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Of all the FinTech and banking trends of the past few years, the story of Buy Now, Pay Later (BNPL) stands out as one of the most prominent and memorable. During a period of tumult and uncertainty, BNPL seemed to go from strength to strength, growing exponentially in scale and popularity and swiftly being incorporated into the offerings of some of the world’s largest and most influential companies.

by Ion Fratiloiu, Head of Commercial, Yobota

Breaking financing down into multiple fixed repayments has allowed consumers to increase their short-term spending power, which can be a tremendous advantage to those with regular income that lack saved capital. The benefits aren’t limited to the user, of course. Retailers are reaping the rewards of this heightened spending power, while BNPL providers have grown in tandem with the product’s popularity.

BNPL is not a license to spend with abandon – it is ultimately a credit product, and its misuse can have adverse effects on the consumer’s credit rating and financial wellbeing if repayments are missed. It is a tool that has the power to help consumers reach their immediate goals, but one that must be treated with care and caution.

With Which? estimating in July 2021 that a third of UK consumers reported having used a BNPL product at least once, this convenient lending system has clearly landed in the business to consumer (B2C) sector with aplomb, changing expectations and best practices for lenders and retailers alike. This sea-change, however, is not limited exclusively to B2C – the next destination of the Buy Now, Pay Later revolution is in fact other businesses.

Back to B2B

The next giant leap for BNPL might stem from its usefulness to startups and small-to-medium enterprises (SMEs). Liquidity and financing are common obstacles for businesses in their early stages, and while specialist services do exist to cater to these issues, BNPL can provide a greater degree of control, flexibility and transparency that could prove invaluable to businesses that are in the process of levelling up.

Support for SMEs and startups comes in many forms, but overreliance on incubators and seed funding can stunt the overall development of the sector. Sometimes, businesses need to be able to manage their own finances at speed, needing short-term injections rather than waiting for their next seed round. Traditional lending options are available, and have existed for years, but can be slow to secure and be laden with complex terms and conditions.

This is what makes BNPL for Business such a tempting proposition. The ability to spread repayment for specific purchases over an agreed period suits businesses with predictable revenues but little capital – like a subscription-based startup or a growing company still awaiting funding. BNPL can make borrowing frictionless and consistent in a way existing options cannot.

This isn’t only good news for small businesses – growth in the BNPL for the Business sector could fuel the same growth that B2C did, with all parties involved able to benefit. We could see SMEs experiencing improved cash flow management and spending power, and specialised B2B BNPL providers expanding with the same speed as their B2C counterparts.

Power to pay your own way

The driving force behind the rate of change within BNPL is the strength of modern core banking. Banking as a Service (BaaS) has simplified the process of setting up seamless and scalable lending and payment solutions to the point that any business can create their own financial products with ease. This means that not only can more businesses offer SMEs lending options, but more SMEs can create their own BNPLs and offer split payments through their own platforms.

In the UK alone, BNPL usage almost quadrupled in 2020, totalling an astounding £2.6b in transactions – this sort of opportunity should not be exclusive to major brands and eCommerce retailers. Whether using the services themselves or offering them to their users, SMEs should consider adopting BNPL as part of their approach if they want to stay ahead of the curve.

The year of BPNL for small business

While the world’s largest companies like Amazon and Apple have already embraced BNPL, enjoying banner years of their own, the success of new businesses is a more encouraging metric of our economy rebuilding. Seeing more SMEs and startups turn to Buy Now, Pay Later could be an indication of better things to come, and of different industries and sectors beginning to get back on their feet.

2022 is a year for optimism, for looking forward and having confidence in better things ahead. BNPL is one area with the potential for success, and the opportunity at hand is there for the taking. All small businesses need to do is embrace it for themselves.

 

From launching his financial career at Deutsche Bank, Ion spent a number of years consulting in the equity capital markets space and leading sales growth for FTSE500 company Fiserv and core banking provider Thought Machine. He joined Yobota in 2021 to launch its commercial operation, leading GTM strategy and building a diverse and multi-faceted team to take the company to the next stage of growth.

