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Banking on Tomorrow: Exploring Emerging Technologies and Trends in Finance

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FinTech

By Catherine Hoff, Managing Director and Co-Founder of Genieology

In the banking world, the 90s feels like a distant memory. It was a time where customer experience was confined to a brick-and-mortar establishment with time-consuming processes and disjointed services. Fast forward to post 2000s and the increased use of the internet pushed the banking sector to embrace digital. The journey from then to now is a tale of innovation, disruption and financial evolution, thanks to rapid advancements in technology and changes in consumer expectations and behaviours.

Blockchain and Cryptocurrency

Blockchain technology, originally created to underpin cryptocurrencies like Bitcoin, has found applications beyond digital currencies. Blockchain’s decentralised and secure ledger system can streamline various banking processes, including cross-border payments, trade finance and identity verification. Financial institutions are exploring the use of blockchain to reduce fraud, lower transaction costs, and improve transparency in operations.

Its full impact with traditional institutions is still evolving, but blockchain features have the potential to disrupt and transform specific aspects of the financial industry. Along with the possibility of faster and cost-effective cross border payments, this tech can deliver Smart Contracts, which are self-executing agreements with the terms directly written into code.

Big Data Analytics

Big data analytics can be used to distill the vast amounts of daily data generated by the banking and finance industry into valuable, decision-driving insights. Financial institutions use data analytics to optimise operations, create personalised marketing campaigns, and better understand customer behaviour. Predictive analytics can be used to forecast market trends, identify risks, and make data-driven investment decisions. Analysing customer data leads to tailored financial solutions for customer satisfaction and retention. This shows that a ’one-size-fits-all’ solution doesn’t work, and product design plays a crucial role in ensuring optimal engagement.

Artificial Intelligence (AI), Large Language Models and Machine Learning

AI and machine learning, by which we mean automation and large language learning models (LLMs), are transforming the banking industry in numerous ways. AI-powered chatbots and virtual assistants are used to enhance customer support and streamline routine inquiries. Machine learning algorithms are employed to assess credit risk more accurately, detect fraud in real-time, and personalise financial product recommendations.

The early iterations of robo-advisors (RAs) had a bad reputation in banking resulting in the tech being rolled back or cancelled altogether. But with ChatGPT and more sophisticated LLMs, they are gaining popularity to created automated investment platforms to manage diversified portfolios, making wealth management services more accessible and cost-effective, as well.

Fertile Ground for Fintech Disruption

The rise of fintech startups has disrupted various aspects of banking, from payments and lending to wealth management and insurance. Fintech companies have introduced innovative solutions and digital-first services that challenge traditional banking models.
Open banking initiatives and regulations in several countries are providing a fertile ground for fintech to drive innovation, competition and growth.

Though still in its infancy, it will benefit the sector if they continue to widen the range of products and services available to customers within the open banking ecosystem. Also, to accelerate the adoption among customers, the industry needs to enhance awareness about the benefits of open banking. A recent survey found that only 20% of consumers in the UK are aware of open banking, which calls for more education and outreach to consumers.

The Cyber and Data Security Considerations

It’s important to note that with the growing reliance of new technologies and models in the financial industry, there’s a very real and growing threat of privacy and cyberattacks. Using large language models raises concerns of data privacy, security, and ethical considerations. Banks need to ensure that they handle customer data responsibly and adhere to relevant regulations, such as GDPR and financial data protection laws, when implementing these technologies.

Cybersecurity is another area that the banking and finance sectors need to heavily invest in to protect customer assets and maintain trust. Advanced encryption techniques, biometric and multi-factor authentication, behavioural analytics, securing APIs and continuous monitoring are becoming standard practices in the fight against cyber threats.

An Exciting Future for the Sector

New and emerging technologies have led to a profound digital transformation in the banking and financial sectors. The adoption of everything from digital currencies and artificial intelligence to open banking initiatives are democratising financial services, fostering greater inclusion, while bolstering the sector’s defences against threats. And this is just the beginning. As the banking sector evolves, institutions can continue to harness these technologies to position themselves at the forefront of a more agile, innovative and customer-focused era in finance.

