The role of technology in improving the Customer Experience in the banking sector: a systematic mapping study

Information Technology (IT) has revolutionized the way we manage our money. The adoption of innovative technologies in banking scenarios allows to access old and new financial services but in a faster and more secure, comfortable, rewarding and engaging way. The number, the performances and the seamless integration of these innovations is a driver for banks to retain their customers and avoid costly change of hearts. The literature is rich in works reporting on the use of technology with direct or indirect impact on the experience of banking customers. Some mapping studies about the adoption of technologies in the field exist, but they are specific to particular technologies (e.g., only Artificial Intelligence), or vice versa too generic (e.g., reviewing the adoption of technologies to support any kind of banking process). So a specific research effort on the crossed domain of technology and Customer Experience (CX) is missing. This paper aims to overcome the following gaps: the lack of a comprehensive map of the research made in the field in the past decade; a discussion on the current research trends of top publications and journals is missing; the next research challenges are yet to be identified. To face these limitations, we designed and submitted 7 different queries to pull papers out of 4 popular scientific databases. From an initial set of 6,756 results, we identified a set of 89 primary studies that we thoroughly analyzed. A selection of the top 20% works allowed us to seek the most performant technologies as well as other promising ones that have not been experimented yet in the field. Main results prove that the combined study of technology and CX in the banking sector is not approached systematically and thus the development of a new specific research line is needed

WoX+: A Meta-Model-Driven Approach to Mine User Habits and Provide Continuous Authentication in the Smart City

The literature is rich in techniques and methods to perform Continuous Authentication (CA) using biometric data, both physiological and behavioral. As a recent trend, less invasive methods such as the ones based on context-aware recognition allows the continuous identification of the user by retrieving device and app usage patterns. However, a still uncovered research topic is to extend the concepts of behavioral and context-aware biometric to take into account all the sensing data provided by the Internet of Things (IoT) and the smart city, in the shape of user habits. In this paper, we propose a meta-model-driven approach to mine user habits, by means of a combination of IoT data incoming from several sources such as smart mobility, smart metering, smart home, wearables and so on. Then, we use those habits to seamlessly authenticate users in real time all along the smart city when the same behavior occurs in different context and with different sensing technologies. Our model, which we called WoX+, allows the automatic extraction of user habits using a novel Artificial Intelligence (AI) technique focused on high-level concepts. The aim is to continuously authenticate the users using their habits as behavioral biometric, independently from the involved sensing hardware. To prove the effectiveness of WoX+ we organized a quantitative and qualitative evaluation in which 10 participants told us a spending habit they have involving the use of IoT. We chose the financial domain because it is ubiquitous, it is inherently multi-device, it is rich in time patterns, and most of all it requires a secure authentication. With the aim of extracting the requirement of such a system, we also asked the cohort how they expect WoX+ will use such habits to securely automatize payments and identify them in the smart city. We discovered that WoX+ satisfies most of the expected requirements, particularly in terms of unobtrusiveness of the solution, in contrast with the limitations observed in the existing studies. Finally, we used the responses given by the cohorts to generate synthetic data and train our novel AI block. Results show that the error in reconstructing the habits is acceptable: Mean Squared Error Percentage (MSEP) 0.04%

A Sustainable Approach to Delivering Programmable Peer-to-Peer Offline Payments

Payment apps and digital wallets are powerful tools used to exchange e-money via the internet. However, with the progressive disappearance of cash, there is a need for the digital equivalent of physical banknotes to guarantee the same level of anonymity of private payments. Few efforts to solve the double-spending problem exist in P2P payments (i.e., in avoiding the possibility of a payer retaining copies of digital coins in absence of a trusted third party (TTP)), and further research efforts are needed to explore options to preserve the privacy of payments, as per the mandates of numerous central bank digital currency (CBDC) exploratory initiatives, such as the digital euro. Moreover, generic programmability requirements and energetic impacts should be considered. In this paper, we present a sustainable offline P2P payment scheme to face the double-spending problem by means of a one-time program (OTP) approach. The approach consists of wiping the business logic out of a client’s app and allowing financial intermediaries to inject a certified payment code into the user’s device, which will execute (asynchronously and offline) at the time of payment. To do so, we wrap each coin in a program at the time of withdrawal. Then the program exploits the trusted execution environment (TEE) of modern smartphones to transfer itself from the payer to the payee via a direct IoT link. To confirm the validity of the approach, we performed qualitative and quantitative evaluations, specifically focusing on the energetic sustainability of the proposed scheme. Results show that our payment scheme is energetically sustainable as the current absorbed for sending one coin is, at most, ~1.8 mAh on an Apple smartphone. We advance the state-of-the-art because the scheme meets the programmability, anonymity, and sustainability requirements (at the same time)