Cloud technology for distribution and processing of market and reference data is disrupting financial data management. According to a comprehensive research report by Market Research Future, the financial cloud market size is expected to reach US$ 52 billion by 2028, growing at a compound annual growth rate of 24% between 2018 and 2028.

by Mark Hermeling, CTO, Alveo

The migration of market and reference data to the cloud has been an ongoing process for several years.  Shifting to the cloud has not only reduced infrastructure and maintenance costs by moving off on-premise infrastructure to increase scalability and elasticity, and therefore ensure an element of future-proofing, it has also helped reduce the cost of market data management through appropriate-sized infrastructure, centralised licensing and more easily sharing data sets.

The use of cloud-native technology can make the approach more easily scalable depending on the intensity or volume of the data. Using cloud-based platforms can also give firms a more flexible way of paying for the resources they use, including driving an organisation-wide standardisation of data charging and consumption. In addition to this, an improved data lineage ensures that source data and any transformation in the data’s lifecycle can be clearly captured. This transparency not only helps firms optimise and share their data assets internally where appropriate but reduces the cost of change.

Shifting the ecosystem to the cloud

All the above show the benefits of moving to the cloud. Today, we are witnessing a seismic shift in the market and reference data management process, with the whole data ecosystem now migrating to the cloud, where financial services firms can move away from slow manual processes and fragmented on-premise systems and start reaping the rewards of improved efficiency and lower costs that the cloud can bring.

Data vendors are starting to push their products directly onto cloud platforms like AWS, Microsoft Azure and Google Cloud Platform. Added to that, we are witnessing providers of applications like portfolio management systems, trading solutions and risk and settlement systems, moving there also. Again, they are being attracted by the enhanced security and scalability, increased efficiencies and reduced cost cloud deployment can bring. So, rather than it being a case of companies placing individual applications in the cloud or using specific software as service providers to host their data management platforms, the entire data ecosystem is now moving to the cloud.

The implications are that data management systems need to be both cloud-agnostic and cloud-native to optimally source, integrate, quality-control and distribute market data. In other words, systems used need to be designed and built to run in the cloud and to work effectively in that environment but at the same time, they should not rely on a single cloud provider’s proprietary services or in any way be locked into a single cloud vendor.

With this shift accelerating, firms need to find new ways of provisioning data onto the cloud and into their applications that also reside there – and it is increasingly urgent that they do if they want to keep up with the competition and retain their edge over their rivals.

Every firm will need to consider everything: from building in more robust information security to keep data safe in the cloud right through to enhanced permissions management, usage monitoring, and of course, data quality, which is always a topic. That’s important. After all, if organisations automate more, put more applications in the cloud, or simply more directly connect them, then data quality becomes even more critical because the process of change removes what is typically a manual step in between cloud and on-premise, which could potentially act as a safety net to prevent mistakes escalating quickly into significant issues.

Achieving all this can be made easier through the partial or full utilisation of vendor-managed solutions with a ‘one-stop-shop’ for the end-to-end provision of market data from vendor feeds all the way to distribution to their customers. It is, after all, essential that cloud environments are optimised to achieve maximum efficiency. To be truly effective, these solutions need to be cloud-neutral: part of which involves being capable of interacting with data on any public cloud platform.

Starting the move today

Given all the above, while the ongoing migration of financial services market reference data to the cloud is nothing new, the migration process is now gathering pace. It is now longer just data management solutions and processes that are moving over to the approach. Upstream, data vendors are putting data on public cloud platforms and, downstream, application providers are doing so also.

There is therefore a growing imperative for financial services firms to shift their market and reference data to the cloud. They can’t afford to wait if they want to remain competitive. However, in migrating their approach, they will need to opt for cloud-native solutions that support ease of use and ease of management. These solutions will also need to be cloud-neutral and cloud-agnostic to deliver the scalability that firms will need moving forwards.

Moreover, in rolling out their approach, financial services businesses will also benefit from opting for a managed services approach to data management which allows them to tap into all the benefits of the cloud while eliminating the day-to-day burden of data processing and platform maintenance. With all that in place, they will be well placed to maximise the benefits of having their financial data in the cloud.

With hybrid working seemingly set to stay, can complete discovery of data and devices and ongoing monitoring of asset behaviours across highly dispersed financial service estates mitigate remote security concerns in the new hybrid working world?

by Andrew Gehrlein, Chief Financial Officer, Park Place Technologies

Across the conclusions of a recent McKinsey report on the future of the physical workplace it was clear that the majority of employees (52%) would prefer a continued hybrid model of working. McKinsey expanded the definition of hybrid workplaces to include the usage of flexible workspaces that are physically located outside existing company office locations to include home office workspaces alongside hub working and communal space works. How do banking infrastructure leads accommodate this ongoing transfer of working conditions, especially with the increased security parameters that the world of trading demands?

