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CONTACT CENTRES: AI LEADING THE CHANGE

Simon Black, CEO, Awaken

 

Artificial Intelligence (AI) might be considered by many as the buzziest of buzzwords but it’s getting harder to escape the fact that those deploying it across key areas of their business are already reaping the rewards. A recent study by Accenture found that AI technology can enhance business productivity by up to 40% and with an estimated 7 billion devices now operating with AI-powered voice assistants (IHS MARKIT) if you’re not already using it in your contact centre, it’s time to make that move.

 

In an industry where person-to-person contact and communication is paramount and highly valued by both agents and customers, there is an understandable suspicion around employing AI to handle customer enquiries, concerns and issues. But there is so much more to it than just using an automated voice!

 

At a time where agents are working from home, budgets are under greater pressure than ever before and customers’ expectations are at an all-time high AI could be the key to streamlining your contact centre processes and taking your customer service to the next level. When integrated with contact centre systems and databases, it empowers operators to predict customer behaviour and make proactive decisions that deliver competitive advantage. By analysing historical customer data, it can also be used to forecast how customers will behave in the future and anticipate their needs to ensure a good experience when interacting with your business.

 

AI delivers significant benefits for contact centres, enabling organisations to develop a well-informed strategy that results in competitive advantages, including:

  1. Turning customer interactions into useful data

We all know that contact centre systems capture a wealth of data, and while many operators already use business intelligence analytics to understand trends, it can take significant time to process and analyse accurately. By the time those reports are fed into your business strategy, the information may no longer be relevant, or a new, more urgent issue could be emerging.

AI can expedite the analytics process, promptly identifying trends within a large data set. That’s particularly helpful for labour-intensive jobs like quality checking voice calls. Tools such as sentiment analysis and voice analytics can review recorded voice calls in a matter of minutes, recognising signs of anger and dissatisfaction and identify the cause. Enabling centre managers to quickly identify any issues (for example, agents giving customers incorrect information) means that you can quickly make amends all while ensuring your business meets regulatory compliance and improves upon quality assurance standards significantly.

 

  1. Predicting what customers want

The ability to identify and extract insights across phone calls, email or web chat as trends emerge is critical. It means that your agents can respond to customers’ changing expectations faster and ensure that they capitalise on opportunities or mitigate potential negative outcomes.

AI will also help call centre managers to improve strategic resource planning, staff training as well as sales and marketing campaign planning. You can use it to predict the outcomes of implementing business decisions or new processes. In the longer term, AI allows call centre managers to model best practices based on a more accurate understanding of the voice of the customer, their preferences and behaviour.

 

  1. Reducing recruitment costs

Beyond automating and speeding up analytics processes, AI also helps to reduce the burden of training requirements and the need to keep refreshing training. Voice analytics reveals what customers are really thinking and feeling. At the same time, it helps contact centre managers to monitor agent performance over a period of time, AI can measure how the agent is feeling and whether they need any support in their role.  By automating the intensive process of monitoring agent-customer interactions at scale, AI can identify agents that might need further training, which is proven to reduce agent attrition. Since the average cost to recruit a single agent can be up to £25,000, this offers significant cost savings for businesses where contact centres play a key role in their organisation.

According to Statista1, the AI market grew by 154% last year and with 41% of consumers already believing that AI will improve their lives in some way (Strategy Analytics) you might be wondering what’s holding you back. Meeting customer demands and creating a frictionless experience has never been more important. AI can help your agents and centre to turn unstructured conversations across multiple channels into structured and contextual data, delivering insight that can be utilised to improve customer service. It also enables you to take a strategic view to plan as well as support your agents in real time during live customer interactions.

Leveraging behavioural and emotional analytics has never been easier and enables you to truly understand your customers and more than ever meet their needs. AI can truly deliver this for you, if utilised effectively.

