By Fabrice Martin, Chief Product Officer, Clarabridge
When a bank or financial services company directly uses customer feedback to make decisions at the executive level, it’s almost as if that company has given its customers a seat in the boardroom; however, just because a business is open to using customer feedback in this way doesn’t mean it has successfully done so.
Companies may think they’re listening to “Voice of the Customer (VoC) data,” but they must make sure their information is truly representative of the customer voice. Failure to address this subtle yet critical nuance can result in an organisation making decisions based on a limited understanding of the customer perspective.
If a company uses misleading data to make important business decisions, it will not be able to understand what the customer really wants. This reality can have devastating effects on a business’s ability to maintain a compelling value proposition and can put it at a disadvantage if competitors succeed in more effectively using the data.
To mitigate the risk of failing to consider customer input, businesses must first understand why certain metrics may be misleading and then understand how to turn accurate insights into action.
Understand when the data doesn’t show the full picture
Many executives in the financial services sector believe that relying on metrics such as NPS or CSAT provides a comprehensive view of the customer experience. In fact, an article in the Wall Street Journal states that the term “net promoter” or “NPS” was cited more than 150 times in earnings conference calls by 50 S&P 500 companies in 2018. But, as the WSJ article points out, this statistic fails to tell the entire story.
By relying on a single metric to capture the complexity of the end-to-end customer experience, senior executives can miss important data that impacts the bottom line. Businesses often measure NPS through surveys, but the results only reflect the views of those actually completed the survey and may be more likely to reflect the perspectives of those who had an especially good or bad experience. Therefore, the findings may not represent the views of customers outside of those categories, causing the company to overlook a potentially huge portion of its customer base and sacrifice relevant insights that could increase profit.
While executives may be mentioning NPS frequently, a sole reliance on this metric offers a very shallow and incomplete picture of how customers actually feel.
Listen to multiple sources of data
In order to broaden the types of metrics used to examine the customer experience, companies must look beyond the survey. Customers are using a variety of channels such as email, chat, calls, surveys and social media to interact with banks and financial institutions regarding issues ranging from checking an account balance to arranging a mortgage. They’re also sharing their experiences and communicating with other customers on blogs, forums and review sites. Regardless of the channel, it’s imperative that customer-centric organisations analyse them all.
By including feedback from multiple channels, businesses can access the unsolicited feedback their customers are offering and review insights that reflect both structured and unstructured data.
Through the process of analysing multiple sources of data, companies can ensure that the voices of all their customers are heard.
Integrate findings and enrich your insights
Once a company establishes a process for ingesting feedback from a variety of channels, it must integrate the findings from those sources. By looking at a single, aggregate view of the data, the business can begin to identify the areas where customers are satisfied and those which they feel need improvement. Then it can begin determining recommendations and action items.
Using this approach, a large banking customer determined that customers were finding one of its investment options to be confusing, and employees were also unclear about the product offering. The company promptly updated the employee training process and rewrote the product brochures to eliminate confusion and drive product adoption.
This example illustrates the importance of considering metrics beyond NPS and CSAT when identifying opportunities to create a better customer experience. It’s necessary to enrich the data by measuring characteristics such as sentiment, effort and emotion to really understand the entirety of the customer experience.
Insight into customer engagement, emotion, effort and sentiment also serves as a strong predictor of loyalty, which is vital for any bank. For example, research from Gartner shows that solving problems quickly and easily is the most successful way to build customer loyalty. The research also shows that 94% of customers are likely to repurchase after a low effort experience. By enriching the data and examining more nuanced measures of CX, companies can begin looking at the leading indicators of loyalty and satisfaction instead of the lagging ones.
Demonstrate a willingness to act on insights
After identifying accurate insights, banks and financial services organisations must act upon that information. By listening to customers at all touchpoints and integrating the findings, they’ve already taken the first step toward giving the customer a seat in the boardroom; however, it’s imperative that they demonstrate their commitment through action.
By putting a spotlight on initiatives that highlight the insights-to-action process, companies will encourage customers to trust that they are truly listening. This technique will also add an element of authenticity to the brand by sending the message that the company cares. It’s important for the business to incorporate some degree of visibility into the process and communicate its efforts to customers in order to enjoy maximum business and brand benefits while creating a better CX.
It’s always more effective to show customers that a business cares than it is to simply tell them, and customers will show their appreciation with revenue and loyalty.
To truly give customers a seat in the boardroom, banks should look beyond basic metrics, consider data from every channel, integrate findings and act upon the information. If an organisation follows these steps, it will make significant progress toward improving the customer experience.
STOP THE CONFUSION: HOW TO KNOW IF YOUR BUSINESS MAY BE INSURED AGAINST COVID-19
By Alex Balcombe, Partner at Harris Balcombe
The last few weeks has seen businesses in hospitality, tourism, retail, leisure and more forced to close their doors following the Government’s orders that they should close to prevent the spread of coronavirus.
While this is expected to flatten the curve and reduce the number of coronavirus cases, it will of course have an impact on businesses and employees alike. For small businesses especially, there are many concerns about how they can claim on their insurance to weigh the fall of this impact.
In response to calls to help struggling businesses, the Government has informed the public that companies who are facing turmoil will be able to claim on their business interruption insurance during this difficult time. For most, this is wrong.
The insurance industry has also been extremely vocal that there is no cover for any coronavirus-hit businesses during this tough financial period. This isn’t strictly true either.
How can businesses see through the mixed messaging and best secure their future and their livelihoods and reduce money worries? It’s an extremely stressful time for many companies, and confusion over whether or not they can be covered can only cause more unnecessary stress.
