2023

The implementation of open banking and PSD2 in Europe has already forced banks towards being more customer centric. However, while some may have initially seen this as a challenge, this shift is providing an excellent opportunity for banks to offer far greater value to customers and unlock more revenue opportunities than ever before through platformification.

By Danny Healy, financial technology evangelist, MuleSoft

We are amid a complete transformation of the banking sector, affecting the way that we, as consumers, will access and use financial services for years to come. The banks of tomorrow will no longer define how financial services are delivered – the demands and expectations of the markets they serve will. Customers won’t be tied to a single bank, but instead will access financial services wherever they want, whenever they want, and however they want.

Building a platform on APIs

Data is key to tapping into these new opportunities, offering huge potential for banks to build personalised customer experiences in partnership with other service providers. PSD2 and open banking encourage banks to do precisely this, prompting them to develop APIs that open up their capabilities and data for others to build upon. The more open that banks become, the more opportunities they have to join new value chains.

Platformification and open banking present an opportunity for banks to establish themselves as a hub where customers and providers can come to select the best products at the right price. They can capitalise on this and enable more revenue to flow through their business by building a platform of reusable APIs that connect to third parties. HSBC, for example, was one of the first UK banks to realise this vision with the release of its Connected Money app, bringing in data from more than 20 rival banks to create a hub from which customers can manage all their bank accounts.

Opening up to new opportunities

For banks to position themselves as modern financial services hubs, they need to reimagine their business through platformification. This can best be achieved by unbundling and repackaging their digital assets as a set of capabilities exposed via APIs. It certainly seems that many are on the right track, as the Connectivity Benchmark Report 2020 revealed that those in financial services were amongst the most likely to be using APIs – 85% versus the cross-industry average of 80%.

In time, this will lead to the emergence of an application network, composed of applications, data and devices. Every asset on the network becomes pluggable and reusable for any team that requires them, even for third parties. This lays the perfect foundation for future success, enabling faster innovation and greater collaboration between banks, FinTechs and other service providers.

With the implementation of an application network, traditional banks will be able to create new revenue channels by sharing their core banking capabilities and customer base with authorised innovation partners. Mastercard, for example, has turned many of its core services into a platform of APIs.

Into a more open future

As banks continue moving towards this vision, it is critical that they understand that going it alone will not maximise value for customers. Success can best be achieved with an API-centric mindset that accelerates integration and innovation and provides seamless banking experiences. Unlocking data through APIs and an application network is ideal for achieving a competitive edge as the pace quickens in the race towards a more open future for banking.

As it gradually becomes mainstream, evolutionary AI’s capability to innovatively create complex AI models, and to optimise decisions considering multiple scenarios, is set to reimagine the financial sector. It will enable every player in this field to spot novel strategies that would never have been identified by human data scientists, and, in turn, allow companies to take full advantage of today’s massive data sets.

 by Babak Hodjat, VP of Evolutionary AI at Cognizant

 AI driven solutions are becoming a competitive differentiator for banks and other financial services — delivering a hyper-personalised customer experience, improving decision-making and boosting operational efficiency. Yet, many financial services institutions (FIs) remain in an experimental phase and will need to accelerate actual AI deployment. Otherwise, they risk being left behind by digitally native players. AI is rapidly transforming every aspect of the financial world. This transformation has accelerated recently, thanks to evolutionary AI – a new breed of technologies that allows AI to automatically design itself with little need for explicit programming by humans

How it all works

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.

The advantages of evolutionary AI

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.

Reaping the benefits

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

• Create and maintain responsible AI applications – 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.
• Craft business-driven AI strategies – AI should be viewed through a business lens, rather than as a technology issue. 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.
• Adopt an experimental mindset – 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.