 

Press targets:

  • Contact centre press
  • Tech press

Finance

AI: CUSTOMER FACING EMPLOYEES’ BEST FRIEND IN THE FINANCIAL SERVICES INDUSTRY

By Ryan Lester, Senior Director, Customer Experience Technologies at LogMeIn

 

We’ve all heard the old saying “money talks.” Well when it comes to customer loyalty and retention, good customer experience talks much louder, with 30% of customers leaving a brand and never returning due to a bad experience.

The truth is, there are a lot of companies with similar products and services, but that doesn’t mean that differentiation is impossible. So, what’s the solution? For financial services, large and small, customer experience is becoming the key competitive differentiator and the best way to deliver an impactful experience is to empower customer-facing employees to do their best work. Artificial intelligence (AI) is enabling these employees to create remarkably better customer experiences, resulting in customer loyalty, advocacy, and overall growth.

For financial institutions that have been considering new strategies for improving the quality and efficiency of their customer experience, here are a few ways AI can enable them to deliver the “human factor” that good customer experience demands whilst ensuring customer facing employees can provide a more positive experience for customers.

 

Increase employee productivity

How much of employees’ time is spent searching for answers to questions? Do they ever have to put customers on hold or even step away to get additional help? AI helps provide front-line employees real-time guidance so they can spend less time looking for information and more time solving problems. An AI-powered chatbot, for example, can be listening in the background of a conversation helping point employees to the right data, solutions, and processes to resolve customer issues faster than ever before.

 

Deliver a consistent customer experience

When banking customers engage with their financial institutions, they measure the speed and accuracy of the service through two criteria. First, how quickly can the system access their account and deliver the correct information? Is it faster than a human could type it in and share it? And second, if they eventually do need to be connected to a live customer support agent, is their information captured and passed along accurately? AI technology takes those general queries off the customer support team’s plate, providing a quick, accurate, and effective response. If a query needs a more in-depth response, AI can hand it off to support staff to address.

Not only this but leveraging a centralised, AI-powered knowledge solution ensures every employee has access to the same, updated information, so no matter who the customer speaks to, they can be assured that employee responses are both consistent and accurate across the board.

 

Accelerating employee training and onboarding

Like any industry, employee turnover is inevitable and can be costly. But, not training new employees correctly or in a timely manner could be much more costly. When it comes to financial services there is a lot to learn, whether it is something simple like the process for checking an account balance to all the nuances associated with mortgage loans. AI can support on-the-job training by helping new employees answer questions confidently, correctly, and much quicker than they could before.

 

Improving employee satisfaction

Today’s banking customer has all kinds of new ideas about their banking experience. “The Amazon Effect” has successfully raised consumer expectations to the extent that a consistent, personal, and relevant experience is the new normal. As a customer, how many times have you been told “I’m sorry, I don’t know the answer?” Customers want solutions to their problems and employees want to be able to deliver those solutions as efficiently and effectively as possible. AI assisting in the background helps minimise those negative moments – making employees job easier, less stressful, and overall more enjoyable.

 

Identify knowledge gaps

Do you know all the questions employees are getting asked? Do you know what’s easily answered and what’s not? Real-time insights allow knowledge managers to keep up to date on frequently asked questions and gaps in current resources. This allows them to strategically improve or add content where needed.

 

Augmenting customer service

Whether talking with an AI chatbot or a personable customer service team member, the modern banking customer has high expectations for convenience, speed, and security. Which means that the technology you choose to deploy and how you deploy it is now just as important as who you hire and how you train them.

Today’s AI solutions won’t replace customer service agents or get in the way of the human factors that drive the customer experience. On the contrary, they augment it, allowing the business to do more without adding human resources. The higher the quality of a AI chatbot solution, the better it will be at taking the routine requests off the plate of customer service agents—giving them more time to provide a personalized and positive experience for customers.

 

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Technology

BEFORE THE INK IS DRY: CORRECTING BIOMETRIC SPOOFING MYTHS

Eric Setterberg, System Design Engineer at Fingerprints

Biometric authentication is highly robust, and the latest solutions offer considerably greater security than their authentication predecessors: PINs and passwords.

