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CHECK, PLEASE! ADDING UP THE COSTS OF A FINANCIAL DATA BREACH

Reliance on email as a fundamental function of business communication has been in place for some time. But as remote working has become a key factor for the majority of business during 2020, it’s arguably more important than ever as a communication tool. The fact that roughly 206.4 billion emails are sent and received each day means we’re all very familiar with that dreaded feeling of sending an email with typos, with the wrong attachment, or to the wrong contact. But this can be more than just an embarrassing mistake – the ramifications could, in fact, be catastrophic.

In particular, for the financial services industry that deals with highly sensitive information including monetary transactions and financial data, the consequences of this information falling into the wrong hands could mean the loss of significant sums of money. Emails of this nature are the Holy Grail for cyber criminals. So how can financial services organisations keep their confidential information secure to safeguard their data and reputation? Andrea Babbs, UK General Manager, VIPRE, explains.

 

How much? 

According to research from Ponemon Institute in its Cost of a Data Breach Report 2020, organisations spend an average of $3.85 million recovering from security incidents, with the usual time to identify and contain a breach being 280 days. Accenture’s 2019 Ninth Annual Cost of Cybercrime found that financial services incurred the highest cybercrime costs of all industries. And while examples of external threats seem to make the headlines, such the Capital One cyber incident, unintentional or insider breaches don’t always garner as much attention. Yet they are both as dangerous as each other. In fact, human errors (including misdeliveries via email) are almost twice as likely to result in a confirmed data disclosure.

Costs will be wide ranging depending on the scale of each breach, but at a minimum there will be financial penalties, costs for audits to understand why the incident happened and what additional protocols and solutions need to be implemented to prevent it from happening in the future. There could also be huge costs involved for reimbursing customers who may have been affected by the breach in turn.

 

Priceless damage

The fallout from data breaches goes far beyond that of financial penalties and costs. Financial services businesses have reputations to uphold in order to maintain a loyal customer base. Those that fail to protect their customers’ sensitive information will have to manage the negative press and mistrust from existing and potential customers that could seriously impede the organisation as a whole. Within such a highly competitive market, it doesn’t take much for customers to take their money elsewhere – customer service and reputation is everything.

 

Check, please!

Within the financial services sector, the stakes are high, so an effective, layered cybersecurity strategy is essential to mitigate risk and keep sensitive information secure. With this, there are three critical components that must be considered:

  1. Authentication and encryption: Hackers may try to attack systems directly or intercept emails via an insecure transport link. Security protocols are designed to prevent most instances of unauthorised interception, content modification and email spoofing. Adding a dedicated email to email encryption service to your email security arsenal increases your protection in this area. Encryption and authentication, however, do not safeguard you against human errors and misdeliveries.
  2. Policies and training: Security guidelines and rules regarding the circulation and storage of sensitive financial information are essential, as well as clear steps to follow when a security incident happens. Employees must undergo cyber security awareness training when they join the organisation and then be enrolled in an ongoing programme with quarterly or monthly short, informative sessions. This training should also incorporate ongoing phishing simulations, as well as simulated phishing attacks to demonstrate to users how these incidents can appear, and educate them on how to spot and flag them accordingly. Moreover, automated phishing simulations can also provide key metrics and reports on how users are improving in their training. This reinforcement of the security messaging, working in tandem with simulated phishing attacks ensures that everyone is capable of spotting a phishing scam or knows how to handle sensitive information as they are aware and reminded regularly of the risks involved.
  3. Data loss prevention (DLP): DLP solutions enable the firm to implement security measures for the detection, control and prevention of risky email sending behaviours. Fully technical solutions such as machine learning can go so far to prevent breaches, but it is only the human element that can truly decipher between what is safe to send, and what is not. In practice, machine learning will either stop everything from being sent – becoming more of a nuisance than support to users – or it will stop nothing. Rather than disabling time saving features such as autocomplete to prevent employees from becoming complacent when it comes to selecting the right email recipient, DLP solutions do not impede the working practices of users but instead give them a critical second chance to double check.

It is this double check that can be the critical factor in an organisation’s cybersecurity efforts. Users can be prompted based on several parameters that can be specified. For example, colleagues in different departments exchanging confidential documents with each other and external suppliers means that the TO and CC fields are likely to have multiple recipients in them. A simple incorrect email address, or a cleverly disguised spoofed email cropping up with emails going back and forth is likely to be missed without a tool in place to highlight this to the user, to give them a chance to double check the accuracy of email recipients and the contents of attachments.

Finance

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.

 

Predictive power

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.

 

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Finance

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

Krishnan Raghunathan

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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