As AI applications increasingly design and test themselves, the pace of innovation and the accuracy of predictions will vastly improve. It is inevitable that FIs will soon consider it irresponsible to make important business decisions without first consulting with an AI system. Robots will handle routine tasks while flagging exceptional cases for review and resolution by employees. Employees will spend their time on more complex decisions and sensitive interactions with customers, such as resolving complaints or providing sophisticated financial advice. In short, humans and AI robots will be working side by side, delivering more value in combination than either could on its own.

The world of international remittances is now worth $550 billion to low- and middle-income countries, and the World Bank only expects this growth to continue. 

by Daumantas Dvilinskas, CEO and co-founder of TransferGo

As physical borders look to once again be drawn firmly in the sand, virtual borders – such as those in financial services – are expanding and becoming ever more inclusive.  This trend is reflective of the role of FinTech in navigating geo-political tensions to provide a service that connects us all, no matter which physical borders separate us.

Democratising financial access

For too long, financial services has not worked for hard-working migrants. They have been victimised by an outdated system that benefits local communities as opposed to those who maintain a need for global connections. Traditionally, migrant communities have been stung by predatory fees, inefficient processes and unfair foreign exchange margins when making international money transfers. Remittances are a vehicle for international development, effectively lifting people out of poverty by funding education, healthcare, housing and business investments. They empower families to explore new opportunities abroad, learn new skills and seek out better career prospects.

Yet, the existing model can penalise this movement of workers by charging unfair fees. The World Bank estimates the global average cost of sending $200 at around 7% – or $14. However, traditional incumbents have been charging anywhere between 11-29% of the transfer value, and few can settle those transfers in anywhere near what consumers should accept.

Thankfully, this system of remittances no longer needs abiding by. It’s a model that is synonymous with the same attitudes as creating physical borders and preventing free movement. Instead, FinTechs have created an alternative; borderless financial services that create access for migrants the world over.

Leading by example

Across Europe, there are start-up hubs that are leading the charge in breaking down the obstacles in remittances, and creating virtual, permeable borders. One FinTech strain that is pioneering change is digital money transfer services. These facilitate the flow of money across borders without unfair fees and hidden exchange rate mark-ups, empowering migrant communities by giving them total control over the movement of their money.

As well as empowering consumers, a separate cohort of FinTechs that specialise in payments are creating open, financial borders for businesses of all sizes. Companies are unlocking the global opportunity for online businesses, allowing them to accept payments in foreign currencies, scale into new markets, and tap the growing global e-commerce market. Similarly, point of sale (POS) merchant platforms are enabling businesses to accept online, mobile and POS payments and access a global customer base.

Therefore, while geo-political trends [and the pandemic] may be leading to the affirmation of physical borders and a move away from globalisation, FinTech is playing an evergreen role in connecting international communities regardless. The incumbent money transfer system is outdated and detrimental to migrants, but innovative start-ups across Europe are helping to provide borderless remittances and offer an inclusive alternative.

Now more than ever, digital transformation and the ability to respond rapidly – in what is a very fluid situation – are critical.

By David Murphy, Financial Services Lead, EMEA & APAC Publicis Sapient

Unlike the last major financial crisis, which played out over the course of months and years, the current economic upheaval has impacted markets, businesses and livelihoods at lightning speed. Similarly, in contrast to the events of 10 years ago, banks find themselves on the front-line of the recovery, charged with helping to address the acute financial needs of their customers. The ultimate test is whether they can do so effectively and at speed.

Customers at the centre of the response

If there’s one thing we can be certain of with Covid-19, it’s that life isn’t returning to normal any time soon. On the other side of the curve, when the economy shows signs of an upward trajectory, the recovery is likely to be protracted and arduous.

While banks need to confront and mitigate risks – spanning income, operations, capital and reputation – all solutions must start with the customer. And in line with the expected slow pace of recovery, they’ll have to move from shorter-term metrics driving customer decision-making to a far longer-term focus on lifetime value.

