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The Great Resignation: can AI help businesses with recruitment?

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by Joseph George, MD, Dufrain

Artificial Intelligence (AI) was a term coined in 1950s America, but it wasn’t until the 1980s that we saw the first real “boom” of discussions on the subject globally. Hollywood and literature exploded on the topic, dreaming up Star Wars’ CP-30, and Space Odyssey’s HAL 9000 which fed into the psyches of scared employees who feared they would soon be replaced by robots.

In more recent years, however, the conversation has turned. AI is now seen, and used, to enhance a business’s day to day: automating tasks for efficiency and removing the risk of human error where appropriate. AI is just an evolution of traditional tech – if trained with accurate data, it is there to help businesses better streamline everyday processes at a lower cost.

An area where AI has taken off in recent years is recruitment. Using tech to help a business increase the efficiency, reliability and accuracy of its recruitment processes has become even more important in recent years, as Brexit and the more recent Coronavirus pandemic sparked a mass resignation of professionals in all sectors. Financial and professional services in particular are feeling the pinch.

Potential bias

As a basic example, AI can be trained to sift through applications for a certain role, pulling out candidates that it deems to have certain qualifications via the identification of key words. The intention is that this removes the potential subconscious bias of a human process.

However, it is important to note that AI driven algorithms are only as good as they are trained. They are taught by the data which is fed into them, including personal information and past examples to be replicated (or not, as the case may be).

Advanced artificial intelligence uses machine learning to mimic human behaviour. It takes volumes of structured data to achieve this effectively and avoid the risk that it will unintentionally learn a human’s unconscious bias by following the same trends as the data. Well publicised cases have shown recruitment algorithms favouring candidates based on gender, background or upbringing by mimicking previous trends. It’s vitally important to get it right if we’re going to deploy it.

The role of data

Establishing sound data processes is crucial reducing the risk of discrimination. That means ensuring only the correct type of data is used in AI systems. Data should only be collected from authoritative sources and in compliance with GDPR and privacy laws. Only the highest-quality data, which is relevant to the task, should be used. It should also be anonymised where possible with limited identifiers which could perpetuate bias and it is down to the user, in this case the employer, to make sure that their data is in a fit state to ensure the technology will work ethically and effectively. The role of reporting and transparency driven by various regulators across differing industries plays a big part here.

Financial institutions should not be shy in outlining what data algorithms are processing, and how they are doing so. That way, all parties can be confident that ethical standards are being met.

Less time, more results

The reward of doing all of this properly is tangible. Not only can it make the process more efficient, but it can also help that business stand out to the candidate by having more time to spend engaging with candidates, building relationships and improving overall experience.

In the environment of ‘The Great Resignation’ and high competition, AI can also help businesses find a higher quality of candidates quicker, and from a larger pool. By leveraging machine learning, substantial data pools can be searched in seconds to identify candidates who meet search criteria. This technology is especially helpful in the recruitment of what are known as “passive candidates” – people who are not activity looking for a job but may fit the bill.

Once potential candidates have been sourced, humans can step in to begin the vetting process and ensure that there can been no bias. The more that the technology is used, refined and corrected, the better the results will be each time.

It is vitally important that the data is good, but while we are still refining AI processes, we must also ensure that a diverse workforce is in place to decide what good looks like, what data is being used and, ultimately, when to override a decision made by an algorithm. Using this method, the way in which AI is trained will get infinitely better over time.

Clearly, artificial intelligence can improve recruiting efficiency and effectiveness. It can scan for key words and eliminate people who may not fit specific criteria, but the human element cannot be replaced, and AI is not the sole solution to increased proficiency.

Used alone, it may provide data that does not prove useful, it will ignore the human aspects of culture fit and it may overlook qualified candidates with underachieving resumes. Technology must be used alongside human interference to ensure the best process for recruitment across the board.

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How can businesses boost employee experience for finance professionals?

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By Martin Schirmer, President, Enterprise Service Management, IFS

Over the course of the last year, The Great Resignation has seriously impacted organisations across the globe. Staff are quitting in huge numbers, leaving companies unprepared and struggling to fulfil their workloads. In fact, mass departures are happening at all levels of the labour market, as employees attempt to adapt to the hybrid working model and growing socio-economic uncertainty.

In light of this, optimising the employee experience (EX) to attract and retain talent has become a top priority for employers. Organisations have come to understand the necessity of taking immediate steps to drive employee engagement and reshape workplace culture.

The financial services (FS) industry is no exception to this trend. From increasing employee burnout to growing career dissatisfaction, the pandemic has exacerbated the need for transformation across finance teams. This is exemplified by recent data from Spendesk, which found that approximately 40% of finance professionals are willing to leave their roles or already have concrete plans to do so.

Organisations looking to get ahead of the competition must put in extra efforts to retain their existing workforce. The fact is that employee expectations and requirements have irreversibly changed, with more workforces becoming increasingly distributed. Today’s hyper-connected workforce values flexibility and simplicity, and it is organisations which offer these experiences that will succeed in the long term.

As part of this process, finance companies must look towards the power of technology to create seamless user experiences across devices. From automating workflows to improving overall efficiencies, Enterprise Service Management (ESM) can help organisations to boost user satisfaction and go that extra mile for their employees.

How poor EXs are driving finance teams to quit

With over 40% of employees spending a significant proportion of their time carrying out mundane, manual tasks, it is not surprising that poor EXs are having a detrimental impact on job satisfaction. Finance teams in particular have been slower to digitise core processes, leading to a heavy reliance on manual tasks. This not only increases the amount of time spent on each task, but also impacts the engagement levels of finance professionals who cannot focus on more strategic aspects of their roles.

