Kris Sharma, Finance Sector Lead at Canonical - the publisher of Ubuntu - offers Finance Monthly his thoughts on APIs and how firms are already using them to enhance their services.
Cloud computing, big data analytics, artificial intelligence (AI), machine learning (ML), distributed ledger technology and process robotics are all playing a key role in reimagining financial services for a digital world. A growing number of financial institutions are drawing plans to adopt these technologies at scale as part of their digital transformation initiatives to accelerate financial data processing, deliver mass personalisation and increase operational efficiencies.
Most organisations currently deploy a complicated mix of technologies, legacy software platforms, applications, and processes to serve customers and business partners. On their digital journey, financial firms will have to integrate data, processes and business functionality from legacy systems of record to this set of new technologies. Many businesses have tried to adopt various transformation approaches such as re-platforming and re-hosting, direct integration between applications, rip and replace, and deploying middleware technology to deal with legacy systems and their integration with new technologies. But each of these approaches have their own drawbacks and can limit the adoption of new solutions within the constraints of legacy technology debt.
An evolutionary approach to digital finance, however, will unify information and data without the need to merge operational systems. Application programming interfaces, or APIs, can overcome the challenges involved with adopting new technologies and more innovative solutions while integrating with legacy run-the-business applications.
Where APIs become a core piece of the puzzle
APIs are increasingly playing a central role in digital finance. They essentially bind different parts of the financial value chain together, even though the underlying components may be based on different systems, technology, or supplied by different vendors. Using APIs, financial firms can securely share digital assets while masking backend complexity, integrating software applications and focusing on maximising their proprietary strengths by sharing data, systems, and functionality with customers, partners and developers. This in turn drives digital transformation without a complete overhaul of existing infrastructure.
Application programming interfaces, or APIs, can overcome the challenges involved with adopting new technologies and more innovative solutions while integrating with legacy run-the-business applications.
Since APIs are self-contained, they can be readily deployed and leveraged for innovation at speed, enabling financial institutions to introduce and integrate new features. When powered by the cloud, firms can develop, test and launch new services to customers quickly and cost-effectively, fuelling business growth. For example, insurance firms can make more timely offers by cross-selling home, auto and life policies. Financial institutions can leverage APIs to connect sources and use cloud computing to handle massive amounts of data, as well as AI and ML services live in the cloud, thereby analysing all this data faster and cheaper than they can on-premises.
Who is successfully using APIs?
Challenger bank Starling was designed and built completely on AWS cloud to deliver and scale infrastructure on demand. Additionally, by building a bank with open APIs from day one, Starling is natively compliant with the European Union’s Payment Services Directive (PSD2) directive.
According to ProgrammableWeb research, financial services is ranked highly in the fastest growing API categories, given the rise in digital forms of payment, an ever-increasing customer demand for connected solutions, and open banking initiatives. APIs are at the heart of the PSD2, the UK’s open banking mandate, as well as the Bank of Japan and the Monetary Authority of Singapore’s open banking initiatives.
Finastra’s Open Banking and collaboration: State of the nation survey 2020 finds that “86% of global banks surveyed are looking to use open APIs to enable Open Banking capabilities in the next 12 months”.
As APIs attract an ecosystem of developers, a financial API provider can encourage participation to fill go-to-market gaps and extend its services and data to new markets and use cases. Barclays is fostering collaboration and generation of new ideas through secure, innovative APIs. The Barclays API exchange has built an API library that is available for use by third parties to develop and test new products. Barclays and third-party developers work together to create, develop and test new product ideas before releasing them to the regular API catalogue. Similarly, Starling Bank provides a marketplace that enables developers to build their own products and integrations using its API.
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Unleashing the potential
There is an opportunity for financial firms to leverage the power of APIs by bringing them together with digital technologies to broaden the possibilities for innovation and expand customer experiences. Financial institutions need to reimagine APIs as product offerings that will drive business expansion and increase revenues.
