Banking
AI in banking needs to be ‘explainable’
Published
1 year agoon
By
admin
Richard Shearer, CEO of Tintra PLC
In the world of banking, AI is capable of making decisions free from the errors and prejudices of human workers – but we need to be able to understand and trust those decisions.
This growing recognition of the importance of ‘Explainable AI’ (XAI) isn’t unique to the world of banking, but a principle that animates discussion of AI as a whole.
IT and communications network firm Cisco has recently articulated a need for “ethical, responsible, and explainable AI” to avoid a future built on un-inclusive and flawed insights.
It’s easy to envisage this kind of future unfolding, given that – in early February – it was revealed that Google’s DeepMind AI is now capable of writing computer programs at a competitive level – and if we can’t spot flaws and errors at this stage, a snowball effect of automated, sophisticated, but misguided AI could start to dictate all manner of decisions with worrying consequences.
In some industries, these consequences could be life-or-death. Algorithmic interventions in healthcare, for example, or the AI-based decisions made by driverless cars need to be completely trustworthy – which means we need to be able to understand how such AI arrive at their decisions.

Richard Shearer
Though banking-related AI may not capture the imagination as vividly as a driverless car turned rogue by its own artificial intelligence, the consequences of opaque, black box approaches are no less concerning – especially in the world of AML, in which biased and faulty decision-making could easily go unnoticed, given the prejudices which already govern that practice.
As such, when AI is used to make finance and banking-related decisions that can have ramifications for individuals, organisations, or even entire markets, its processes need to be transparent.
Explaining ‘explainable’ AI
To understand the significance of XAI, it’s important to define our terms.
According to IBM, XAI is “a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms.”
These methods are increasingly necessary due to the ever-increasing advancement of AI capabilities.
To those outside the sphere of this technology, it might be assumed that the data scientists and engineers who design and create these algorithms should be able to understand how their AI makes its decisions, but this isn’t necessarily the case.
After all, AI is – as a rule – employed to perform and exhibit complex behaviours and operations, and outperforming humans is therefore a sought-after goal, on the one hand, and an insidious risk on the other – hence the need for interpretable, explainable AI.
There are many business cases to be made for the development of XAI, with the Royal Society pointing out that interpretability in AI systems ensures that regulatory standards are being maintained, system vulnerabilities are assessed, and policy requirements are met.
However, the more urgent thread running throughout discussions of XAI is the ethical dimension of understanding AI decisions.
The Royal Society points out that achieving interpretability safeguards systems against bias; PwC names “ethics” as a key advantage of XAI; and Cisco points to the need for ethical and responsible AI in order to address the “inherent biases” that can – if left unchecked – inform insights that we might be tempted to act upon uncritically.
This risk is especially urgent in the world of banking and, for AML, in particular.
Bias – eliminated or enhanced?
Western AML processes still involve a great deal of human involvement – and, crucially, human decision making.
This leaves the field vulnerable to a range of prejudices and biases against people and organisations based in emerging markets.
On the face of it, these biases would appear to be rooted in risk-averse behaviours and calculations – but, in practice, the result is an unsophisticated and sweeping set of punitive hurdles that unfairly inconvenience entire emerging regions.
Obviously, this set of circumstances seems to be begging for AI-based interventions in which prejudiced and flawed human workers are replaced with the speed, efficiency, and neutral coolness of calculation that we tend to associate with artificial intelligence.
However, while we believe this is approach to diversity and fairness is absolutely the future of AML processes, it’s equally clear that AI isn’t intrinsically less biased than a human – and, if we ask an algorithm to engage with formidable amounts of data and forge subtle connections to determine the AML risk of a given actor or transaction, we need to be able to trust and verify its decisions.
That, in a nutshell, is why explainable AI is so necessary in AML: we need to ensure that AI resolves, rather than repeats the issues that currently characterise KYC/AML practices.
In response to the ethical and societal impact that can be caused by AI systems, several initiatives have arisen which aim to guide and support companies in the development of trustworthy AI.
