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How AI is revolutionising data in the banking industry

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Zahi Yaari, VP of EMEA, SnapLogic

 

It should go without saying that data in the banking industry is some of the most valuable a business can own. Indeed, for many organisations the data they possess is their most valuable asset and as this data grows in both quality and quantity, so too does its value.

However, many businesses, particularly those in the banking sector, are not getting the most out of their data by allowing silos to form within their organisation, whilst also squandering the talents of their most skilled employees.

When data is locked in different locations, it becomes a burden rather than an asset, weighing down the flow of communication within your business and making simple processes complex and time-consuming.

Take, for example, the most basic line of business processes. Where data silos exist between different teams, the most fundamental back-end tasks become unnecessarily difficult, as chains of communication are weighed down by critical information stored in a variety of different places.

Zahi Yaari

Many banks are essentially building data vaults, inaccessible by other teams in their organisation. Not only can this greatly harm the efficiency of a business’s employees but it also restricts the ability of executives to access valuable data insights.

As the quantity of data increases, banks are rapidly becoming victims of their own success, being hamstrung by the amount of data they possess. What should be their most valuable asset ends up weighing them down and ultimately, it becomes the job of an already overburdened IT staff to step in to help glue together data that should flow seamlessly in the first place.

To make matters worse, IT staff are not the only teams under increasing pressure from unnecessary workloads. Banks are also facing the challenge of legacy technology making even the most basic reporting tasks incredibly labour-intensive.

Month-end processes can weigh down entire finance teams in a mass of administrative tasks, whilst executives wait to gather insights from manual reports.

This is clearly not right, banks in particular need to have the most efficient transfer of information possible, whether it is data in-between teams or insights to the C-suite.

Looking to AI

The realisation that AI-driven automation can both integrate different tools and technologies whilst also freeing up a large proportion of employees’ time has helped the banking industry revolutionise their use of data.

Whilst banking and finance as an industry has often fallen short when it comes to digital transformation, relying on legacy systems for far too long, proactive banking groups are beginning to show that the adoption of cloud technology, integrated systems and process automation can push organisations out ahead of the competition.

Banks that adopt new technologies are changing the competitive landscape within the industry. In particular, cloud-based challenger banks are putting pressure on incumbent banks’ revenues and will continue to do so, unless these banks evolve with the times.

With evolution comes innovation, and AI and machine learning have two key roles here. Firstly, AI-powered integration platforms can glue together different areas of a business, not only allowing for data pipelines to be built with ease, but actually suggesting integrations to the business user with up to 90 percent accuracy. This means that every user can be empowered to take full advantage of advanced technology that can make their work lives far easier and more efficient.

Secondly, once these pipelines are built, AI works to automate highly-repetitive, low-skill tasks that otherwise burden talented teams in manual processes. By learning from billions of existing data flows, these AI-powered platforms can eliminate the data and integration backlog.

The dual benefits of an increase in productivity and efficiency, whilst also cutting down costs and employee workloads makes automation and AI a no-brainer to many executives.

This is particularly true as these executives can benefit from real-time access to data, gaining insights that were impossible with legacy tech and manual processes.

Why now is the time to adopt AI

With the rise in self-service, low-code technology, digital transformation no longer requires a difficult adoption process. In fact, platforms are designed for ease-of-use, meaning companies no longer have to factor in skill shortages or training costs.

One organisation that benefited from this self-service technology was Hampshire Banking Trust, who discovered they could utilise a low-code-no-code infrastructure to quickly deploy these technologies, connecting together their various tools and applications with ease. This meant their slim IT team could easily break down silos within the business whilst also relying on AI to help individual users to manage routine tasks by themselves.

AI integration technology is like the nervous system of a business, passing information from one part to another, whilst also responding to changes and challenges, scaling as needed.

Furthermore, given the vast amounts of highly sensitive information that banks handle and as data regulations continue to evolve, the banking sector needs to stay ahead of the curve; or else poorly-managed data could result in fines and serious reputational damage. Adopting a solution that can not only safeguard critical data and ensure compliance with regulations, but also evolve and grow with the business, is therefore critical to any bank’s future.