The future of digital finance will be driven by organisations building digital business models, redefining their API strategies and bringing new customer propositions to life using modern web architectures, best-in-class technologies and new ecosystems.
The world’s biggest work-at-home experiment has now shifted into a more permanent structural change, leaving companies grappling with the next operational challenge – intensifying cybercrime. Prior to the pandemic, businesses typically over-relied on in-office cybersecurity systems to protect data, because they rarely had to worry about threats to data outside of the workplace. Fast forward to March 2020, and companies had to quickly recalibrate their entire operations or face their business model being rendered redundant. Since the crisis took hold, approximately 90% of banking and insurance workers worldwide transitioned to a work-at-home set-up[1], the majority of whom are accessing corporate and customer data online on insecure devices.
The scope for cybercriminals to exploit the vulnerabilities of remote technologies to commit financial crimes has increased exponentially for customers being onboarded, and having their financial matters dealt with online. While safeguarding customers remains at the top of the corporate agenda, providing a seamless, omnichannel digital experience cannot be compromised. In this fast-evolving FinTech landscape, financial services must seek to leverage technology that can meet both increasing expectations for an elevated customer experience, whilst fighting internal and external cybercrime. The industry has an important opportunity to leverage Artificial Intelligence (AI) solutions, used in the front-office, to prevent and react to threats, potentially saving billions in lost funds – not to mention protecting brand reputation.
Fast-evolving threat landscape
According to a recent report, the financial services sector fell victim to over half (51%) of all opportunistic cyber-attacks during the crisis[2]. Fraudsters have been launching sophisticated attacks to impersonate financial organisations, by luring in customers with fake emails or phone calls offering financial assistance, only to extract customer data. In fact, impersonation scam cases in the UK were up a staggering 84% in the first half of the year compared to the same period last year[3].
As financial services companies expand their omnichannel offerings, to meet the demand for real-time access to services, so too does the opportunity for potential vulnerabilities. Interacting with customers requires access to their personal information on a granular level, with each interaction involving a traditional phone call, but likely to also include a communication via chat, email, SMS, social media, or all channels combined. Out of 5.2bn financial transactions in the first half of the year in the UK, 84% of these are through mobile devices, broadening the number of access points and the opportunity for exploitation.
Safeguarding data with AI
Customer-facing AI chatbots present an affordable solution in fraud detection and payment protection –capable of identifying anomalous activity that could be easily missed by human agents. This helps to rectify a staggering 90% of data breaches in the UK that were down to human error last year[4]. Used to assist customers in a number of financial transactions, such as reviewing accounts and making payments, chatbots allow users to handle simple tasks on their own, but in a highly secure manner.
Leveraging deep Machine Learning (ML) capabilities, AI-powered chatbots are programmed to learn patterns of work across multiple banking channels. By monitoring vast datasets that have been collected from past incidents, companies can recognise inaccuracies in payment information or unusual behaviours of users to continuously improve detection capabilities. Alleviating pressure from IT teams in the process, security analysts can refocus their time and resources toward actual cases of fraud and strengthen trust with affected customers. Lessons learned can then be quickly communicated and translated into targeted training for affected work groups and used to tailor customer experiences accordingly.
By prioritising AI for risk reduction systems, financial services can avoid hefty fines for failing to detect fraud and improve acquisition and retention. Customers are more likely to choose or stick with trustworthy banks that have a good track record of preventing cyber-attacks.
Banking on an AI-enabled future
It has fast become table stakes for financial institutions to build and implement robust security software and include fraud prevention and detection tools at a keystroke level. Leveraging technologies that are already used on consumers’ digital channels, and using these to secure each point of interaction, can help build an ecosystem of trusted devices while maintaining a consistent user experience. As a self-learning solution, AI-powered chatbots can assume future attack scenarios in the uncertain post-pandemic world – keeping the internal infrastructure running smoothly for employees, whilst maintaining consistent and safe online transactions for customers.
