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REVOLUTIONISING GLOBAL BANKING THROUGH THE POWER OF AI

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Richard Shearer, CEO of Tintra PLC

 

Let’s imagine a scenario in which an individual living in Kenya wants to send money to London. If the person were living in the UK, this would be a very simple matter: two taps on their smartphone phone would result in a near-instantaneous transaction with no questions asked.

As a cross-border payment, however, this transaction looks very different: The individual’s money will have multiple arduous hurdles to clear as it’s passed from a local bank to a local electronic money institution [EMI] to a UK EMI, then on to a UK bank, before – if they are lucky – arriving in the hands of the beneficiary. This is a long-winded process riddled with red tape that could last as long as three months.

In addition, this already lengthy process is compounded by a further impediment: because the person is from an emerging country, they will – in the eyes of KYC/AML compliance teams – be considered high risk, despite the fact their earnings and transactions are entirely above board.

In essence, these challenges boil down to two key and interrelated issues: compliance processes are full of friction [often in the form of sluggish, manual, complex, and time-consuming KYC checks from multiple banks and EMIs], and Western KYC/AML teams are subject to bias, meaning they can’t [or possibly won’t] discern ‘good’ clients from ‘bad.’

Therefore, in order to truly achieve global banking, we need to develop a solution that will allow financial institutions to deal with both challenges quickly, efficiently and automatically – which is where technology, and more specifically, artificial intelligence, has the answer.

 

Leveraging technology to eliminate barriers and address bias

The banking industry hardly needs persuading of the benefits of AI in broad terms, as demonstrated by a recent report from McKinsey,which signposted several advantages of its integration, including boosted revenues, lower costs, and the discovery of unrealised opportunities through insights generated by powerful, data-hungry technology.

Perhaps more importantly, however, AI has the potential to significantly improve AML processes. For example, in predictive analytics, machine learning methods can be used alongside customer data to predict possible criminal behaviour – at lightning speeds and at an unprecedented scale – which simply cannot be matched by the people who remain at the heart of legacy banks’ compliance teams.

Not only can AI speed up the cumbersome processes that create the kinds of barriers faced by the likes of the individual from Kenya, but – crucially – the adoption of AI can also help to overcome the significant barriers represented by KYC/AML bias.

For example, using cutting edge AI tools to streamline onboarding and compliance procedures and automate all processes that currently involve manual invention, will effectively replace subjective human decision making with intelligent machines that have learned from years of data and experience. As a result, by reducing human involvement to a minimum, these tasks become fast, fair, transparent, scalable, and flexible enough to be applicable to customers and transactions across the globe.

Of course, AI isn’t always entirely free from bias – it’s made by people, and its insights are interpreted by people too. This reinforced by the last Nordics Anti-Financial Crime Symposium, which highlighted the need to watch out for bias at the programming stage.

In the context of KYC/AML classifiers, an unfair bias could occur if the machine is trained to mimic the human decision-making process, where the ‘right decision’ is fed into the AI solution. This can be overcome by providing evidentiary data instead, where the machine can learn from examples of transactions that resulted in complications as opposed to modelling outcomes on potential human prejudice.

Another key challenge for AI is generalisation caused by ‘narrow’ training data, such as when certain demographics and/or ethnic groups aren’t represented sufficiently in the training set. A similar phenomenon can occur in the context of KYC / AML where criteria for accepting a customer or transaction can vary across geographic area, meaning those in emerging markets may suffer as a result.

That said, it doesn’t mean AI can’t help in eliminating prejudice in AML procedures – far from it – it simply means we need to ensure the next generation of fintechs and challenger banks utilising this technology are feeding their AI models good data that provide explainable results – and that these entities are sincere in their desires to level the global banking playing field.

 

Revolutionising the global finance industry

Taking this kind of technology seriously would be nothing short of revolutionary for the global finance industry.

After all, as the Centre for Global Development has recently noted, KYC/AML discrimination can have serious ramifications in emerging markets, with those most likely to be impacted including “the families of migrant workers, small businesses that need to access working capital or trade finance, and recipients of life-saving aid in active-conflict, post-conflict, or post-disaster situations.”