As a result of the pandemic, flexibility has also moved to the forefront of finance teams’ desires. Given the fast-paced nature of this industry, the conversation surrounding work-life balance has increased rapidly. Failure to offer flexible working policies, coupled with a lack of technology to facilitate this flexibility, has led to poor EXs across the board.

Most notably, the overarching move to omnichannel, digital-first approaches has dramatically reset both customer and employee needs. Finance is the third-slowest running corporate function behind legal and IT. Operating in a competitive environment, 73% of finance operations are facing pressures to speed up, improve efficiency, and prioritise automation.

Mitigating the problem using technology

ESM, an offshoot of IT Service management (ITSM), is the cornerstone of smart digital transformation for organisations. It can help finance teams to streamline and automate routine processes, such as monitoring the status of service requests, approving expenses, sending invoices, and tracking payments. In turn, this will free up employees’ time, reducing the burden of manual tasks and enabling them to focus on the more strategic tasks.

Another advantage ESM can offer finance teams is the ability to adapt to each department’s minimum requirements for data privacy. Accounting, for example, needs additional layers of compliance built into the system.

ESM can also facilitate cross-departmental collaboration, helping finance professionals to communicate with the wider business and perform tasks more effectively.  Organisations can use ESM to incorporate all internal services into a single platform, offering employees a well-rounded view of the business and promoting a sense of community across all levels of an organisation. This will boost productivity, whilst enhancing visibility and control.

Ultimately, the current job landscape has brought with it a new set of challenges. Organisations in the FS industry looking to navigate the storm and retain top talent must refocus their efforts on bolstering the EX. Embracing a new era of technological innovation that empowers employees and boosts engagement is a critical step in this process.

 

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CBDCs: the key to transform cross-border payments

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Dr. Ruth Wandhöfer, Board Director at RTGS.global

 

If you work in finance, you’ll have been hearing a lot about central bank digital currencies (CBDCs) and the moves different markets are making towards using, regulating and evaluating the viability of moving to an economy based on digital currency.

We are already seeing progress in the research, piloting and introduction of CBDCs into the financial system. The Banque de France for example, recently launched its second phase of CBDC experiments in line with the “triple digital revolution” unfolding in the financial sector. The infrastructures of financial markets and fintechs, however, are not prepared to accommodate their security, stability, and viability.

This could be an issue in the not too distant future. Each year, global corporates move nearly $23.5 trillion between countries, equivalent to about 25% of global GDP. This requires them to use wholesale cross-border payment processes, which remain suboptimal from a cost, speed, and transparency perspective. In fact, the G20 cross-border payments programme considers improving access to domestic payment systems that settle in central bank money, as one of the key components in facilitating increased speed and reducing the costs of cross-border payments.

The current state of cross-border payments

International transactions based on fiat are currently slow, expensive, and highly risky due to today’s disconnected financial infrastructure, messaging, and liquidity. Wholesale cross-border payment settlement can take 48 hours or longer, which is not practical in today’s digital world. Even if not every market moves to CBDCs, in an increasingly digital era, cross-border settlements between central banks will unavoidably involve dealing with CBDCs. So, not only will we have different currencies, we’ll have different technical forms of currency being exchanged – digital and fiat – as markets adopt CBDCs at different rates, adding another layer of complexity to cross-border settlements.

While there is much anticipation about the opportunities CBDCs can bring, the adoption of this technology will only be widespread if payment and settlement capabilities are overhauled to allow for new innovations in currencies.  This need for transformation represents an opportunity to redesign existing infrastructure to support cross-border CBDC transactions.

The current cross-border payments system involves correspondent banks in different jurisdictions using commercial bank money. Uncommitted credit lines used in cross-border transactions are a potential risk for any bank that relies on credit provided by a foreign correspondent bank. Interestingly, there is no single global payment and settlement system, only a complicated network of interbank relationships operating on mutual trust. While trust has allowed financial systems to function smoothly, when it begins to fail, as it did during the 2008 financial crisis, the result can be catastrophic.

Following the crisis, the Bank for International Settlements (BIS) implemented the Basel III agreement, which required banks to maintain additional capital against correspondent banking account exposures. These risk-weighted assets impose a costly capital charge on positions held by banks at other banks under correspondent arrangements. While this framework helps combat risk, it neglects to address the inherent problems in traditional correspondent banking that contribute to these risks.

Making the case for CBDCs

CBDCs can offer an improvement in settlement risks and are certainly thought to have potential benefits by the BIS. If implemented correctly, wholesale CBDCs can indeed accelerate interbank transactions while eliminating settlement risk. They can also encourage a more efficient and straightforward method of executing cross-border payments by reducing the number of intermediaries.

It is likely the evolution towards CBDCs will initially see the financial market supplement rather than replace existing payment instruments with new types of digital currency. CBDCs will coexist with current forms of money in a wholesale context, and their payment rails will also work alongside the existing payment systems. In simple terms, CBDCs will need to be linked to the broader capital markets ecosystem and applications such as securities settlement, funding, and liquidity.

If built with an innovation-first mindset, the future of banking infrastructure should provide full interoperability and convertibility between fiat, CBDCs, and any other type of digital money used in wholesale payments.

The future of CBDCs

To unlock the full potential of CBDCs, a ‘corridor network’ will need to be formed. This involves combining multiple wholesale CDBCs into a single, interoperable network under common governance agreed upon by all central banks involved. The legal framework of this platform would then allow for payment versus payment (PvP) or, where applicable, delivery versus payment settlement.

Practical wholesale CBDCs appear to be on the horizon, either as a supplement to existing financial systems or as part of a transition to a digital, cashless world. Looking ahead, central banks would benefit from collaborating with fintechs that provide innovative cloud native technology to enable seamless wholesale cross-border payments without interfering with the flow of funds. If wholesale CBDCs are to become a reality, fintechs must be prepared to accommodate them.

 

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