Since the initial rush to accommodate working from home mandates in March 2020, these IT infrastructure leads have now had the benefit of time and experience to consider, mitigate and control the security impacts that continued hybrid working poses in finance. Today, these leads are proactively focused on developing a clear, structured, and continued strategy for those organisations and employees who elect to work outside of company facilities in an environment where speed, security and increased regulatory pressures are paramount considerations in each financial exchange.

Hybrid staff continually need to access devices and exchange data above and beyond the usual elaborate security firewalls that these organisations typically embrace from within fixed corporate networks. Now, on a permanent basis, these IT leads must identify all possible ingress and egress points in their newly expanded dispersed network before holistically deploying enhanced next generation security and cyber services that give increased protection from hostile activities. This also includes systematic and ongoing understanding of endpoint usage, and endpoints themselves need to be capable of being restricted and isolated quickly, to avoid further contamination should a security breach occur.

Within a hybrid working strategy, organisations also need to develop a clear understanding of usage of cloud accounts, yet the nature of cloud service provision means that much of this is dynamic, and complex to track. Additionally, public network usage provides further challenges in settings such as communal spaces. Data transfer to a wireless printer inside a secure corporate facility poses relatively little risk yet place the same wireless printer within a hub space and the possibilities for hostile activities increase exponentially.

Equally in the home environment additional vulnerabilities exist. Routers can have exposed modem control interfaces; or staff using BYoD that may fall outside of patching windows; or the increase in domestic IoT exposure points, all of which need additional consideration. Faced with the level of challenges, it becomes quickly apparent that finance IT leads essentially need a real-time, always-on, centrally managed discovery and monitoring system of devices and data.

How can this be achieved? Pre-Covid, IT Asset and inventory device management was limited largely to a manual discovery and tracking that assisted with security and audit requirements. Faced with the complexity and threats outlined outside of corporate locations, today this discovery must be conducted as an ongoing service, in real-time, expanded across multiple remote locations for immediate discovery, automating and simplifying asset disclosure without manual IT inventory collection. In short, discovery needs to provide complete visibility into financial services’ data centres and cloud environments, and should include servers (physical, virtual and cloud), desktops, peripherals, edge devices, alongside the infrastructure services.

Discovery is the first step. Monitoring networks this complex is the second. Network monitoring tools have become increasingly specialised and siloed towards departmental usage, neglecting the holistic cross-departmental requirement that hybrid working needs. What’s required today is proactive and predictive generic monitoring across hardware and software that gives leads immediate and actionable insights to gain the greatest level of controls allowing identified new devices to be quickly added to the fold and protection. Only then, when IT leads understand what hybrid workers are using at any given point in time, can appropriate security solutions be confidently layered, safe in the knowledge that there are no gaps within defences.

Policymakers and regulators around the world have pointed to cyber threats from criminal and state actors as an increasing threat to financial stability. Last month, US Treasury Secretary Janet Yellen – along with finance ministers and central bank chiefs from the Group of Seven nations – conducted an exercise covering how G7 members will seek to cooperate in the hypothetical event of a significant, cross-border incident affecting the financial sector.

by Fabien Rech, EMEA Vice President, McAfee

Such concerns are widespread, with 80% of UK IT professionals anticipating a moderate or even substantial impact by increased demand for their services or products this holiday season. The extra demand is compounded by the reduced size of teams and greater online activity. With cyber threats to the financial industry front of mind, and organisations across the sector coming under scrutiny as to whether they are doing enough to protect themselves, this year’s peak season – and subsequent rise in online activity – is cause for concern.

While this paints a bleak picture, organisations can be proactive in defending their networks, data, customers, and employees, against the anticipated increase in holiday cybercrime by implementing certain security measures.

Using technology to bolster teams

Demand for cybersecurity is surging, and today there are a number of technologies that can help to bolster security measures, providing additional support for often stretched security teams. Threat intelligence can offer unique visibility into online dangers such as botnets, worms, DNS attacks, and even advanced persistent threats, protecting FS organisations against cyberthreats across all vectors, including file, web, message, and network.

In addition, taking a Zero Trust approach to security enforces granular, adaptive, and context-aware policies for providing secure and seamless Zero Trust access to private applications hosted across clouds and corporate data centres, from any remote location and device. This will be particularly useful as more employees choose to work remotely.

