is only through digital tools and analytics that finance leaders can identify both the internal and external opportunities to recover revenue and improve cash flow. Whether that’s releasing working capital, minimising revenue loss and accelerating revenue recovery, reducing total cost of ownership or enhancing customer retention – only digitally enabled finance teams will be in a position to capitalise and, ultimately, bolster business performance during what will be a trading period like no other.
About the author: Krishnan Raghunathan
Krishnan Raghunathan is the head of Finance & Accounting (F&A) practice and operations at WNS. He also leads the international delivery locations in China, Costa Rica, Spain, Sri Lanka, Romania, The Philippines, Poland and USA.
Prior to this, Krishnan was Chief Capability Officer for WNS, in that role he headed Horizontal practices across Finance & Accounting, Customer Interaction Services and Research & Analytics, Transformation & Process Excellence, Program Management (Transitions) and Solutions development.
He has more than 27 years of experience across Finance & Accounting, Business Process Management, Sales Solutions and Capability functions including 7 years in Accounting practice.
Before joining WNS in 2013, Krishnan led several challenging roles at Genpact, supporting strategic deals and consultative selling. In addition, Krishnan was also the business leader for a number of industry verticals at Genpact, including hospitality, transportation, logistics, media and professional services
Krishnan is a Chartered Accountant, a Certified Six Sigma Green Belt and a trained Six Sigma Black Belt
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