This speaks to the larger issue – agility. Where the banking industry has failed to adopt these new technologies, there have been growing challenges caused by inflexible business processes and overburdened staff.

The benefits of adopting AI and ML technologies are clear: they can automate the data infrastructure of a business, both freeing up employees and breaking down silos to create an efficient and flexible business.

Now is the time for banks to reevaluate their data needs and look to AI as the key to unlocking the true value of their data.

Banking

The Future of Banking: Streamlined Cash Management for ATMs

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By

Gaetano Ziri, Innovation Manager, Auriga

 

“Maintaining free access to cash for the community demands robust strategies to mitigate the escalating costs incurred by banks and ATM operators in handling cash. A pivotal step in this direction is modernising cash management systems to foster efficiency and reduce operational costs.

Back in 2018, a report by McKinsey underscored the urgent need to overhaul the largely manual and disjointed systems relied upon by nearly half the banks worldwide for forecasting cash requirements at branches and ATMs. Despite the decrease in cash usage noted by the European Central Bank, the cost of managing cash has not abated, primarily due to surging labour costs.

To reconcile the demand for free access to cash with the requisite cost reductions, banks are increasingly turning towards tech-driven solutions in cash management that elevate service levels while driving down expenses.

The Complex Landscape of ATM Network Management

Operating a vast ATM network can be a double-edged sword for banks, simultaneously offering customer convenience and engendering considerable challenges, including substantial cash handling, management, transit and security costs. Each ATM embodies a multifaceted operation involving numerous cash transfer operatives, necessitating a coordinated strategy to forestall costly inefficiencies.

The remedy is a holistic, data-centric approach to streamline the management of intricate ATM networks and counter the escalating costs associated with cash access. The merits of such an approach, grounded in continuous data collection and analysis across ATM networks, encompass:

  • Strategic Planning: Leveraging real-time data to craft bespoke strategies for individual branches or regions, assuring optimal cash flow management and averting superfluous cash loading orders.
  • Operational Transparency: Facilitating stakeholders with instantaneous access to accounting and operational data relating to cash supply chains, thereby enabling timely interventions and adaptations.
  • Enhanced Customer Experience: Minimising ATM downtimes to guarantee uninterrupted cash access to customers, enhancing their banking experience.

Innovations in Cash Management: A Closer Look

So, how does this revolutionary cash management technology function? The answer lies in a series of sophisticated features that employ cutting-edge predictive analytics, automation, and data-driven decision-making:

  • Predictive Analysis: Forward-thinking solutions predict cash necessities of distinct units, offering precise demand and cash flow projections by considering variables such as seasonal fluctuations, holidays, and daily usage trends.
  • Automation and Monitoring: Swapping manual processes or basic mathematical functions with modern software solutions for cash management ushers in real-time monitoring and efficient intervention planning, which can potentially diminish order management costs by a significant margin, whilst improving precision and operational fluidity.
  • Optimised Cash Transit Management: Utilising predictive analytics to strategically plan cash restocks, thereby reducing the likelihood of ATMs depleting their cash reserves and improving customer satisfaction.
  • Data-Driven Decision Making: Availing a comprehensive dashboard to generate timely reports and monitor critical metrics facilitates strategic decision-making grounded in accurate data, substantially reducing residual cash stock in ATMs.

As the financial landscape evolves, banks and financial institutions are impelled to adapt and innovate. Traditional cash management approaches are increasingly becoming outdated, paving the way for modern, data-driven solutions. These not only embody a commitment to technological advancement but also signify a strategic movement towards future readiness.

Embracing such technologies promises streamlined operations, substantial cost reductions, and a superior customer experience, setting a new standard in ATM network management.”

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Building towards an inclusive financial future

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By Catharina Eklof, CCO of IDEX Biometrics

  

From the visually impaired to displaced migrants, the unbanked, and people living with dementia – a burgeoning financial gap exists across many areas of society. In fact, as of late 2021, almost one-third of adults around the world were reported as unbanked according to the World Bank Group. That’s around 1.7 billion people – with half coming from the poorest 40% of the world’s population. Being financially excluded in this way means not having access to common financial services including savings accounts, loans, a credit rating, or even a bank account. Those who are awaiting clearance to join a country’s financial ecosystem, such as migrants, are also finding themselves left behind by the modern financial infrastructure.