But as biometrics moves into new areas such as payments and access control, privacy and security concerns are rising. Biometrics has long been subject to scrutiny, with many elaborate examples of people working to trick biometric sensors to crack devices in the media and online.

To ensure the continued adoption of biometrics, it is important to shine a light on the reality of biometric spoofing.

 

The Evolution of Biometric Solutions…

The first use of fingerprints as forensic evidence was in an Argentinean court case in the late 1800s. With the technology still in its infancy, this was done manually and by eye, comparing latent residual prints lifted from crime scenes to charts of inked fingerprints obtained from the suspects at arrest.

A few decades later, the FBI began collecting fingerprints of criminals and civilians. They also introduced the automated comparison of fingerprints by computers in the 1970s. These “traditional representations” have now been standardized by ISO and ANSI.

… and their Spoofs

The earliest and simplest of these matching devices were easy to spoof. Really, all you needed was a photocopy or a good image of a fingerprint to make a successful spoof.

But as biometrics moved to more advanced technology, the game for biometric ‘spoofers’ has changed and the task of crafting fake fingerprints is considerably more difficult.

The biggest boost for biometric security, however, came with its introduction into mobile phones.

 

How Mobile Changed the Game

Before the widespread integration of fingerprint sensors in smartphones, the technology underwent significant evolution. No operator wanted to use large biometric sensors in modern phone designs. Sensors had to become much smaller to reach the perfect price and design point for the mobile world, but this meant needing to capture data from a smaller surface area of the finger.

To maintain the security of these smaller sensors, algorithms evolved significantly in order to utilize a greater amount of data per unit area. These mobile-driven hardware and software changes resulted in the optimized image capture of modern touch sensors.

As a result, tricking these systems now requires a considerably higher level of detail to be reproduced correctly for a match to be successful, far beyond rudimentary gummi bear spoofs and photocopies

 

Setting the Perfect Spoofing Scenario

Compromising fingerprint authentication via spoofing can still be done, even with all the technological advancements. However, it now requires considerable care, skill, money, and time. And to start, a good latent print…

To retrieve a latent print that’s high quality enough to work, you either need a willing volunteer to lend you their finger, or the commitment to stalk a victim until a viable fingerprint can be retrieved. Even with a decent latent print, modern spoofs then require advanced photoshop skills and/or a lab to successfully convert latent prints into effective moulds.

So – what about those articles boasting how easily they have hacked the latest smartphone device’s fingerprint sensor?

In fact, there are only two instances of fingerprint spoofing seen in the media nowadays: proof of concept and cooperative spoofs. Lay enthusiasts and media go through the effort of setting up a lab to create spoofs with latent fingerprints either from themselves or cooperative volunteers. Even the most successful of these take months of work, a highly skilled team, and the perfect scenario of circumstances.

Put simply, the effort required for spoofing modern fingerprint sensors cannot be applied at any scale. Each biometric spoof needs to go through the same laborious process and clinical conditions. So, if you can bring together a willing group of spoofing enthusiasts, tricking a biometric device could earn you fifteen minutes of fame on the internet, but it is likely to be conducive to a successful criminal business plan…

 

A “How” Without a “Why”

Spoofing biometrics remains technically possible, and there will always be those up to the challenge of trying to hack the latest technology. But the reality is that modern biometric solutions require more time, skill, and frankly, luck, to successfully spoof than ever before. Not to mention that tireless R&D work is continuously strengthening spoofing resistance. And, as use cases start to combine multiple biometric authenticators, such as combining fingerprints with face or iris to perform an authentication, spoofing will only become more complex.

By comparison, hacking PINs and passwords is considerably simpler and more scalable, making it far more lucrative. And, criminals generally take the path of least resistance.

For the average consumer, greater use of biometric authentication is not only a means of simplifying authentication, but dramatically improving the security of their devices, applications, and personal data. With PINs and passwords still the most common authentication method outside of mobile, it is imperative that the true security and advanced nature of modern biometric authentication solutions are understood.

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