Prioritising employee awareness

Beyond technologies, the adoption of an awareness-first approach is vital. Proactive cybersecurity awareness training for all employees – not just those in the security team – is essential, especially when encountering holiday phishing emails. As the cyber threat is always evolving, so too must organisations – ensuring that their team’s knowledge and ability to identify, avoid and negate those threats also grow in turn.

This awareness-first strategy requires leaders to move away from a ‘breach of the month’ approach, instead of using proactive training measures to build security into the fabric of their organisation, breaking down siloes of threat and information intelligence across the business, so that all employees are aware of how they can contribute to the battle against cyberthreats during the peak period and beyond.

Some banks are already taking a proactive approach to testing employee understanding when it comes to cybersecurity, for example, resistance to spam or phishing emails, and knowing not to plug unknown USB keys into their laptop. If employees don’t appear to have sufficient knowledge of threats and best practices, they will automatically be required to take part in further training.

Other key steps to take in this proactive approach include increasing the frequency (and testing) of software updates, boosting the number of internal IT-related communications to keep everybody informed, and implementing new software solutions with due diligence.

Implementing a response plan

It’s also important to recognise that protective measures might not work 100% of the time. As hackers become ever more sophisticated, it’s vital for FS organisations to design a holistic, clearly communicable plan for if (and when) things do go wrong.

Developing a robust incident response plan could mean the difference between being able to respond and remedy a security breach in minutes rather than hours, ensuring the least amount of downtime possible. When asked, 43% of businesses reported suffering from downtime due to a cyber concern in the last 18 months – for 80% this happened during peak season and lasted more than 12 hours for almost a quarter (23%)

Again here, training forms a big part – making sure employees know what to do and who to inform when an incident does occur is at the heart of any effective response plan, as is encouraging a culture of honesty and transparency. An organisation in which employees are wary of acknowledging a mistake or informing someone of a possible accidental breach is not a secure one.

The year is full of challenging peak periods, from the public holidays at the end of the year to summer vacations and various religious/spiritual holidays. The need for vigilance has never been greater or more constant, and financial services organisations, in particular, have a need to protect the data and money of their customers, as well as the resilience of their own organisations.

By using technology, training, and incident response awareness, leaders in the sector can help to bolster teams against the increasing sophistication of cyberthreats, staying safe while staying connected. The peak season offers unique challenges, but ultimately the goal is to develop a resilient and adaptable organisation that can ensure security year-round, allowing employees to thrive, wherever they choose to work without having to worry about threats.

Buy Now Pay Later (BNPL) has seen a surge in growth since the start of the pandemic, but in order for the BNPL industry to sustain its development, it must be underpinned by comprehensive technology designed to optimise experience both for the merchant and the customer.

by Tom Myles, Chief Technology Officer, Deko

The most influential technology for business has been the rise of AI, machine learning and big data, having now permeated almost all sectors. Indeed, recent research highlights the key role that AI is expected to play in the future of fintech as a whole, with two-thirds of fintech firms predicting it to have more impact on the sector than any other tech in the next five years. As for BNPL products in particular, a forecast market of £26.4 billion by 2024 would mean it more than doubling in three years, so there is huge growth potential for AI to help unlock.

Payment optimisation

Lenders can use AI and machine learning to extract more value from BNPL platforms. Machine learning models, for instance, are built on data, and payments systems generate large quantities of data from which potential lenders can gain insights into consumer behaviour.

These data-driven decisions can streamline the process of matching the right lender to the right buyer at the right time, which will be all the more useful for unlocking the potential of platforms that operate on a multi-lender, multi-product basis. AI and machine learning models can match consumers to the right member of a multi-lender roster, enabling an increased provision of credit for consumers.

Delivering a rewarding experience for consumers is just as important as the flexibility of the financial technology involved, as increasingly tech-savvy consumers continually elevate the minimum standard of the online experiences in which they are prepared to engage. In particular, consumers are increasingly reticent to engage in elongated sign-up processes and demand a mobile-first approach. Offering a visibly streamlined, omnichannel payments process will therefore prove to be a vital differentiator in an ever more competitive market.