Since it’s a new disease, most businesses will not be covered for business interruption due to COVID-19. In fact, the vast majority of policies do not cover anything related to COVID-19.
That said – don’t rule out the idea that you may be covered. There is a chance that you will be covered against COVID-19, but not know it. This is a very small chance, but your current cover may already protect your business against the consequences of coronavirus, and the nationwide response to it – though those with this cover are unlikely to realise it.
How Could I Be Covered?
Not everyone has business interruption insurance, as it’s not a legal requirement. It is entirely up to the policy holder to weigh up the benefits of having it, and their ability to trade should a disaster happen.
To be considered for cover for COVID-19, there are two types of policy extensions to your business interruption cover that can potentially cover you for this situation:
Infectious Disease Extension
Many policies expressly state which diseases fall within the realm of being an infectious or notifiable disease. If this is the case, your policy will not provide cover. As it is a new disease, these policies will not have included COVID-19.
Other infectious disease extension policies will define the disease with reference to the actions of the government. Since the UK Government has named COVID-19 as a notifiable disease throughout the UK, it is possible that your business may fall into this definition, thus meaning you may be able to make a claim.
However, again, it’s not always that simple. Many policies require the disease to have been on your premises, while others specify a radius from your premises in order to qualify.
Denial of Access Extension (non-damage)
Denial of Access Extension (non-damage) policies may cover you if you’re prevented from accessing your property. This could be due to an event, or by the actions of a competent authority, which could cause your business interruption cover to engage.
If covered by this clause, there are often very subtle differences in wording in your policy. This could depend on the insurer or policy. You may well be covered, but it will depend on your particular circumstances, and the specific policy wording.
It’s clear that the Government needs to do more in ensuring there is clear messaging for businesses, and to help the insurance market look after policy holders. This is an unprecedented situation, and with many people looking to claim on their insurance, we’re already seeing major delays which could have a domino impact.
People throughout the world are understandably facing all kinds of worries because of the current pandemic. Our ways of living have changed, and many business owners will not have experienced a situation like this in their life times. If you own a business and are unsure about whether you can claim for business interruption, or are confused about ambiguous wording, get in touch with a loss assessor.
These claims are not simple, but loss assessors will be experts in business interruption insurance, and will specialise in large and complex claims. They will be able to help and guide you along the way, check your wording and work on your behalf to make sure you get everything you are entitled to.
HARNESSING ANALYTICS IN THE FIGHT AGAINST FRAUD
By Anna Lykourina, EMEA Fraud Analytics Expert at SAS
In the past, the fight against fraud has been a bit hit-and-miss. It has relied on auditors to identify patterns of behaviour that just didn’t quite fit. They often only detected problems months after the event. And then organisations had to claw back stolen funds through legal processes.
In a world where transactions happen in under a second, however, this is no longer acceptable. We need to be able to detect fraud immediately, if not before it happens. Customers want safe and protected data that is not vulnerable to identity theft through company systems. But they still want to be able to pay online and in seconds. The stakes are high, but fortunately new tools and techniques in fraud analytics are enabling companies to stay ahead of fraud.
Trusting machines to do the work
Machines are much better than humans at processing large data sets. They are able to examine large numbers of transactions and recognise thousands of fraud patterns instead of the few captured by creating rules. On the other hand, fraudsters have become adept at finding loopholes. Whatever rules you set, it is likely that they will be able to get ahead of them. But what if your system was able to think for itself, at least to a certain extent?
New approaches to fraud prevention combine rules-based systems with machine learning and artificial intelligence-based fraud detection systems. These hybrid systems are able to detect and recognise thousands of fraud patterns and learn from the data. Automated analytical-based fraud detection systems can reveal novel fraud patterns and identify organised crime more consistently, efficiently and quickly. This makes them a good investment for businesses across a wide range of sectors, including public sector, insurance, banking, and even healthcare or telecommunications.
How, though, can you harness analytics as a tool in your fight against fraud?
Identifying needs and solutions
The first step is to identify which options you need. Probably the best way to do this is through a series of company-wide workshops with the fraud analytics experts to determine what analytics you need, which data to include and techniques to use, and what results to report. They can also identify the ideal combination of rules-based and AI/ML approaches to detect fraud as early as possible.
Companies looking towards advanced analytics for fraud detection will need to make a number of decisions. They will need to optimise existing scenario threshold tuning, explore big data, develop and interpret machine learning models for fraud, discover relevant information in text data, and prioritise and auto-route alerts. There may be industry-specific decisions to make, too, such as automating damage analysis through image recognition in the insurance sector. By automating these areas, companies can both significantly reduce human effort – reducing costs – and improve their fraud detection and prevention.
Benefits of an analytical approach to fraud detection and prevention
Companies that are already using an analytical approach for fraud prevention have reported several important benefits. First, the quality of referrals for further investigation is better. Investigators also have a much clearer idea of why the referral has been made, which improves the efficiency of investigation. Analytics also improves investigation efficiency by reducing the number of both false positives (that is, alerts that turn out not to be fraud) and false negatives (failure to spot actual frauds). This improves customer experience and reduces risk to the company.
Analytics makes it possible to uncover complex or organised fraud that rules-based systems would miss. Companies can group together customers and accounts with similar behaviors, and then set risk-based thresholds appropriate for each scenario.
There are several sector-specific benefits too. For example, insurance firms can identify fraudulent claims faster to prevent improper payments from going out. Claims investigation is likely to be more consistent because claims are scored through technology, algorithms and analytics, rather than by people. Finally, it becomes possible to shorten the claims process through automated damage analysis. It is no wonder that organizations across a wide range of sectors are placing analytics at the heart of their anti-fraud strategy.
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