One prominent initiative is the European Union’s Ethical Guidelines for Trustworthy AI, which puts forward a set of 7 key requirements that the design of an AI system must adopt, to be deemed ‘trustworthy’. One of these, entitled diversity, non-discrimination and fairness, states that ‘unfair bias must be avoided, as it could have multiple negative implications, from the marginalization of vulnerable groups, to the exacerbation of prejudice and discrimination’.
As we previously highlighted, AI systems are, as Verbeek terms, behaviour guiding technologies. They do not simply reflect society, but actively alter it through the decisions they make. Therefore, the design and training of AI systems capable of highly complex decision making must be undertaken with great responsibility. And to do so, we must be thorough and considered in our approach throughout the process, from design and training to deployment and monitoring.
Transparency and trust
The specific method used to achieve explainable AI in AML isn’t as important as the drive to ensure that we don’t place all our eggs in a potentially inscrutable basket: any AI we use to eliminate prejudice needs to have trust, confidence, and transparency placed at the heart of its calculations.
If we don’t put these qualities first, the ‘black box’ of incomprehensible algorithms may well continue to put a ‘black mark’ by the names of innocent organisations whose only crime is to exist in what humans and AI falsely perceive to be the ‘wrong place.’
Banking
How to avoid failing vulnerable customers as banks’ adoption of digital solutions grows
Published
6 days agoon
November 27, 2023By
admin
Tim Loo, Executive Director of Strategy, at Foolproof a Zensar Company
The way consumers and businesses handle their finances is becoming increasingly ‘faceless’. As banks shift away from pooling their resources into physical bank branches, the tranche of digitally enabled services and features continues to grow and evolve. This movement is not new, many people have been managing the transactional elements of banking online for years. But, what about those that haven’t? And, what about moving beyond the transactional?
This digitisation is being driven by both consumer demand and the need for banks to operate sustainably. However, a key question lies in whether some groups of customers are being left behind, especially those defined as vulnerable, which include the elderly, disabled, and digitally and financially illiterate individuals.
It is also important to note that vulnerability is a fluid dynamic, and that any customer can become vulnerable at any time in their life depending on changes to their immediate circumstances.
To help answer the question of whether some customers are being left behind, we recently commissioned research to uncover consumer sentiment towards banking services.
Tellingly, we found that more than two-thirds (67%) of banking customers feel that banks do not satisfactorily serve vulnerable groups, while almost one in four (24%) believe that banks do not care about helping customers navigate their way out of debt.

Tim Loo
These findings reflect a sentiment that the service provided by banks does need some personal flourishes, or, crucially, to bake the fluidity of changes to people’s lived experience into its digital product. Banks need to think hard about human connection across all touchpoints. At a minimum, this means exercising a duty of care towards the most vulnerable segments of their customer base, which can be any customer at any time depending on their immediate circumstances.
Identifying vulnerable customers
This starts by being able to identify such customers, which in turn relies on banks keeping fully up to speed with the evolving definition of vulnerability.
The Financial Conduct Authority (FCA), which recently launched its Consumer Duty regulations designed to better protect consumers by ensuring firms place them at the heart of their product and service strategies, states that 46% of UK adults show one or more characteristics of vulnerability. As the research was carried out in 2020, this figure could be even higher today given the economic hardship that has been endured over the past few years.
The FCA defines a vulnerable customer as “someone who, due to their personal circumstances, is especially susceptible to detriment, particularly when a firm is not acting with appropriate levels of care”.
There are four key drivers, including health, capability (financial literacy and confidence), resilience (the ability to cope with unexpected financial situations), and life events such as bereavement, which lead to added financial burdens.
Providing accessible support
In today’s volatile environment, it’s crucial that banks provide help and support to customers.
Many may be at risk of slipping into the vulnerable category as their relationship with financial products and services – especially mortgages, loans and other credit products – high interest rates and pressures from inflation, reduces disposable income.
In response, banks need to adopt a “design-for-all” approach and as a minimum integrate and continuously evolve accessible technologies into their service offering, recognising the diverse variables in people’s lives. On the softer side, this might also mean increasing the number of people trained to help those in financial distress and form deeper relationships with professional organisations and charities in this space to blend compliance with care for the customer.