Moreover, empowering consumers and lenders to make more streamlined transactions will also be beneficial for merchants. AI-enabled technology will enhance the flexibility of retail finance products, enabling platforms to process more transactions at a higher pace. This, combined with reduced rates of basket abandonment, will help retailers increase their sales volume.

Fraud prevention

While merchants may relish the prospect of driving more sales, machine learning can also support them in another critical area that may be somewhat sobering to consider. As commerce continues to migrate online, the threat of fraudulent transactions looms larger than ever.

Leveraging AI and machine learning means that payment platforms can learn to recognise patterns in consumer behaviour, based on analysis of the data generated from previous transactions, so even the smallest changes in behaviour can be identified. These data-driven insights will enable automated flagging of potentially risky transactions, which will reliably protect merchants, lenders and consumers from fraud.

Automating this process is vital in a world where online fraud is increasingly sophisticated. An older, rules-based model might be able to test for numerous different types of fraud that have been recorded previously, but the system would remain vulnerable to as yet undetected types of fraud.

Future of FinTech

Using technology both to streamline payments and to prevent fraud will require FinTech platforms to strike a delicate balance. Security is of course vital, but rigorous fraud prevention processes should not come at the expense of a streamlined, speedy checkout from the user’s point of view. Indeed, for fintech platforms as well as for users, improved security and streamlined payment processes will ideally go hand-in-hand.

FinTech firms must therefore invest due consideration as well as resources into AI-enabled functionality for their platforms. And this investment has already proven well worth making. Given the benefits for both merchants and lenders, it is perhaps unsurprising that 83% of financial services professionals agreed that “AI is important to my future company’s success”. Indeed, these forward-thinking technologies and firms are integral to the development of the payments sector.

Instant payment processing is expected by today’s customers and clients, and as the world of business adapts to hybrid work, there is no better way to meet this need than with cryptocurrency. Cryptocurrencies allow businesses to make secure, instantaneous transactions while eliminating the middleman.

by Gabby Baglino, Digital Marketing Specialist, Bryt Software

This keeps everyone’s data safe and reduces transaction fees — and those savings can go toward growing the business rather than paying for unnecessary charges. Let’s take a closer look at why cryptocurrency is key to hybrid and remote work and the powerful new technology that makes it possible.

What is blockchain technology?

A blockchain is a public ledger that contains data from anywhere in the world. This entirely digital database is shared across a network that can include everyone in a company’s workforce, no matter where they’re physically located.

By decentralizing the information, this revolutionary technology ensures the security of financial transactions. When using the blockchain, no third parties are necessary.

Unlike a traditional database, the blockchain collects data and stores it in blocks. When one block is filled with data, it’s closed and linked to the previous block in the chain. Simply put, the blockchain is a chain of digital blocks, and once a block is closed the information it contains cannot be altered or deleted.

In the case of cryptocurrencies like Bitcoin, the blockchain’s decentralized nature allows it to be used as a storehouse of transaction information. All users have collective control over the data, and the changes are irreversible.

Financial transactions can be made securely among an unlimited number of team members located anywhere in the world. And when businesses need to store sensitive transaction information, the data records are protected from any kind of update, deletion, or destruction.

How businesses benefit from using cryptocurrency

Many business owners encourage crypto usage in everyday transactions. Let’s take a look at some ways that this type of transaction benefits small businesses and enterprises alike.

1. It’s more secure

Identity theft can lead to significant personal as well as corporate loss. When you make an online payment, you’ll need to enter credit card information. Your sensitive data is then sent through channels and stored in databases where it may be the target of a cyberattack.

Hackers can gain access to your account details and use them for unauthorized transactions even if your credit card numbers aren’t compromised.

The identification process made possible by the blockchain allows all your personal data to be encrypted in a single place and kept safe by advanced cryptography. With this method, identification is faster and more secure than it would be going through third parties that may be vulnerable to attack.

2. Smarter use of funds

Dependency on third parties can be a challenge for businesses that want to use their finances to expand. Lack of resources and external pressure can get in the way of taking appropriate and timely financial actions.

Though they may have plenty of great ideas, enterprises often cannot expand the way they want due to the lack of funds or the freedom to do what they want with their money. With blockchain technology, businesses have the liberty to use their finances effectively because they have direct access to their money.

3. No dependency on third parties

Cryptocurrency’s ability to allow businesses to avoid the middleman is a primary reason why cryptocurrency is attractive for companies of all sizes.