[1] https://www.bis.org/fsi/fsibriefs7.pdf
[2] https://uk.finance.yahoo.com/news/covid-19-leads-to-surge-in-cyberattacks-144142232.html
[3] https://www.ukfinance.org.uk/covid-19-press-releases/impersonation-scams-almost-double-in-first-half-of-2020
[4] https://www.infosecurity-magazine.com/news/90-data-breaches-human-error/
Ammar Akhtar, co-founder and CEO at Yobota, explores the steps necessary to the creation of successful fintech.
The first national lockdown in March highlighted the importance of the quality and functionality of digital banking solutions. Indeed, most of us quickly became accustomed to conducting our financial affairs entirely online.
Financial services providers have needed to adapt to this shift, if they were not already prepared, and consumers will continue to demand more. For instance, Yobota recently surveyed over 2,000 UK adults to explore how satisfied customers are with their recent banking experiences. The majority (58%) of banking customers said they want more power to renegotiate or change their accounts or products, with a third (33%) expressing frustrations at having to choose from generic, off-the-shelf financial products.
Consumers are increasingly demanding more responsive and personalised banking services, with the research highlighting that people are increasingly unlikely to tolerate being locked into unsuitable financial products. This is true across all sectors of the financial services landscape; from payment technologies (where cashless options have become a necessity as opposed to a trendy luxury) to insurance, the shift to “quality digital” poses challenges throughout the industry.
Providers and technology vendors must therefore respond accordingly and develop solutions that can meet such demands. Many financial institutions will be enlisting the help of a fintech partner that can help them build and deploy new technologies. Others may try to recruit the talent required to do so in-house.
The question, then, is this: how is financial technology actually created, and how complicated is the task of building a solution that is fit for purpose in today’s market?
Compliance and regulation
The finance sector is heavily regulated. As such, compliance and regulatory demands pose a central challenge to fintech development in any region. It is at the heart of winning public trust and the confidence of clients and partners.
Controls required to demonstrate compliance can amount to a significant volume of work, not just because the rules can change (even temporarily, as we have seen in some cases this year), but because often there is room for interpretation in principle-based regulatory approaches. It is therefore important for fintech creators to have compliance experts that can handle the regulatory demands. This is especially important as the business (or fintech product) scales, crosses borders, and onboards more users.
The finance sector is heavily regulated. As such, compliance and regulatory demands pose a central challenge to fintech development in any region.
Businesses must also be forthcoming and transparent about their approach towards protecting the customer, and by extension the reputation of their business partner. Europe’s fintech industry cannot afford another Wirecard scandal.
Compliance features do not have to impede innovation, though. Indeed, they may actually foster it. To ensure fintech businesses have the right processes in place to comply with legislation, there is huge scope to create and extend partnerships with the likes of cybersecurity experts and eCommerce businesses.
The size and growth of the regulation technology (regtech) sector is evidence of the opportunities for innovations that are actually born out of this challenge. The global regtech market is expected to grow from $6.3 billion in 2020 to $16.0 billion by 2025. Another great example would be the more supportive stance regulators have taken to cloud infrastructure, which has opened up a range of new options across the sector.
Addressing technical challenges
It is the technical aspect of developing fintech products where most attention will be focused, however. There are a number of considerations businesses ought to keep in mind as they seek to utilise technology in the most effective way possible.
Understanding the breadth of the problem
The fintech sector is incredibly broad. Payment infrastructure, insurance, and investment management are among the many categories of financial services that fall under the umbrella.
A fintech company must be able to differentiate its product or services in order to create a valuable and defensible competitive advantage. So, businesses must pinpoint exactly which challenges they are going to solve first. Do they need to improve or replace something that already exists? Or do they want to bring something entirely new to the market?
The end product must solve a very specific problem; and do it well. A sharp assessment of the target market also includes considering the functionality that the technology must have; the level of customisation that will be required from a branding and business perspective; and what the acceptable price bracket is for the end product.
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Knowing your client
In the same vein, as a vendor it is important to be specific and strategic when it comes to pursuing the right clients. A fintech might consider itself to be well-positioned to cater to a vast selection of different businesses; however, it’s important to have a very clear target client in mind. This will ensure product and engineering teams have a clear focus for any end goal.
