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THE IMPORTANCE OF DATA VISIBILITY FOR SUCCESSFUL DIGITAL TRANSFORMATION

New ways of uncovering data, improving data quality and establishing a single source of truth in your spreadsheets…

 

Transformation implies you are changing the status quo and most humans are notoriously prone to inertia. Most people love comfort zones and will try to resist change. If any stakeholders feel they are left in the dark, they will have one more reason to sabotage change.

 

Upgrading means changing consolidated systems used company wide and disruption is probably inevitable, but this has to be looked at as an investment to save, day after day, time and money, hence recovering the financial and time outlay. But problems with inaccurate data and a lack of transparency can make the whole process a lot more difficult.

 

Gianluca Bisceglie

Data Quality Issues

‘Unclean’ data is a tremendous problem that causes real financial losses. Many factors contribute to the use of many different processes and software, so many file versions, a lot of different ways to approve decisions: the size of organizations, the type of communication between departments, the workflow that takes so many shapes and forms. This way, the risk of having corrupted or inaccurate data is extremely high. That is why the holy grail that all professionals ask for is the ‘single source of truth’. They crave for systems where they can create information, track edits, share results, stress-test them, and approve decisions in one place, avoiding multiple copies of same files, back and forth emails and consequent data chaos.

 

Mistakes are noticed when it’s too late, and they can cause wrong decisions, financial losses, and people getting fired. The probability of this occurring is proportional with the size of the company that determines the number, the complexity of data-driven processes and the probability that a simple mistake can propagate and create dramatic consequences: a chain is as strong as its weakest link.

 

Improving Visibility

Without visibility, there can be no solid decision making. Organisations should recognise the importance of not excluding talent from the decision-making process and make efforts to enable fluid collaboration and communication among colleagues. This transparency allows all to see what others do and step in if necessary; there are clear lines of accountability.

 

A Smooth Transformation

It’s crucial to appoint competent people to lead digital transformation initiatives and design effective processes to implement. Once the process has been designed, they can identify the best software platforms that fit the company’s needs. Across sectors and functions, the typical platforms deployed have common characteristics: they contain all data, conversations and supporting documents in one place: the ‘single source of truth’. They track changes and approvals, democratise access to information by removing ‘system gurus’ and bottlenecks. The best platforms that are permanently adopted are the ones that are intuitive and easy to use, transparent and elegant, and that do not require extensive training.

 

To prevent the logistics of the switchover breaking down, choose companies that offer data import/export facilities – this acts as a safeguard and allows for a quicker adoption as data are transferred easily and disruption is minimised. Establish the depth and breadth of the systems for your problem. Choose products that require a minimal learning curve and can be adopted immediately and incrementally, meaning that every single new adopter in the company does not need to wait for everybody to be on the platform to start getting some benefits from it. Modern SaaS solutions do not require complex installations and configurations and allow for incremental adoption.

 

So, how do you ensure the success of a digital transformation initiative? There must be a clear definition of what ‘success’ means? What is not working or is perceived as suboptimal? Once this is clear, it is easy to evaluate new products on harmless restricted pilots, hence maximising the chances of success on a larger scale adoption.

 

Gianluca Bisceglie is the founder and CEO of Visyond, a cloud-based spreadsheet software platform that disrupts the way people work with spreadsheets ­– allowing secure, selective and interactive data sharing, minimising errors, and performing analyses in seconds with a few simple clicks. www.visyond.com

 

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Technology

DISPELLING BIOMETRIC MYTHS AND MISCONCEPTIONS

By Lina Andolf-Orup, Head of Marketing at Fingerprints

Gangsters cutting off enemies’ fingers to access secret locations and spies lifting fingerprints from martini glasses – the imagination of the entertainment world has been running wild ever since biometrics entered the scene.

Couple that with the limitations of some early biometric solutions from fifteen years ago, still anchored in the minds of many consumers, and you have the perfect recipe for an apprehensive and uncertain public.

 

Thawing lukewarm attitudes with a biometric touch

The biometrics industry has made great strides in the last few years – something particularly true for smartphones. Fingerprint authentication has replaced PINs and passwords as the most popular way to authenticate on mobile, with 70% of shipped smartphones now featuring biometrics.

And it doesn’t end there. Many adjacent markets are now eager to benefit from the secure and convenient authentication solutions that biometrics offer. Take the payments industry, for example, where biometrics payment cards are currently gathering real momentum.

However, some consumers are still uneasy about accepting biometrics. A recent study found that 56% of US and EU consumers are concerned about the switch to biometrics as it’s not enough understood to be trusted.

Although attitudes are shifting for the better, stats like this demonstrate there is still some work to do to disprove common biometric myths and showcase just how smart today’s solutions really are.

 

Lina Andolf-Orup

Dispel, adopt, repeat

The evolution in consumer biometrics in the last two decades has been phenomenal. And today’s solutions are far more advanced and safe than many may think.

To help bring an end to the myths, let’s expose some of the most common misconceptions around biometrics.

Myth: Biometric data is stored as images in easy-to-hack databases.

A leading myth about biometrics is that when a fingerprint is registered to a device, it is stored as an image of the actual fingerprint. This image can then be stolen and used across applications. In reality, the biometric data is stored as a template in binary code – put simply, encrypted 0s and 1s. Storing a mathematical representation rather than an image makes hacking considerably more challenging. In most consumer applications, this template is also not stored in a cloud-based location, its securely hosted in hardware on the device itself for example in the smartphone, in the payment card. Thus, it stays privately with its owner.