Commentary – CRISPR-based techniques: Cas9, Cas13 and their applications in the era of COVID-19

The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/ Cas9 (CRISPR-associated protein 9) system enables scientists to edit diverse genome types with relative ease, with the aim – in the near future – to prevent future human beings from developing genetic diseases. The new opportunities arising from the system are broad-ranging and revolutionary, but such prospects have also been the cause for alarm throughout the international scientific community. The authors have laid out a review of the trials carried out so far in terms of genome editing, for the ultimate purpose of weighing implications and criticisms. We feel that possible valuable alternatives, such as induced pluripotent stem cells should not be overlooked

HF-SCA: Hands-Free Strong Customer Authentication Based on a Memory-Guided Attention Mechanisms

Strong customer authentication (SCA) is a requirement of the European Union Revised Directive on Payment Services (PSD2) which ensures that electronic payments are performed with multifactor authentication. While increasing the security of electronic payments, the SCA impacted seriously on the shopping carts abandonment: an Italian bank computed that 22% of online purchases in the first semester of 2021 did not complete because of problems with the SCA. Luckily, the PSD2 allows the use of transaction risk analysis tool to exempt the SCA process. In this paper, we propose an unsupervised novel combination of existing machine learning techniques able to determine if a purchase is typical or not for a specific customer, so that in the case of a typical purchase the SCA could be exempted. We modified a well-known architecture (U-net) by replacing convolutional blocks with squeeze-and-excitation blocks. After that, a memory network was added in a latent space and an attention mechanism was introduced in the decoding side of the network. The proposed solution was able to detect nontypical purchases by creating temporal correlations between transactions. The network achieved 97.7% of AUC score over a well-known dataset retrieved online. By using this approach, we found that 98% of purchases could be executed by securely exempting the SCA, while shortening the customer’s journey and providing an elevated user experience. As an additional validation, we developed an Alexa skill for Amazon smart glasses which allows a user to shop and pay online by merely using vocal interaction, leaving the hands free to perform other activities, for example driving a car

Randomised trials and meta-analyses of double vs triple antithrombotic therapy for atrial fibrillation-ACS/PCI: A critical appraisal

•The optimal antithrombotic regimen to be used in patients with AF and PCI or ACS is still debated.•Each of the six randomised controlled trials comparing double to triple therapy has limitations.•None was powered to assess differences between treatment arms in ischaemic event rates.•The contrasting results regarding ischaemic events within published meta-analyses can be explained by heterogeneity, incompleteness and varying definitions of stent thrombosis.•The overall reduced bleeding rates, but increased early definite and probable stent thrombosis rates with double versus triple antithrombotic therapy encourage consideration of triple therapy during the first weeks from PCI followed by double therapy

Microvascular Dysfunction in Heart Failure With Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is an increasingly studied entity accounting for 50% of all diagnosed heart failure and that has claimed its own dignity being markedly different from heart failure with reduced EF in terms of etiology and natural history (Graziani et al., 2018). Recently, a growing body of evidence points the finger toward microvascular dysfunction as the major determinant of the pathological cascade that justifies clinical manifestations (Crea et al., 2017). The high burden of comorbidities such as metabolic syndrome, hypertension, atrial fibrillation, chronic kidney disease, obstructive sleep apnea, and similar, could lead to a systemic inflammatory state that impacts the physiology of the endothelium and the perivascular environment, engaging complex molecular pathways that ultimately converge to myocardial fibrosis, stiffening, and dysfunction (Paulus and Tschope, 2013). These changes could even self-perpetrate with a positive feedback where hypoxia and locally released inflammatory cytokines trigger interstitial fibrosis and hypertrophy (Ohanyan et al., 2018). Identifying microvascular dysfunction both as the cause and the maintenance mechanism of this condition has opened the field to explore specific pharmacological targets like nitric oxide (NO) pathway, sarcomeric titin, transforming growth factor beta (TGF-β) pathway, immunomodulators or adenosine receptors, trying to tackle the endothelial impairment that lies in the background of this syndrome (Graziani et al., 2018;Lam et al., 2018). Yet, many questions remain, and the new data collected still lack a translation to improved treatment strategies. To further elaborate on this tangled and exponentially growing topic, we will review the evidence favoring a microvasculature-driven etiology of this condition, its clinical correlations, the proposed diagnostic workup, and the available/hypothesized therapeutic options to address microvascular dysfunction in the failing heart