The value of a good cultural fit should also not be underestimated. The business-to-business relationship between a fintech and its client (a bank, for example), particularly at senior levels, is just as important as finding the right niche. There must be a mutual understanding of what the overall vision is and how it will be achieved, including the practical implementation, timeline and costs.
Balancing “best tech” with (perceived) “best practice”
Leveraging the newest technology is not always the best approach to developing a future-proof proposition. This has been learned the hard way by many businesses keen to jump on the latest trends.
Shiny new technology like particular architectures or programming languages can have an obvious appeal to businesses looking to create the “next big thing”. But in reality, the element of risk involved in jumping on relatively nascent innovations could set back progress significantly.
The best technology systems are those that have been created with longevity in mind, and which can grow sustainably to adapt to new circumstances. These systems need to run for many years to come, and eventually without their original engineers to support them, so they need to be created in modern ways, but using proven foundational principles that can stand the test of time.
Curating a positive user experience
To revert back to my original point, fintech businesses cannot forget about the needs of the end customer. There is no better proof point for a product than a happy user base, and ultimately the “voice of the customer” should drive development roadmaps.
The best technology systems are those that have been created with longevity in mind, and which can grow sustainably to adapt to new circumstances.
Customer experience is one of the most important success factors to any technology business. Fintechs must consider how they can deftly leverage new and advancing technology to make the customer experience even better, while also improving their underlying product, which users may not necessarily see, but will almost certainly feel.
Another important consideration is ease of integration with other providers. For example, identity verification, alternative credit scoring, AI assisted chatbots and recommendation algorithms, next generation core banking, transaction classification, and simplification of mortgage chains – these are all services which could be brought together in some product to improve the experience of buying a mortgage, or moving home.
Progressive fintech promotes partnerships and interoperability to reduce the roadblocks that customers encounter.
The human side of fintech
Powerful digital solutions cannot be created without the right people in place. There is fierce competition for talent in the fintech space, especially in key European centres like London and Berlin. Those who can build and nurture the right team will be in a strong position to solve today’s biggest challenges.
In all of these considerations, patience is key. It takes time to identify new growth opportunities; to build the right team that can see the vision through; and to adapt to the ever-changing financial landscape. Creating fintech is not easy, but it is certainly rewarding to see the immense progress being made and the inefficiencies that are being tackled.
Karoline Gore gives Finance Monthly an overview of promising Candian fintechs to look out for.
With the rest of the world sprinting toward the inclusivity and diversity of fintech, Canada is catching up swiftly. It is the inclusivity of cashless transactions and peer-to-peer lending, in particular, that are catching the attention of the Canadian market. So it isn’t surprising that Canadian fintech is now attracting a rather diverse age demographic with 46% of them being over the age of 40, according to TransUnion Canada.
In response to this growing demographic, Canadian fintech companies are rolling out some very exciting developments. So which companies are making a splash, and how?
Talem Health Analytics and Ownest Financial
Two Canadian fintech companies are front and center in Holt FinTech Accelerator’s 2020 Cohort list. Talem Health Analytics, based in Nova Scotia, has helped insurers streamline data and empowered them to detect and avoid fraudulent attempts through their AI injury causation tool. They also help insurance firms map out rather accurate recovery trajectories so they can better develop plans to suit their clients. The Calgary-based Ownest Financial that cut down the internal processing time of their partner lenders by 90%. They partnered up with 125 Canadian lender companies to give consumers an easier time to shop around for mortgages, personal loans, and even car financing, to mention a few. They also boast that their clients need about 70% less paperwork, making the whole lending experience swifter and less complicated.
MindBridge’s AI Reducing Financial Risk
Surprisingly, only 45% of consumers feel confident that they can spot and identify errors in financial statements before turning them into reports, according to the Association of Certified Fraud Examiners. The Canadian fintech MindBridge has developed an AI that rapidly scans and identifies anomalies in financial statements and reports. This helps organizations and consumers reduce their financial risk and avoid damaging credit scores. MindBridge’s AI is effectively transforming how accounting can be done, streamlining the auditing process, and improving financial management for businesses and their owners, and private consumers.