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Cash and Its Persistent Meaning

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digital payments

Authored by: Konstantin Vladimirovich Tserazov

In recent years, the global shift towards digital payments has been evident. More countries are witnessing a decline in cash transactions, with Gulf countries upholding this trend. By the end of this year, over half of all financial interactions in this region are expected to be cashless. Despite this tendency, cash remains in the pockets of millions of people, and this phenomenon can’t be ignored.

The Evolution of Money

Before money existed, bartering was used, but it was inefficient. As a result, mediums of exchange were created, beginning with items like shells, which later developed into metals, coins, and eventually banknotes. While this shift towards digital payments offers convenience and efficiency, it also creates challenges for certain groups in any society, such as the elderly, minors, and individuals with disabilities. Even in the face of digitalization, cash remains important for those who cannot access banking services, such as temporary migrants. Unfortunately, these groups face a risk of digital exclusion.

The Cash Dilemma

In some countries, the demand for cash increases even as cash payments decline. This can be explained by the fact that cash is used sometimes as a preferred savings method, especially during times of crisis.

The push towards cashless and digital payments is driving a reduction in physical bank branches, encouraging the transition to digital money.

However, this transition faces several obstacles:

  • High Cost of Smartphones: Not everyone can afford a smartphone, which is crucial for conducting digital transactions.
  • Unreliable Internet Access: Consistent Internet connectivity is necessary for digital payments, yet it is not universally accessible.
  • Challenges for Older Adults: Seniors may struggle to adapt to digital payment systems.
  • Fraud Risk: Ease of transfer increases fraud risk, especially for vulnerable groups.
  • No Local CBDCs: Many countries lack central bank digital currencies (CBDCs).
  • Unclear Crypto Laws: Cryptocurrency laws are often unclear or restrictive.

Cryptocurrency as a Potential Solution

Cryptocurrencies could potentially address some of these challenges, but it is essential to ensure that the development of CBDCs and the broader crypto ecosystem includes applications for the deaf, blind, or visually impaired, as well as individuals with developmental disabilities.

This area currently receives little attention in the crypto sphere but holds the potential for successful business models and innovative solutions for millions of people. Ultimately, these solutions will contribute to the adoption of digital means of financial interaction.

The Necessity of Digitization

The move towards digitization aligns with the Environmental, Social, and Governance (ESG) agenda for money emission. Managing cash incurs costs for the state, and a digital system should be significantly more efficient than handling physical cash, which requires transport and management. The marginal cost per transaction would be very low if the central bank provided a digital payment system.

Moreover, if CBDCs were interest-bearing, they could theoretically impact monetary policy quicker. This would make it more advantageous to hold money in CBDCs rather than cash, which does not generate income.

Digital Money as a Tool for Inflation Management

When high interest rates are necessary to curb inflation, digital money could become a silver bullet. The circulation of such financial instruments reduces business costs, allowing them to raise prices less.

In short, the distribution of CBDCs could be as effective a tool for central banks in managing inflation as increasing key interest rates and tightening reserve requirements for banking activities. Unlike cash, where it is unclear what goods are being purchased at any given moment, CBDCs provide for monetary policy makers transparency in transactions .

Why People Still Prefer Cash

Despite the advantages of digital payments, many people still prefer cash. This preference can be traced back to when dollars had guaranteed gold backing. When thinking about digital currencies and cryptocurrencies, some feel they are “somehow out of thin air,” not backed by anything.

In reality, current fiat currencies are also not backed by anything. However, cryptocurrencies like Bitcoin have a guaranteed reduction in the rate of issuance and a “cap” on the maximum number of units that can be issued, unlike any fiat currency.

The inflationary nature of fiat encourages even those who save in cash to spend it. If a person saves in Bitcoin, there are no such incentives; due to its deflationary model, there is a high likelihood of further increases in the value of such cryptocurrency relative to fiat money. This is precisely why the adoption of Bitcoin as a means of payment is stagnating — in El Salvador, for example, despite the ability to pay with Bitcoin in stores, there is no significant enthusiasm.

Another interesting point about why people prefer cash is the relative anonymity of spending. Additionally, there is the feeling of control. In some countries, there is a strong fear that hard-earned money in banks could disappear during a financial crisis. The Cypriot banking debacle of 2012-2013 serves as a chilling reminder. Billions of euros—a staggering €8 billion—were simply wiped out, leaving depositors high and dry. Fast forward a decade, and a glimmer of hope emerged: last year a Cypriot court ordered the government to make amends to one unlucky depositor. But whether this lone victory will set a precedent for broader compensation remains a major question mark.