In looking beyond the benefits that this new breed of global banking will have on individuals, there are also huge implications for the global economy.

McKinsey’s report on the future of cross-border payments points out that international payments revenues already amount to around $200bn globally – but a closer look at the figures reveals that while Western Europe sees 5.5 annual cross-border transactions per capita, Latin America only sees 0.7.

If compliance barriers were lowered through the leveraging of new technology, it seems perfectly plausible to suggest that places like Latin America would see cross-border transactions increase, with all the economic benefits associated with this increased flow of money on an international scale.

And, with AI and machine learning leading the charge towards revolutionised banking, it’s worth remembering that decreased prejudice needn’t come at the cost of increased risk: in fact, a recent Deloitte survey found that 41 per cent of respondents believed too many false positive AML alerts were the biggest AML compliance challenge faced by banks today.

Therefore, the right technology operated by new, forward-thinking financial entities has the real potential to simultaneously address the prejudices that underpin AML compliance processes, eliminate the sluggishness that those processes entail, unlock new streams of money to circulate in the global economy, and address the current lacklustre state of addressing financial crime.

When one really allows oneself to really absorb this new paradigm, the potential is there for AI to completely repackage the way in which the global banking industry operates. The question is who will be first to the party!

 

Business

Accounting Automation in the Future

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Accounting automation is the process of streamlining repetitive tasks in financial processes. For example, some processes like invoicing are time-consuming and repetitive. Automation can reduce manual labor and save businesses both time and money. Also, it helps improve accuracy, reduces errors, and provides more accurate financial reporting.

Accounting automation in the future will be increasingly important for businesses to stay competitive. But every new change comes with both advantages and challenges. Let’s dive in to get ready for this future trend.

 

Potential Future Benefits of Accounting Automation

Increased Efficiency and Cost Savings

Accounting automation is a great way to increase efficiency and cost savings. For example, AI bookkeeping uses advanced algorithms to automate many accounting tasks. So, companies can track expenses, prepare financial reports, and more using AI.

It reduces the time needed for manual entry. So, businesses can spend fewer labor hours on tedious processes. They can increase efficiency by freeing up resources for more strategic work. It also helps reduce errors and inconsistencies associated with manual processes. So, the cost of compliance is lower because of greater accuracy.

 

Improved Accuracy and Reliability

Accounting automation can improve accuracy and reliability in accounting processes. For example, Automating bank reconciliation is less prone to errors from human mistakes or miscalculations. You can automate the process to identify discrepancies between the bank statement and accounting records. It helps to ensure that financial reports remain accurate and reliable. So businesses can take corrective action faster than processing data manually.

 

Streamlined Business Processes

Streamlined business processes involve eliminating unnecessary steps, reducing paperwork, and automating repetitive tasks. This allows businesses to focus on higher-value activities, such as developing new products, improving customer service, and developing strategic plans for the future.

 

Making a Better Decision

Accounting automation can enhance decision-making in 3 ways.

1. It enables businesses to access real-time information from multiple systems. So they can identify trends for better decision-making.
2. Automated accounting also helps with forecasting, budgeting, and auditing tasks. It enables businesses to be more proactive in their decision-making processes.
3. Also, automated accounting tools can integrate with enterprise resource planning (ERP) systems. They can manage data across the enterprise and make concise decisions that are favorable to the company as a whole.

 

Increase Customer Satisfaction

Accounting automation can help businesses increase customer satisfaction by streamlining their processes and providing a more efficient customer experience. For example:
4. Automated accounting systems can automate tedious manual tasks such as invoicing, data entry, and payroll processing. This allows businesses to focus on other aspects of their operations that are more important for customer service.
5. Automated accounting systems can also provide customers with more accurate and timely financial information. The information can help them make better decisions about their finances.
6. Also, accounting automation enables businesses to respond quickly to customer inquiries. It helps reduce wait times and improve the overall customer experience. So, you can build better relationships with their customers.