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AptPay’s Faster Cash Disbursement
The Canadian fintech AptPay is making a splash in the UK. They’ve partnered up with Mastercard to facilitate an accelerated cash disbursement processing for businesses in various industries and sectors. It is through AptPay’s Application Programming Interface (API), that companies and businesses can integrate Mastercard Send to start payouts. Through AptPay’s compliance services, businesses and their employees can be assured that their transactions are secure and are compliant with the rules set for their particular industries. The API will also enable real-time digital payments that can be linked to banks. The best feature is that payments can be rejected, approved, and reversed by recipients—so they are not simply inert in the whole process.
As consumers and businesses are fully realizing the convenience, inclusivity, and safety of cashless transactions, it is the job of fintech companies to provide better services and processes. Thankfully, Canadian fintech is paying attention and is setting its own trends through its developments and initiatives. The coming months will be a truly exciting time for Canadian fintech and consumers should pay attention.
Charlie Roberts, Head of Business Development for the UK, Ireland & EU at IDnow, outlines the need for more effective identity verification in the financial services sector and how it can be achieved.
In 2019, even before COVID-19 struck, the UK fraud prevention service – Cifas - recorded in excess of 223,000 cases on its National Fraud Database, an increase of 18% on the previous year and a 32% rise over the previous five years. And looking ahead, experts predict that by 2021, the damage caused by internet fraud will reach $6 trillion, making cyber fraud one of the world’s fastest growing and most dangerous economic crimes.
Worryingly for the financial services sector, IBM recently revealed that in 2019, it was the most targeted industry for cyber criminals.
It should come as no surprise then, that financial institutions are increasingly being thrust into the spotlight when it comes to digital security and protecting the identities of their customers.
These worrying figures are certainly one driving factor in the UK government’s new Digital Identity Strategy Board, which has developed six principles to strengthen digital identity delivery and policy in the country.
A hybrid approach
We already know the important role technology is playing in the fight against cyber criminality – from biometrics and machine learning to artificial intelligence (AI) – and we recently discussed the significance of supplementing this verification technology with human identification experts. These professionals are able to use their intuition and understanding of human interactions and behaviours to identify when a person is being coerced or dishonest.
Worryingly for the financial services sector, IBM recently revealed that in 2019, it was the most targeted industry for cyber criminals.
However, while these highly skilled and trained identification specialists are playing a vital role in the fight against cyber and identity crime, for some financial institutions, particularly larger banks, they present a barrier.
Bringing the entire verification process inhouse
Working on a SaaS basis, typically, identity software vendors provide financial institutions with the software and technology required for identity verification. However, the final decision on verification rests with the vendor’s algorithms or ident specialists.
However, many banks want to own the entire verification process, from utilising the technology and software to making the ultimate decision on the identity of a person. By handing this level of control over to the bank, institutions can integrate the verification systems within their own infrastructure, enabling the people that know their brand the best to set their own levels of security and determine what is authenticated and what is declined.
Upskilling inhouse teams is critical
While working with a third-party verification specialist is the preferred option for some, for others, the idea of upskilling and training existing compliance teams in identity verification is the priority, empowering the bank to own the process and the risk. In the long term, it will also provide significant cost savings while showcasing a major investment in talent and people, which will undoubtedly help attract and retain customers too.
With the UK seeking to develop a legal framework for digital identity, it is clearly becoming an increasingly important feature on the governmental agenda, not least to ensure that not only can people feel safe online, but also to deliver faster transactions and ultimately add billions to the economy. As such, all eyes will soon be turning to the safeguards the financial sector is putting in place to help protect the online identities of customers.
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Arguably, then, now is the time to invest in a robust identity verification system that will not only provide the advanced technology needed to automate the process, but that can help train and upskill inhouse teams to truly deliver an embedded and hybrid approach to identity verification at a time when it is of paramount importance.