The Convenience of Cash

There are many instances where, if you travel to another country, you can often pay with your home country’s bank card. However, the exchange rate is a significant question. Additionally, there are built-in fees. In some cases, carrying cash from your home country and exchanging it locally can be more beneficial than using a card or ATM.

Sure, digital payments are all the rage, but cash still holds its own. It’s secure and private and gives you a sense of control. If we go completely cashless, some people will get left behind. We need to embrace the new while still holding onto the old. That’s how we build a financial system that works for everyone.

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Features

Paving the Way for AI Success in Business

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AI in business

By Karim Azar, Regional Vice President – Middle East & Turkey, Cloudera

The digital landscape is evolving at an unprecedented pace, and at the heart of this evolution lies the transformative potential of artificial intelligence (AI). Across industries, AI is not merely a buzzword but a revolutionary force driving innovation, efficiency, and growth. Its impact extends beyond automation, touching every side of business operations and decision-making. It can revolutionize multiple sectors and fundamentally reshape the corporate industry.

Nonetheless, challenges arise with technological evolution, particularly in accessing and overseeing varied datasets across diverse environments. These challenges frequently act as obstacles to achieving successful AI implementation. In response to these challenges, the technology landscape is witnessing significant advancements in open data lakehouse technologies, providing a robust foundation for AI and analytics. Let’s delve into key technological developments and their advantages, focusing on the broader implications rather than specific products.

Unlocking Business Potential

AI has the potential to unleash new opportunities for businesses. McKinsey’s findings reveal that more than 62% of companies in the Gulf Cooperation Council (GCC) region currently utilize Generative AI in some operational aspect. The research underscores the substantial potential of AI to create tangible value in the GCC, with an estimated value of up to $150 billion.

This adoption trend is not without merit; statistics show that 83% of businesses adopting AI report substantial (30%) or moderate (53%) benefits. AI can address various challenges by providing predictive analytics and personalized customer experiences, enabling organizations to make faster and more accurate data-driven decisions.

Despite the obstacles in adopting AI, such as data management complexities and security concerns, offering air-gapped deployment for large language models (LLMs) is still a viable option. This feature boosts security, data privacy, and performance while also lowering customer operational expenses. However, overcoming these challenges requires more than just technological solutions. It demands a comprehensive approach that includes robust data governance frameworks, continuous employee training programs, and collaboration with regulatory bodies to ensure compliance with data protection laws.

AI Across Industries

AI is not a one-size-fits-all solution. It is applied differently across industries and business functions, including healthcare, finance, manufacturing, and retail. The potential uses of AI are vast, from boosting supply chain efficiency to transforming healthcare outcomes and customer service.

For example, in the healthcare industry, AI-powered predictive analytics can help doctors identify patients at high risk of developing certain diseases, allowing for early intervention and personalized treatment plans. AI algorithms can analyze market trends and financial customer behavior to recommend customized investment strategies. In manufacturing, AI-driven predictive maintenance can proactively anticipate equipment failures and schedule maintenance activities, minimizing downtime and reducing costs.

As businesses increasingly adopt AI, they invest in their organization’s future. By promoting innovation and agility, companies can leverage AI to maintain competitiveness in a digital era. Prioritizing data privacy and security helps build trust with customers and stakeholders, ensuring AI technologies’ responsible and ethical use.

AI is a significant transformation in how businesses function and innovate. Embracing AI opens up vast opportunities for organizations to reshape their operations, stimulate growth, and influence the future of business. While the journey may present challenges, the potential benefits are boundless for those willing to embrace the power of AI.

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Smart Cities and the Rise of Intelligent Transportation Systems: Exploring the Benefits and Risks of Vehicle Surveillance

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By: Dr Ryad Soobhany, Associate Professor, School of Mathematical & Computer Sciences, Heriot-Watt University Dubai

Intelligent Transportation Systems (ITS) have emerged as a transformative solution in urban areas, tackling challenges such as high traffic and pollution. These systems, incorporating a network of static and mobile sensors, including cameras on buildings or vehicles/drones, embedded in the smart city infrastructure, are revolutionizing traffic management. By harnessing data from cameras, in-vehicle GPS systems, in-vehicle Near Field Communication (NFC), IoT devices, and Artificial Intelligence (AI), ITS enable the monitoring and tracking of vehicles for Intelligent Traffic Management Systems (ITMS) or Public Transportation Management Systems (PTMS).