In terms of digital application, moving beyond compliance as a tick box exercise and exploring new avenues is key. Applied in the right way, generative AI can also help solve this problem. If more of the transactional evolution of design can be managed through smart approaches to design and technology production and deployment, more members of design and engineering teams can be freed up to focus on new frontiers of digital and technology for vulnerable customers and their needs. By shifting focus, you can maintain the crucial part of the business without impacting service, while also embodying design for all as a strategic focus to better share the latent market.
It’s clear that simply leaning on automated customer service tools will not be sufficient here – for instance, according to our survey, nearly one in two banking customers (47%) feel that chatbots are not answering their questions. At the same time, nearly half (46%) called for more human interaction when dealing with their bank.
As well as providing more accessible support through digital and human channels, financial institutions must start to break down the stigma of debt – this will help them to be much more proactive in facilitating advice, planning and open dialogue to solve debt-related problems.
Building trust with customers
Customers, especially those who are vulnerable, are seeking someone to trust as they navigate through difficult financial situations.
These situations are not new, and banks have had to look out for vulnerable customers throughout their financial lives. Indeed, as the years have passed, the world of banking has transformed markedly, and largely for the better for most people.
That said, by connecting with and understanding customers, and developing a more human connection, banks can tap into an underserved group and enhance their brand reputation.
Banking
Q&A: Enhancing the employee experience in the banking sector
Published
2 weeks agoon
November 21, 2023By
editorial
As costs for everyday items continue to fluctuate and reports of company layoffs and budget reviews increase, economic uncertainty around the world has people on edge.
In banking, these dynamics all place a strain on services. A continued tight labour market also makes it difficult to fill open jobs and keep expertise and staffing at the rights levels.
Consumers too are dealing with a considerable amount of stress to make ends meet. When they reach out to banks, employees on the frontline often find themselves the undeserving targets of angry customers. People get anxious when they are unable to quickly resolve their financial questions. And this has an economic impact for banks too – angry consumers are more likely to air their frustrations on social media, leading to reputational damage.
On top of this, there’s considerable tension between banks and their employees as many are ordering return-to-office mandates, with JPMorgan Chase recently joining the list of many organisations making this a requirement. Employees are also faced with concerns that their jobs may be displaced with the rise of automation and AI, leading them to feel increasingly insecure. Under these conditions, it is more important than ever that banks invest in their employee experience to support staff retention and in turn, customer satisfaction.
David Porter, Managing Director of Financial Services at Genesys, discusses the impact of increasing pressure on banking services and their employees, and how banks can deploy the right tools to alleviate this.
How have customer expectations of banks changed in recent years?
As technology evolves, customer expectations are continually being reset. People today want more. More convenience, more ease of use, and more seamless experiences. Brands such as Uber, Google and Amazon are setting this standard. Being able to self-serve has become a differentiator between those that deliver on customer expectations, and those that don’t. These expectations are no different to the ones the banking sector now faces.
In the banking industry, customers want digital experiences that allow them to perform tasks with ease, such as checking balances, transferring funds, and setting up recurring payments, all without having to step foot inside a branch. Any issues that may arise must be addressed quickly and efficiently, but this hasn’t been straightforward to achieve. And when you look at the data, it’s easy to see why – only 18% of banking executives have reported being in a ‘mature stage’ of digital transformation efforts.
What barriers does the banking sector currently face approaching their customer experience?
An executive at Citi recently shared with me that efficiency, quick wins, and employee engagement were top priorities at present – and they’re not alone as it appears to be a growing industry trend. This is a step change, as typically, the employee experience has been viewed as secondary to that of the customer experience within banking. However, as the industry increasingly faces challenges in hiring throughout customer service functions, from front to back office, the employee experience has become increasingly important. Banks are far more open to exploring introducing tools and capabilities to improve this. Yet barriers to implementing these tools remain.
Banks are highly regulated, meaning that adopting technology in a way that is compliant with industry standards is always a challenge. Any new channels or capabilities that are deployed need to be properly reviewed and risk assessed, which in some cases means a slower time to market.