A study has made a link between powerful bank CEOs and the risk of money laundering. Syed Rahman of business crime specialists Rahman Ravelli considers the research and argues that prevention is everyone’s responsibility.
It may not please certain figures at the top of a number of financial institutions, but research has linked powerful bank CEOs with money laundering dangers.
According to researchers at the University of East Anglia, banks that have such CEOs and smaller, less independent boards will probably take more risks and, as a result, be more prone to money laundering than those with a different concentration of power at the top.
The researchers’ study examined a sample of 960 publicly-listed US banks for the period from 2004 to 2015. The study’s results showed that money laundering enforcement was associated with an increase in bank risk. From its findings, researchers stated that the impact of money laundering is more pronounced where a powerful CEO is present – and is only partly reduced by the presence of a large, independent executive board. They concluded that banks that have powerful CEOs attract the attention of regulators engaged in anti-money laundering efforts, and that this is especially the case if the bank’s board of directors is small and lacks independence.
The study has been viewed by some as the first to demonstrate that money laundering is a significant driver of bank risk. This effectively means that it can take its place alongside business models, ownership structures, competition in the marketplace and regulation as having an impact on risk.
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It is perhaps surprising that previous research on banks’ risk-taking has not explicitly homed in on the possible effect of money laundering, especially as regulators have made no secret of the importance they attach to tackling it. But now, it could be argued, is an appropriate time to make that link. The increased numbers of cross-border transactions – and the sheer scale of many of them – have made banks more vulnerable to money laundering. Regulators are carrying out ongoing assessment of money laundering risks posed by organised crime and those with terrorist links while states – many of which have had obligations placed on them in recent years – are increasing their use of sanctions against countries, organisations and individuals.
The banks that do not recognise and respond appropriately to this state of affairs could well find themselves suffering fines, claims against them and significant reputational damage. Such outcomes are the logical consequences for any bank that can be shown not to have done all it could or should to minimise the dangers of money laundering.
It is worth noting, at this point, the researchers’ argument that the size and independence of a bank’s board can mitigate the impact of money laundering on bank risk but cannot fully compensate for the possible adverse effects. Aside from the study’s conclusions, what also needs to be emphasised is that the shape of fraud and money laundering is constantly changing and developing. As the risks posed by money laundering grow, the regulators adapt to rise to the challenges and the banks themselves have to meet their obligation to identify and assess the risks to which they are exposed. Just as importantly, the banks need to ensure that those risk assessments are kept up to date.
Such procedures can and will, of course, be instigated by those at the top. But regardless of the concentration of power in the upper echelons, once those procedures are in place the bank needs to make sure that its employees understand and comply with them. Those procedures need to be subject to regular monitoring, review and, when necessary, revision to ensure they are effective in countering the threat posed by money laundering. Banks have many methods available to them to ensure this is achieved. It almost goes without saying that banks will have a money laundering officer to supervise all anti-money laundering activities. Investing in anti-money laundering controls involving artificial intelligence (AI) technology is another approach, as it can support enhanced due diligence, transaction monitoring and automated audit trails. But what cannot happen is that the CEO or the board simply issues an edict about the wish to prevent money laundering: genuine prevention will only succeed if it is adopted and carried out by all levels of personnel.
Investing in anti-money laundering controls involving artificial intelligence (AI) technology is another approach, as it can support enhanced due diligence, transaction monitoring and automated audit trails.
The standing of a CEO in a bank and the relative power of its board may well have an impact on the risk posed by money laundering. But a bank will always be vulnerable if its approach to tackling that risk is not embraced by all levels of its workforce.
Karoline Gore shares her thoughts on the evolution of fintech in insurance with Finance Monthly.