While intelligent transportation systems offer significant benefits, it’s crucial to acknowledge the challenges and risks they pose. ITMS provides real-time monitoring of traffic on roads and at junctions, while PTMS focus on managing transportation fleet and passenger information services. Emergency Response Management Systems (ERMS) primarily monitor the emergency responders of the smart city. The use of intelligent vehicle surveillance systems improves traffic management, public safety, and urban planning, but it also raises concerns about the data privacy and security of users and infrastructure, a risk that must be carefully managed.

Benefits

There are several benefits from the implementation of vehicle surveillance systems in urban areas and the most obvious one is a better vehicle traffic flow by using ITMS. Cameras placed strategically across the city monitor traffic to identify congested areas and road traffic incidents (e.g. accidents). Implementing dynamic traffic lights systems at junctions and temporary speed limits can improve traffic flow. Using AI, predictive traffic routing forecasts traffic bottlenecks and suggests alternative routing.  The use of PTMS leads to enhanced scheduling of public transportation; for example, the arrival/departure of trains/metro at the station is synchronized to feeder buses or taxis being stationed outside the station. There is an improvement in customer satisfaction and journey planning with real-time updates for public transport. Traffic flow is also improved by monitoring of cycle and pedestrian lanes, where safer cycle lanes will encourage road users to adopt cycling in certain urban areas adapted for cycling.

There is an overall improvement in public safety by better traffic management, with better response time to emergency situations by the ERMS, such as ambulances. LPR/ANPR (Licence Plate Recognition/Automatic Number Plate Recognition systems and GPS tracking systems in cars allow the monitoring of vehicles while they are located withing the bounds of the smart city. Stolen or wanted vehicles can be detected and followed through the city. The use of surveillance cameras, LPR/ANPR systems and GPS tracking can improve identification of criminal activities, which should enhance the response of law enforcement. Under-Vehicle Surveillance Systems (UVSS), which are cameras placed at strategic places on roads in the city take pictures or videos of the underside of vehicles to check the chassis for stolen cars. UVSS can also be used to detect contraband at ports or entry/exit points in smart cities.

The use of LPR/ANPR systems ease the management of Low Emission zones, which are areas where low emission vehicles (e.g. electric or hybrid vehicles) can circulate without charges and vehicles with higher emission rates have to pay an hourly or daily charge. The implementation of Low Emission zones can bring environmental benefits. The improved traffic flow in the urban areas can also lead to environmental benefits with less emissions in traffic jams and long traffic queues at junctions. Apart from environmental benefits, there are economic benefits linked to better health and overall happiness of citizens and visitors.

Risks

Several risks are associated with the amount of data collected from the vehicle surveillance systems. The main concern is the privacy of the smart city’s car drivers and car owners. Vehicles and their drivers are tracked everywhere they travel around the city and the speed they travel. This can lead to tracking drivers and without proper legal frameworks, the data collected can be used to encroach on the users’ privacy. The large amount of collected and stored data can be quite attractive to cyber criminals and might lead to cyber-attacks. Any data breach from these attacks might expose the personal information of drivers and their vehicles. Cyber-criminals can target the surveillance systems, for example hacking the intelligent dynamic traffic speed system and changing the traffic speed around the city.

Having video surveillance around the urban areas recording the public can lead to ethical issues. Most of the time, drivers might not have provided informed consent to participate in the vehicle surveillance systems. The lack of consent from users can lead to non-compliance with regulatory bodies and can result in legal challenges from user groups. Users need to be made aware that they are entering a vehicle surveillance zone and their data might be recorded. Vehicle surveillance systems can be used to discriminate against certain sections of the community, for example, young drivers might be unfairly targeted by the vehicle surveillance systems because they allegedly drive fast and dangerously, which allegedly cause accidents. Any cyber security attack or data intrusion can lead to users losing trust in the vehicle surveillance system.

The use of vehicle surveillance systems can benefit smart cities and enhance the quality of life of residents and visitors, but the authorities must respect the personal privacy of the public by ensuring that data are collected and processed ethically and guarded against any cyber-attack. Security policies and mitigation plans are primordial for vehicle surveillance systems.

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