When a business depends on banks or other payment gateways, each transaction comes with a percentage fee, usually between 1% and 4%. Transaction fees can add up quickly, particularly for larger corporations. This can reduce the efficiency of the business in the long run.

Transaction fees can be crippling for smaller businesses, so it’s natural for small to midsize businesses to turn to cryptocurrency for relief. With blockchain technology, businesses can transact with global markets with little concern about exchange rates and processing fees.

Thanks to the technology, buyers and sellers can now communicate with each other directly without having to go through a bank. As a result, many businesses can afford high discounts to draw customers who can pay using cryptocurrency.

A study conducted in 2020 reports that 40% of customers who pay using digital cryptocurrency are new to the sellers. Clearly, the adoption of cryptocurrency as a mode of payment has increased the client base for many enterprises.

Cryptocurrency and the hybrid work era

As industries find ways to adapt to the explosion of work from home (WFH), the importance of paying employees in cryptocurrency has become central to the conversation. Thanks to remote work, businesses can cultivate hybrid teams, recruiting the best talent from anywhere in the world to work virtually with their in-office team members.

As fiat currencies are subjected to inflation and processing fees, among other things, cryptocurrencies make it easier for companies to pay their employees. When the employees get a combination of digital and fiat currencies as payment, they can later convert the crypto into fiat. 

Workers who are paid in cryptocurrencies have more control over their cash. And since the process uses effective encryption via blockchain technology, hackers have no access to sensitive data.

As hybrid work has become established, digital payment methods are also becoming acceptable in modern society. As an entirely online mode of payment, cryptocurrency offers an advantage over other payment methods with convenience as well as security.

Remote work isn’t going away anytime soon. As hybrid work cements its place in the world of work, digital currencies ensure that businesses run smoothly by offering the best solution to conduct transactions. Hybrid work and cryptocurrency will go hand-in-hand for data security and ease of use in the coming years.

Trade surveillance departments are under intense pressure from regulators to catch trade market abuse and fraudulent activity. But monitoring is becoming increasingly complex.

by Paul Gibson, Business Development Director, KX

Financial institutions must monitor activity relevant to their specific business, this means checking for market abuse, fraud, market disruption and fair practice as well as more malign abuses such as money laundering to support criminal activities like terrorism and people trafficking. This often means analysing vast amounts of both historical and real-time data, in a variety of formats from trade data to electronic communications. Analysts are becoming weighed down by large amounts of alerts and investigations, many of which prove to be unnecessary when other factors are considered.

To deliver a successful trade surveillance programme that satisfies the rigour of the regulators and the efficiencies demanded by the business, a consolidated approach is required. It must be effective across all lines of business for the detection of emergent, systemic and often unknown risk, and take a proactive approach to make sense of all of the interactions, dependencies, changes, patterns and behaviours across the entire trade lifecycle.

Cross-Product Analysis

Organisations need a platform that can process vast amounts of data from multiple streams in real-time, allowing users to make decisions on alerted behaviours much more effectively with significantly greater efficiency. This means using cross-product analysis to identify errors, automated techniques to reduce false positives and machine learning to extract insights from both historical and real-time data.

Traditional instrument-by-instrument trade surveillance techniques do not typically extend their analysis to related products. This means that in certain areas, such as credit and rates, the links between the topics and how they are affecting one another go unseen. This is opposite to risk management techniques across the same technologies where trade dependencies are closely monitored.

As such, it is important to incorporate risk management elements, such as benchmark and sensitivity measures to help identify potential abuse over a range of instruments. This enables products to be broken into their risk fundamentals and effectively ‘look through’ to the underlying securities in an analysis. In looking for evidence of manipulation of a Financial Risk Advisor (FRA), for example, the analysis may extend to monitor both futures and interest rate swaps too.

Reducing False Positives

The more information available to businesses means the more insightful judgements can be made. In regard to false positives, the presence of surrounding data can help contextualise results by automatically classifying high volumes of alerts. Analysis can then determine which are material and which are not. False positives reduction techniques fall into three areas:

• Data Filters – Filtering out specific data or activity that may not be applicable. For example, excluding immediate-or-cancel (IOC) orders from Spoofing profiles.
• Use of Dynamic Thresholds/Benchmarks – Replacing static thresholds with automatically adjusting parameters that reflect evolving market conditions and changing behaviours, not only of individual traders but across the market.
• Alert Feature Overlays – Including surrounding factors for context in assessing alert severity. For example, factoring in change in portfolio concentration when monitoring potential insider trading.