While the industry has seen huge progress, with challenger banks accelerating the transition to a digital-first banking model, many financial services companies continue to be held back due to legacy technology infrastructures and silos between department; particularly larger traditional banks. This results in disjointed customer journeys. In fact, according to our own recent research, only 26% of financial services companies today offer multiple channels for customer interactions and have integrated technologies and connected data. With consumer demand for digital skyrocketing and contact volumes increasing, more needs to be done to accelerate the transition to a unified omnichannel experience that provides visibility into the customer journey end-to-end.
What has the impact of this been on employees?
Employees are under increasing amount of strain to meet heightened customer expectations. For example, when a customer reaches out for assistance, they expect employees to have the necessary information on how and why they got there. Customers don’t like having to repeat authentication processes and the details of their issue. Being met with unsatisfying solutions can quickly lead to frustration as they feel like they’re going round in circles. Employees often take the brunt of these frustrations.
Additionally, with banking services seeing an increasing number of customers reaching out, employees are being stretched to meet service demand. This means that customers are not always matched with the best person with the right expertise to deal with their issue, leading to additional stress on both sides if a meaningful solution isn’t found.
Why is it important that banks invest in their experience?
For banks to be successful, they need to recognise the link between employee satisfaction and customer satisfaction. This will require an overhaul of traditional thinking around the employee experience.
While many banks are reverting back to office-based working, hybrid continues to be favoured by employees. As such, for banks to be competitive at a time where both customer and employee experience are closely tied, they need to cater to employee needs and empower them with ways of working that suit them. However, with no one set definition of what this looks like, banks are navigating doing so in a way that meets both employee and business needs.
At the same time, banks have faced an overhaul in service delivery. Branch-based service models have been in decline, which has pushed more customers to reach out via digital channels, increasing strain on services. When employees are under this amount of pressure, without the appropriate means to manage it, the outcome is often a high turnover of staff. Banks are then having to work harder to recruit new talent for roles that are increasingly difficult to fill, and remaining employees are increasingly stretched due to understaffing, which has a domino effect on the customer experience they deliver.
This has forced banking leaders to recognise the importance of employee engagement. With banks struggling to fill job vacancies, especially in the back office, they need to find ways to reduce employee frustration and make jobs more efficient, simpler and quicker. While the priority has been equipping customers with self-service options, now banks need to turn the table and provide employees and invest in the right tools to provide them with real and meaningful support.
With advancements in technology, particularly AI, banks have an opportunity to reimagine traditional work processes and empower their employees with the means to thrive. It’s important that instead of succumbing to fears about AI replacing employees, these are positioned as tools to help supercharge performance and create satisfying experiences for employees and customers alike. Doing so will not only drive greater efficiencies, but improve customer loyalty.
What technology can banks implement to improve their employee experience?
Banks stand a lot to gain by investing in modern cloud-based technologies. While banks face challenges in overhauling multiple legacy systems and ensuring solution aligns with strict regulation, adopting a single cloud-based platform means banks can better sync operations across the business for a more seamless experience for both customer and employee across the board.
At the same time, layering modern technologies, like AI, on top of this can add additional complexity, particularly when banks are dealing with sensitive customer information, meaning they need to have stringent measures to ensure data is handled securely. However, banks have already made significant progress with AI – predictive engagement and routing capabilities are supporting banks to offer personalised services by predicting customer needs and behaviours, and offering tailored products and solutions, vastly improving the customer journey.
Bots powered by generative AI are proving to be a gamechanger here, improving efficiency and outcomes for customers. Bots can quickly sort and prioritise knowledge content most relevant to customer inquiries, whether that’s on how to set up a saving account or where their local bank is. Through this, employees can save time resolving queries, while ensuring the solutions they provide are meaningful to the individual customer.
Additionally, investing in modern employee experience technologies tightly integrated with their customer experience can help banks improve engagement with their workforce. AI too has a role to play here. For example, through AI-powered coaching and real time insights, they can provide employees with valuable guidance on how to improve performance, supported with recommendations and training plans personalised to their specific need. This creates a continuous learning loop, where human capabilities are enhanced by AI’s support and insights.
Through implementing tools like these, and more specifically, AI, banks can become more employee centric and show themselves as employers who truly care. Employees have the support they need to thrive, allowing them to deliver an experience in line with what today’s customers want.
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