 

Improved Accessibility

Accounting automation takes place online or comes with cloud-based solutions. So, you can access your information and do your job from anywhere instead of being confined to one spot.

 

Challenges to Implementing Accounting Automation in the Future

Cost of Technology Infrastructure Upgrades

Automating an accounting system often requires businesses to invest in new hardware and software, such as servers and other associated equipment. These upgrades come with a hefty price tag that may be difficult for small businesses to afford.

There are also extra costs, such as installation fees, setup charges, software licensing fees, cloud storage costs, and maintenance fees.

 

Training Requirements for Staff Members

Accounting automation involves using advanced technology to automate certain processes. So, it creates a need for trained staff members who can handle the new technology. Training requirements vary depending on the type of software used.

Some common training includes record-keeping procedures, software applications, and troubleshooting skills.

 

Regulatory Compliance Issues

Accounting automation can be a time-saver, but it also requires firms to be aware of the applicable rules and regulations. Companies must ensure that their automated systems are compliant with relevant laws and regulations such as Generally Accepted Accounting Principles (GAAP), International Financial Reporting Standards (IFRS), and other applicable accounting standards.

Besides, they must also comply with legal requirements related to taxes, financial statements, and other reporting obligations.

So, businesses must consider the complexities of regulatory compliance when automating accounting.

 

Security and Data Protection Concerns

As businesses move their accounting processes to the cloud, they are exposed to a wide range of potential security risks. Data breaches can cause significant damage to the business’s financial and reputational integrity. Besides, the complexity of automated accounting systems can make it difficult to identify and detect suspicious activities or errors in the system.

To ensure data is kept secure, businesses must have strong measures in place to protect against unauthorized access, encryption, and regular backups of data.

Furthermore, companies must train their staff on the proper use of the system. It helps staff to know how to protect confidential information from being accessed or misused by unauthorized personnel.

Businesses may also need an experienced IT team to monitor and maintain the system to keep up with any changes or updates for optimal performance.

 

Final thoughts

Accounting automation has come a long way in the past few decades. It is likely to continue to advance in the future. As technology continues to evolve, more businesses will likely begin taking advantage of automation in their accounting processes. So, businesses should be aware of the potential challenges and prepare to stay competitive.

 

Author bio: Kassidy Li is a Certified Public Accountant and online entrepreneur who is passionate about helping people to solve problems and grow wealth with accounting knowledge and technology. She has 10+ accounting experience in small to large-scared corporations and expertise in financial accounting, management accounting, budgeting, and payroll.

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Business

Three ways data can help financial organisations thrive in today’s economy

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By Rinesh Patel, Global Head of Financial Services, Snowflake

 

Financial organisations are caught in the middle of an ever-evolving landscape caused, in part, by emergent fintechs, shifting consumer expectations and increased regulatory change. Businesses are therefore turning to their data, re-imagining how they collect, process and analyse it, to drive growth and opportunity.

Despite this intention though, firms can often find themselves overwhelmed with the amount of data at their fingertips. Data tends to reside in individual departments that have no secure, efficient way of sharing it with other teams, creating silos of information. When teams need to collaborate, organisations are faced with additional costs and complexities in the movement of that data. The current infrastructure used by many financial institutions is not able to support the changing requirements of the industry, where data is the lifeblood.

Rinesh Patel

Firms looking to harness their data should leave behind their outdated legacy architecture and implement an enterprise data strategy with a cloud-native platform. They can reposition themselves to accelerate time to market and value, with differentiated products and improved client offerings to gain a critical competitive advantage. Here are three ways that financial services are using better technology and enhanced data management to add business value.

 

Adhering to regulatory requirements

The volume of global regulations and reporting obligations has risen exponentially in the past decade, creating greater complexity and security challenges for firms capturing and processing data. Many of these regulations were taken by supervisors to ensure financial stability after the financial crisis of 2008. Regulators have greater expectations of firms with the aim of risk mitigation and transparency. With advanced technologies facilitating data capture, storage and analysis now available, supervisory bodies are also keen in part, to ask for additional disclosures because it’s now possible to demand more documentation and seek greater transparency.