Customers will be looking to banks to cut them some slack. Following standard rules and policies won’t work for a population that remembers very clearly the bail-outs of 2008. Since then, banks have focused on improving customer leadership, revenue growth, operational efficiency and automation, but with the emergence of this new crisis, they will need to revisit their communications, policies, business rules and operational processes to ensure they are fit for a very different economic, sociological and reputational era.

Digital transformation’s time has arrived

The availability of new digital capabilities means that banks can fundamentally change their response from previous crises. Organisation-wide digital transformation is the catalyst that enables them to act and implement changes faster than ever before; specifically addressing three key pillars:

Prioritising customer help: Access to significant levels of data means that banks can identify strategies and comms appropriate to different segments, repurpose existing products and generally enable a broader set of personal and business customers to address and take control of their finances. Empowering these customers to digitally serve themselves through the crisis can provide both stability and longer-term growth.

Optimising decision-making: Decision-making and approaches to many of the income, capital and reputational risks, can be optimised through the implementation of technical solutions, such as machine learning and AI. Triaging, adjusting and deploying new models for a more relevant and impactful response will not only increase effectiveness but generate new organisational capabilities.

Maintaining operational resilience: Changing traditional ways of working to enable the successful deployment of technology will be required to secure and maintain operational resilience. This can include assessing and adjusting governance structures, streamlining highly complex and manual processes to reduce the operational burden and retraining staff for remote proficiency.

Clients taking action

We’re already seeing banks take positive steps to leverage existing digital transformation capabilities or accelerate programmes. They’re emphasising strategic thinking and operational efficiency and framing responses around customers. From fast tracking solutions for health workers and vulnerable customers to leveraging cloud-based technology to bridge financing gaps for small businesses, this bold approach is precisely what’s required.

But in the early days of this crisis, there’s a lot more work to be done and many more institutions need to lift their game. Not just to provide the help that many customers so desperately need but to manage the considerable organisational impact and successfully navigate the uncertain digital transformation journey ahead.

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 15 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.

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 safer 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.

By Kiran Kumar, Co-Founder and Executive Director of Profinch Solutions.

Growth and relevance are quintessential business matters that keep organizations on the qui vive for opportunities to conduct business more efficiently and profitably while keeping step with changing times. The last few decades saw digitisation and technology emerging as this opportunity – starting off as a differentiator that set the leaders apart from the laggards to eventually becoming the only option available to stay relevant. The tech quarters are now abuzz with Quantum Computing – the nouveau arrive that promises to bring in the new wave of disruption.

Quantum Computing and Financial sector – What’s the fit?

Quantum Computing is a field which applies theories developed under quantum mechanics to solve problems. It entails the use of qubits to represent data as opposed to traditional binary units (0 and 1). Qubits are more flexible and allow for a combination of 0 and 1 simultaneously thus storing way more data than traditional bits wherein data must be either a 0 or a 1.

Quantum Computing’s enormous advantages over traditional computing stem from its conceptual design – the solution space of a quantum computer is orders of magnitude larger than traditional computers, even immensely powerful ones. The power of a quantum computer can be approximately doubled each time only one qubit is added. Relative to classical information processing, quantum computation holds the promise of highly efficient algorithms, providing exponential speedups in a multitude of processes.

Armed with these, Quantum Computing lends itself seamlessly to the financial sector since faster, more accurate, and more secure processing is at the core of how the industry needs to function.

Sample this – Google’s most advanced quantum computer named Sycamore could possibly solve a specific computational task that a traditional supercomputer takes 10,000 years to solve within 3 minutes. With that kind of speed and efficiency in tow, Quantum Computing is expected to produce breakthrough products and services likely to successfully solve very specific business problems. This could well usher in a new heyday, with financial sector holding the odds for being one of the most mightily favoured.

Delineating the Impact – what are the gains?