When used together, these factors help avoid unnecessary and time-wasting alerts that distract analysts from the more important and pressing investigations. Thereby, optimising both operational efficiencies and effectiveness for mitigation of true risks.

Future of Trade Surveillance relies on Machine Learning

From calibration to error reduction, machine learning enables a variety of business practices to be improved. Detection rates can be continuously refined using a blend of supervised learning, unsupervised learning and feature extraction techniques from the historical data store.

Supervised learning uses analyst feedback and assessment of historical results to train models and improve their accuracy. Unsupervised learning works on its own to discover the inherent structure of unlabelled data, using techniques like One-Class Support Vector Machines (SMVs) to detect anomalies to help classify results based on distributions and similarities.

SVMs establish normal behaviour by learning a boundary and then adding a score to the results, based on their distance from that boundary. This adjustment can then guide analysts on what investigations to prioritise. Indeed, the benefits of AI and machine learning are well documented, but their application for improving detection rates in trade surveillance is limited.

Regulators are still hesitant to allow machines to determine whether an activity is suspicious or not. This means that the majority of what we are seeing is a supervised learning approach. However, the regulatory landscape continues to evolve and the demand for real-time decision-making is mounting. Therefore, organisations will need to make a shift in mindset and capitalisation of narrow AI with unsupervised machine learning if they are keen to detect fraud effectively and accurately.

As a result of the ever-evolving market abuse tactics being detected, and which need to be prevented, the requirements for strong trade surveillance are more demanding now than ever. For firms, this increased complexity requires them to adopt a consolidated solution that delivers accurate insights when it’s most valuable – at scale both historically and in real time, enabling users to analyse data at a breadth and scale that wasn’t previously possible.

The flexibility of a high-performance streaming analytics platform is a game-changer for real time intervention where necessary and the timely flagging of abnormal behaviour based on large amounts of historical data. By using this technology, firms can take a proactive approach in their response to abnormal behaviour in as quick as microsecond, instead of reacting when it is too late. By doing so, firms can work to improve detection rates and make significant savings through fewer false positive cases and ensure operational efficiency is met.

For several years, the financial sector across the world has been undergoing a digital transformation. In a socially distanced world, the pandemic created more opportunities to innovate new digital financial services, while also uncovering the gaps in the Indian financial system, such as the inaccessibility of credit to Micro, Small, and Medium Enterprises (MSMEs). MSMEs are vital cogs in the growth engines of the Indian economy, contributing to about 30% of the GDP.

by Lalit Mehta, Co-founder & CEO, Decimal Technologies

However, during the pandemic, numerous MSMEs have suffered due to the absence of access to credit. The MSME credit gap approximately amounts to a monumental $240 billion due to traditional institutions’ lack of flexibility and their inability to effectively leverage the available user data and viably reach the semi-urban and rural areas.

This, however, is not just a problem, but also an opportunity. There is immense potential in the MSME segment for banking institutions as they keep adopting digital and tech innovations. As we step into the year 2022, let’s look at how this opportunity might play out within the financial sector.

Open Banking

Open banking is a solution that is emerging as a way to completely transform the way credit is disbursed, making it more suited to the financial situations of MSMEs. Open banking refers to a system where banks and other financial institutions allow third parties, such as fintech companies, to access user data via secure Application Program Interfaces (APIs). Not only can the APIs enable fintech partners to build new services that are more efficient and accessible, but also allow traditional financial institutions to offer experiences fit for the digital age.

Open APIs have the capability to help financial institutions digitise the process of lending and address the growing credit demand. They can also help with some much-needed customisation in the offerings, thereby catering to specific needs that might not be addressed in their entirety by a single legacy product. Artificial Intelligence (AI)-based solutions offer flexibility that suits the borrowers’ needs that might not always be feasible for traditional processes to identify or address.

Risk Assessment

The value of approved and disbursed loans is mainly determined by how an individual or business is likely to pay it back. This is why risk assessment, or determining how likely an individual is to default is critical for the entire sector, and this is where AI and Machine Learning (ML) can change the game. The AI/ ML components employed by FinTech firms can match the customer with the lender without minimal to zero manual intervention, solving one of the key problems of the lending industry- that of risk assessment. This is done with the assistance of detailed, user-friendly credit assessment memos which allow lenders to practice controlled yet faster risk assessment.