As societies reliance on digital and contactless transactions over cash continues to grow, this financial gap is only set to widen. In less than 10 years, the share of Americans not using cash for payments has increased by double digits, reaching 41%. By 2031, cash payments are expected to make up only 6% of all transactions.

Fortunately, biometric smart cards can bridge this gap for people in the Global South, migrant populations, as well as those with visual or cognitive disabilities worldwide, who deserve to feel secure, included, and independent.

 

The challenges surrounding passwords

 COVID accelerated the transition from cash to contactless payments and the use of digital wallets, creating a challenge for many. By 2024, it is expected that digital wallets and cards will account for 84.5% of all e-commerce spend.

Digital transactions traditionally rely on the use of PINs that can easily be forgotten, as studies have found that we manage 100 passwords on average across various sites and services. In the US alone, consumers report relationships with more than three financial institutions and have more than four accounts per household. The challenge of password recollection is only growing. To counter rising cybersecurity threats, several countries now mandate two-factor authentication for retailers and service providers, creating further complexity.
However, organizations are responding to financial exclusion. Card provider Mastercard introduced its contactless PayPass offering, as well its Touch Card developed alongside Amjan Bank which enables the visually impaired to distinguish between their cards. Both look to provide a better customer experience for people struggling with the digital changeover. For those living with dementia, Mastercard has also partnered with Sibstar and the Alzheimer’s Society to create a specific card where limits, transactions, top-ups and notifications can be viewed and managed via a complementing app. Likewise, Turkish neo bank Papara introduced a Bluetooth debit card that provides visually impaired users with audio prompts when making payments.

 

Protecting the visually impaired

There are at least 2.2 billion visually impaired people globally. In 2019, it was found that 89% of visually impaired have been victims of fraud or have made errors when paying for goods and services. This figure comes prior to the pandemic, and the proliferation of digital transactions, suggesting an even bigger concern today.

PINs present an obvious security issue for this demographic, with others able to oversee their inputs and then manipulate them. Contactless payments go some way to solving that problem but pose the risk of fraud as there is no PIN verification below the increasing threshold amount, now at £100 in the UK, where the average annual wage is £27,756. In India, where the average annual wage is 9,45,489 rupees (roughly £9000), contactless limits are set to 5000 rupees (£48). Many accounts also require visual-based inputs to prove identity, such as CAPTCHA, proving as a barrier for the visually impaired.

Enhancing awareness on a regulatory level is key for driving change and reassuring vulnerable groups. The EU Accessibility Act is an example of how payment service providers are obliged to comply with accessibility standards. This includes making interfaces perceivable, operable, understandable, and robust, to ensure that individuals with disabilities can effectively navigate payment interfaces.

 

Paving the way with biometrics

 Including braille on cards for easy identification is a crucial step for the visually impaired. This can also be used on biometrics smart cards, with sensor textures to confirm the user has selected the correct method of transacting. Not only do these cards provide convenience and inclusivity, but they also promote ultimate security by linking a person’s identity directly to their fingerprints. This data is encrypted within the card itself, reducing any concerns surrounding fraudulent behaviour or of data being lost via a centralized breach or large-scale hack.

In this context, biometrics can be used to serve the unbanked and those currently unrecognized within national infrastructures. South America is an example of an early adopter of biometrics, turning to the solution to cope with swelling population sizes, and the challenges associated with accessing proof of identity when setting up traditional bank accounts. Meanwhile in India, pension payment fraud has dropped by 47% thanks to bypassing the need for prior credit ratings or credentials.

Liveness detection, however, which ensures the biometric sensor is reading a true biometric source (rather than a false or recreated image of one), is vital to the success of financial aid programs globally. Securing remittances through biometric authentication ensures transparency and better fund control. Directing funds to cold wallets or biometrically authenticated cards can also improve program efficiency, safeguarding the interests of individuals and communities.

Overall, the biometrics market is expected to grow to US$87.4 billion by 2028, at a CAGR of 17%. Whilst its value as a simple and secure method of transacting is growing substantially, you can’t put a price on its impact on those who have so-far fallen through the gaps of finance’s digital revolution.

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