1. Enhance the efficiency of crucial operational processes in banking like

–  Client management, KYC processes, Client onboarding
–  Loan origination
–  Treasury management, trading and asset management

2. Revolutionise data security

Financial data encoded with quantum cryptography will be far more secure than other kinds of digital security. Such data cannot be hacked because the data in quantum states is perennially shapeshifting, i.e. constantly changing states and hence cannot be read. In fact, Quantum Computing has the potential to break even the most powerful security encryption of classical computers today. One of the examples to illustrate the use of quantum cryptography is known as a “quantum distributed key system” which promises secure digital communication that cannot be broken, even by a quantum computer itself. Banks such as ABN-AMRO are already starting to integrate this technology.

 3. Fraud detection

Quantum technology adeptly extends itself to fraud detection. As per a report in Feb 2019, financial institutions lose between USD 10 billion and 40 billion in revenue a year due to frauds and sub-optimal data management practices. Automation of fraud detection relies on recognizing patterns in data. Thanks to the qubit setup, the data modelling capabilities of quantum computers will prove superior in finding these patterns, performing classifications, and making predictions that are not possible today because of the challenges of complex data structures, thus averting fraud before it happens.

4. Customer targeting and service in banking

Classical computing is limited in its ability to create analytical models that can accurately and promptly cull insights from heaps of data available and target specific products at specific customers in near real-time. This greatly constrains the agility of response to rapidly evolving needs and behaviours of customers today. As per a study in 2019, 25% of small and medium sized financial institutions lose customers due to offerings that don’t prioritize customer experience. Quantum Computing can be quite the gamechanger for customer targeting and predictive modelling. It can also significantly enhance efficiency of critical frontal processes like customer onboarding which can sometimes take as long as 12 weeks to ensure due diligence. Use of quantum technology can turn around efficiencies thus enabling a far more superior and consistent customer experience.

5. Quantum data and transactions

Quantum technology’s ability to handle billions of transactions per second will be highly sought after by financial institutions consistently saddled with huge volumes of transactions. Quantum Computing reduces the likelihood of crashes and data loss. This will significantly accelerate the field of high-frequency trading.

Quantum computers will be able to mine colossal volumes of data almost instantaneously. This could enable the use of AI to make automated decisions using sets of pre-programmed rules.  AI is heavily reliant on large chunks of data to be able to learn. Given that Quantum Computing can handle that with incredible efficiency and speed, machines will quickly gather feedback that shortens their learning curve. Operations such as loan and mortgages can be automated, making them faster and efficient with seamless approvals and near zero delays.

6. Risk profiling

Financial services institutions are under increasing pressure to balance risk, hedge positions more effectively, and perform a wider range of stress tests to comply with regulatory requirements. With an ever-evolving regulatory climate, the complexity and cost of compliance is only expected to spiral in the coming years. Currently, Monte Carlo simulations are widely used to analyse the impact of risk and uncertainty in financial models but are highly limited by the scaling of the estimation error. In the face of more sophisticated risk-profiling demands and rising regulatory hurdles, the data-processing capabilities of quantum computers can improve the identification and management of risk and compliance.

7. Onward from here/ The shape of things to come

While the advantages run aplenty, Quantum Computing is still in the inceptive stages. A 2000 qubit quantum computer is expected only after 2025; beyond 2022, some aspects of Quantum Computing may start getting integrated with other cutting-edge technology of the day (such as AI and blockchain) to unravel amazing use cases in consumer experience, cybersecurity etc. The long and short of it is that, we stand at least five years away from Quantum Computing significantly impacting the financial services landscape. However, speculation abounds that Quantum Computing will mature at a velocity unseen by classical computing, and market developments and activities around it in the last couple of years endorse it. Reports say that financial bigwigs like Goldman Sachs, JP Morgan, CBA, Barclays, RBS, Allianz have already started investing in Quantum Computing technology.

The time is ripe for the penny to drop – for enterprises to start exploring investments in Quantum Computing. Those who adopt quantum early can seize major competitive advantages, including the potential to vault ahead of competition and become market leaders.