With the help of AI and ML, banks can understand how an individual’s or a company’s recent financial behaviour deviates from past behaviour, and therefore get early insights into potential causes of concern. In this scenario, having early insights enables financial providers to take action with a relevant response – i.e., reassessing the approved loan amount or declining a loan.

Maximising Profits

For years, banks and other lenders have been using computer systems to automate more and more of the loan process. With the massive growth witnessed by businesses on the back of new-age technology, many institutions are now trying to fully automate the process. Adoption of AI results in an enhanced borrower experience and assists in making informed decisions with utmost certainty. It eliminates administrative expenses and delays to maximize the amount of profit for every loan created. Removing human bias, decisions will increasingly be based on verified customer data like their monetary status and accuracy, giving little room for error and helping businesses focus on other aspects of the lending process that still require human attention.

The banks will also have the liberty to consider a more proactive approach towards the onboarding of new customers. During the loan application phase, AI and ML are often used to anticipate credit needs by analyzing credit line usage and understanding historical data patterns. For instance, an agricultural business is likely to have seasonal credit needs; these needs can be modelled to understand typical versus atypical patterns.

Better Banking Experience

An increase in the integration of AI and ML will also mean the elimination of human intervention. Decisions made by humans are almost always influenced by biases which may end in either a poor experience for the customers or losses in terms of loan frauds for financial institutions. AI-driven tools run the available data against a group of rules to work out the borrower’s acceptability, thereby speeding up the process, and also ensuring security for the institution.

By understanding how a company’s recent financial behaviour deviates from past behaviour, banks can detect or create opportunities for expanding their business relationship with the customer – or get early insights into potential causes of concern. In both these scenarios, having early insights enables financial providers to take action with a relevant response – i.e., extending credit proactively or declining a loan.

Conclusion

2022 is set to witness a further increase in the adoption of AI and ML. This will lead to a bridging of the credit gap that the MSMEs are suffering from, resulting in further bolstering of the economy. This will also exponentially enhance customer experience while cutting down on the risks. This New Year will be a better year for banking.

While disruption from the pandemic has highlighted many opportunities for development across multiple industries, it has especially emphasised the need for digital transformation within the financial services market.

by Hans Tesselar, Executive Director, BIAN 

At the beginning of the pandemic, financial institutions realised what it meant to be truly digital. Research from EY found that 43% of consumers changed the way they banked due to Covid-19 favouring a more digital approach. Almost overnight, banking organisations were forced to shift their focus towards becoming more agile, resilient and, above all, digital.

Despite the importance of transformational efforts, the financial services industry continued to come up against obstacles, highlighting the need for urgent industry action.

Digital-First Customer 

The financial services sector has realised that without the comprehensive digital infrastructure necessary for today’s environment, they are unable to bring services to market as quickly and efficiently as they would like – and need. The extensive use of legacy technology within banks meant that the speed at which these established institutions could bring new services to life was often too slow and outdated.

This challenge is also complicated by a lack of industry standards, meaning banks continue to be restricted by having to choose partners based on their language and the way they would work alongside their existing ecosystem. This is instead of their functionality and the way they’re able to transform the bank.

To move forward into the ‘digital era’ and continue on the path to true digitisation, banks need to overcome these obstacles surrounding interoperability. Additionally, with today’s digital-first customer in mind, financial institutions need to take advantage of faster and more cost-effective development of services. Failing to provide these services may force customers to take their business elsewhere.

One thing is certain, consumers will continue to prioritise organisations that can offer services aligned to both their lifestyle and needs.

Coreless Banking 

The concept of a ‘Coreless Banking’ platform is one that supports banks in modernising the core banking infrastructure.

This empowers banks to select the software vendors needed to obtain the best-of-breed for each application area without worrying about interoperability and being constrained to those service providers that operate within their language. By translating each proprietary message into one standard message model, communication between financial services is, therefore, significantly enhanced, ensuring that each solution can seamlessly connect and exchange data.

With the capacity to be reused and utilised from day one, and the ability to be used by other institutions, Coreless Banking provides these endless opportunities for financial services industries to connect, collaborate and upgrade.

The Future is Bright

It’s clear that the world is facing a digital awakening, and banks are eager to jump on board. Ensuring that the rapidly evolving consumer has everything they need in one place has never been more essential, and the time to enhance the digital experience is now.