Myth: Fingerprints can be easily replicated to ‘trick’ devices.

The internet is full of articles and videos that claim it is possible to use materials from cello tape to gummy bears to craft fingerprint spoofs and access biometric systems. Although there may have been a time where gummy bear spoofing was the go-to party trick, todays’ consumer biometric authentication solutions have too many technological defences, such as improved image quality and matching algorithms, to simply ‘trick’ devices. Plus, on top this, the criminal needs to have access to the person’s device where this fingerprint is enrolled e.g. smartphone, payment card, before he/she notices and blocks it. This is not scalable nor common, in comparison to gaining access to someone’s PIN code or skimming a contactless card.

Myth: Physical change will prohibit access to my device.

Although our irises don’t change as we age, our fingerprints can and our faces will. Does that mean we have to update our biometric devices every few months to capture these changes? Not quite! Unless there are drastic, sudden changes, the ‘self-learning’ algorithms in modern-day biometric systems are able to keep up with our developing looks.

 

Who you gonna call? Mythbusters!

These are just some of the common biometric myths and misunderstandings perpetuating in consumer mindsets. Thankfully, though, while we’re working hard to rid the world of the myths, belief in the value of biometrics is only expected to grow. But as solutions expand and diversify, the myth-busting fight will continue.

Fingerprints has been a leader of innovation in biometrics for the last two decades. We’re proud of the expertise and R&D we’ve been able to pour into our biometrics solutions to deliver stronger security and a better user-experience. To learn more about the most common biometric misconceptions and the modern-day technology that allows us to dispel them, download our eBook here.

 

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Technology

WHAT EVOLUTIONARY AI MEANS FOR FINANCIAL SERVICES

FINANCIAL SERVICES

by Babak Hodjat, VP of Evolutionary AI at Cognizant

 

Many banks and other financial services institutions (FIs) are beginning to recognise the benefits of AI-driven solutions as a way to get ahead in the market and challenge the competition. Amongst many other benefits, the technology enables organisations to offer hyper-personalised customer experience,  dramatically improve internal decision making, and drive operational efficiency. However, many businesses are struggling to move beyond the experimental phase and reach actual AI deployment. It is those organisations that are at risk of being left behind.

The financial world has already been transformed by AI, and this transformation is continuous. A new breed of AI, known as ‘evolutionary AI’ has begun to further accelerate innovation. It is capable of automatically designing itself with little need for explicit programming by humans – innovatively creating complex AI models, and optimising decisions considering multiple scenarios.

This technology is revolutionary for industries across the world, but in particular it is set to transform the financial services sector. Enabling businesses to spot novel strategies that would never have been identified by human data scientists, and, in turn, allowing companies to take full advantage of today’s massive data sets – evolutionary AI will soon be a vital tool in all FIs’ arsenals.

 

The nuts and bolts of evolutionary AI

Emerging technologies that enable AI algorithms to design themselves are allowing organisations to transcend human limitations. Evolutionary AI operates iteratively. Firstly, it randomly generates a set of potential solutions to form an initial population and assigns a score to each solution based on how well it performs relative to other solutions. In the second round, it retains the solutions that performed best, perhaps only 5% of the total, and recombines their components, sometimes “mutating” them to create a new population. This new population is then tested, and the process begins again. Over multiple generations, the appropriate components of the more successful solutions become increasingly prevalent in the population, and eventually a solution is discovered that yields the best outcomes.

 

Advantages and use cases

Compared to human design, evolutionary AI can be deployed far more quickly, avoids biases and preconceptions, and typically performs better. Furthermore, the chosen model will evolve and improve over time based on new data.

Evolutionary AI can be applied in a wide variety of areas at FIs. Some examples include designing quantitative trading strategies to maximise returns while minimising risk and loan underwriting. Rather than relying on human analysis, evolutionary AI solutions can quickly analyse all the combinations of relevant variables to create models that more accurately assess the risk of default by a potential borrower.

 

A recipe for success

In order to reap the benefits of the technology, FIs should focus on the following:

  • Responsible AI – Behave in ways that make customers and employees comfortable, i.e. not making decisions that are unethical or exhibit bias. Companies need to monitor them to ensure they continue to act appropriately, as they learn and evolve.
  • Viewing AI through a business lens – Having AI projects managed by cross-functional teams with business executives in the lead is a good place to start. Companies also need to look across their organisations to identify opportunities to generate concrete business value from AI — not only in reduced costs but also in boosting revenues by delivering enhanced customer experiences and through improved decision-making.
  • Enhance data management – AI applications depend on access to timely and accurate data, which is a challenge for many FIs that have fragmented data architectures with multiple legacy systems. Companies need to identify which types of data are required for each AI project and ensure they can be captured in an appropriate format.
  • Approach with speed and caution – AI projects need to be rolled out quickly, while at the same time be rigorously measured, so failures are terminated promptly while successes are moved into production.

The sophistication of AI technology is set to significantly improve over the coming years as it continues to design and test itself. As a result, it will become more critical to the productivity of FIs, and soon businesses will recognise it as a vital tool for consulting on important business decisions. It will not be long before humans and AI are working alongside each other, with robots handling routine tasks, enabling employees to focus on more complex and sensitive activities. Delivering more value together than either could on their own.

 

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