The landscape of differing interpretations, overlapping regulatory requirements across asset classes and geographies and strict, even unrealistic deadlines for implementation have forced customers to take tactical quick-fix solutions, elevating operational risk and the chance of regulatory fines. Compliance departments have therefore been spending years building reporting processes, managing inconsistent data sets, maintaining ageing data stores and importantly overseeing differing levels of governance, adding more cost and complexity to the task at hand. For a large multi-segment global bank or asset manager this fragmented and manual approach to data management and analysis is not sustainable given the scale of processes and multi-geographic considerations that they have to comply with.

As regulators continue to push the long-term structural change agenda, financial services must now ready themselves to meet more robust reporting requirements to comply with the ever-changing regulatory landscape. The objective is to simplify and better manage data across teams with the governance and security provided by technological capabilities now offered through modern cloud capabilities to drive needed reporting. This will allow firms to replace old and inconsistent data with a centralised data architecture, providing a single source of truth. The time and cost reduction from data sourcing, ingestion, and the normalisation of data for analysis, can shrink to significantly streamline reporting processes.

 

Customer 360 experience

Consumers provide financial institutions with a vast amount of information, ranging from their banking habits to their behavioural preferences. Financial organisations have traditionally been slow to tap into the totality of this information to provide a better experience for customers.

The quest to provide greater visibility and a 360-degree view of customer behaviour is at the core of financial services organisations’ priorities. Customers want smooth, easy digital experiences that can speak to their desire for ease of use and convenience. This is seen in the ways virtual banking consumers have opted for technologies that are simple to interact with, self-directed and frictionless when it comes to carrying out digital transactions. New regulations, such as PSD2 and rules around open banking have also primed customers to expect more.

The challenge for legacy institutions is to bring the ease and usability of digital-first platforms with the sophistication of a major, global provider. Tapping into the full spectrum of data created by consumers is central to a successful transition.

Wealth advisory, investment management professionals are increasingly looking at data capabilities to support ongoing relationship management with their clients. Using data to understand customers in this way helps banks to successfully move customers up the wealth value chain. Wealth management organisations can digitise the investment process – from finding customers to managing accounts, and offering bespoke plans. Effective use of data in this sector can free up time for advisors, helping to retain key customers and charge higher commission levels thanks to a new level of personalised service.

 

Developing an effective ESG strategy

Environmental, social and corporate governance (ESG) considerations have grown in significance with increasing stakeholder pressures, driving a response by firms to prioritise their sustainability agenda. To understand, evaluate the problem and take action, firms need access to technology providing holistic ESG data capabilities and solutions, with performance and scale.

Financial firms are amassing large data sets from the public sector, including government reports, scientific bodies and private sector reports, to understand and address the climate challenge. Businesses are moving with urgency to acquire robust data sets, to meet ESG criteria and sustainability metrics needed to evaluate impact and make progress against their own commitments. There are several pervasive business use cases for teams experiencing ESG data challenges, including portfolio construction, financial planning and regulatory reporting that will require an effective ESG data management strategy.

Ever present challenges in the ingestion, standardisation, and sharing of ESG data will be at the forefront of every organisation – as they process the magnitude of the challenge and transform their operations to address the issue. With cloud-native solutions, firms can use ready-to-use query data across established marketplace data sets. They can then share that data across teams in a secure, governed way – with greater speed to market. Organisations can meet the need for scalable analytics, and access a data ecosystem to build their own proprietary ESG applications for different user and workflow requirements.

 

A business fit for the future 

With data cloud solutions, businesses can effectively analyse the vast amounts of data available to them, equipping them to meet the ever-changing financial landscape. Leaving behind legacy systems will open up a multitude of opportunities and benefits that will drive business growth. This includes developing a 360 view of the customer, improved data governance and the opportunity to use data to support an effective ESG strategy. Without the ability to harness data through the cloud, companies will get left behind the competition and struggle to meet the standards that modern consumers expect.

 

 

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