The lockdown restrictions imposed in the UK this year have seen the adoption of fintech increase exponentially, according to a survey commissioned by AltFi. The insurance sector has been faced with strong competition in recent times as a number of other industries have started to offer financial solutions that can rival traditional insurance. Not only is the healthcare industry offering ‘medical memberships’ that eliminate the need for insurance, but banks are also quicker at providing loans to help remedy financial damages. It is for these reasons, among others, that operators within the insurance sector have to ensure that they have an advantage over their competition. With the aid of fintech, this goal becomes significantly easier to achieve.
Apps and digital platforms appeal to a younger clientele
As of 2018, Millennials enjoyed a greater spending power than Baby Boomers. Tapping into this segment of the market can be very fruitful as Millennials can provide business for a significantly longer period of time than older generations. Fintech can make insurance offerings increasingly appealing to a younger, more tech-focused client base. Smartphone applications can be designed with businesses, their clients, or both in mind and can streamline traditional insurance processes considerably. Popular features of mobile applications include a policy overview section, premium calculator, and payment processing area. Many apps as well as dedicated websites also provide clients with a range of relevant reviews. If you are looking at taking out car or home appliance insurance, for instance, reviews can cover aspects such as premiums, service fees, and even cancellation policies.
Machine learning improves data utilisation
Machine learning, which is classified as a type of AI, is another form of fintech which is greatly transforming the insurance industry as we know it. In essence, it is a technology that makes it possible for a machine to ‘learn and adapt’ over a period of time. Typically, insurance operators collect substantial amounts of data on an ongoing basis. Unfortunately, only approximately 10% of the data collected is adequately utilised, rendering it almost useless to the business. Thanks to machine learning, insurance companies can put the collected data to better use. It can be used in a number of ways including fraud detection, risk modelling, underwriting, and demand modelling.
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Niche products become more prevalent
Apart from smartphone applications and machine learning, there is a range of other emerging fintech solutions such as telematics, big data, and comparators that are influencing insurance in numerous ways. Thanks to these technologies, insurance companies are becoming more adept at offering niche products (that more traditional insurers won’t touch) to their clients. A good example of this is London-based Bought by Mary, who made it possible for clients with underlying medical conditions such as cancer to obtain travel insurance. Similarly, a partnership between a leading worship centre insurer in the USA and another entity resulted in the creation of an insurance product that made provision for the protection against frozen pipe leaks in low-tenure buildings.
Fintech has had a great impact on the insurance industry. Apart from improving customer service, fintech can also aid in new customer acquisition while saving the company a significant amount of money.
Kris Sharma, Finance Sector Lead at Canonical, explores the value of open source technologies in steering financial services through times of disruption.
In a post-Brexit world, the industry is facing regulatory uncertainty at a whole different scale, with banking executives having to understand the implications of different scenarios, including no-deal. To reduce the risk of significant disruption, financial services firms require the right technology infrastructure to be agile and responsive to potential changes.
The role of open source
Historically, banks have been hesitant to adopt open source software. But over the course of the last few years, that thinking has begun to change. Organisations like the Open Bank Project and Fintech Open Source Foundation (FINOS) have come about with the aim of pioneering open source adoption by highlighting the benefits of collaboration within the sector. Recent acquisitions of open source companies by large and established corporate technology vendors signal that the technology is maturing into mainstream enterprise play. Banking leaders are adopting open innovation strategies to lower costs and reduce time-to-market for products and services.
Banks must prepare to rapidly implement changes to IT systems in order to comply with new regulations, which may be a costly task if firms are solely relying on traditional commercial applications. Changes to proprietary software and application platforms at short notice often have hidden costs for existing contractual arrangements due to complex licensing. Open source technology and platforms could play a crucial role in helping financial institutions manage the consequences of Brexit and the COVID-19 crisis for their IT and digital functions.
Open source software gives customers the ability to spin up instances far more quickly and respond to rapidly changing scenarios effectively. Container technology has brought about a step-change in virtualisation technology, providing almost equivalent levels of resource isolation as a traditional hypervisor. This in turn offers considerable opportunities to improve agility, efficiency, speed, and manageability within IT environments. In a survey conducted by 451 Research, almost a third of financial services firms see containers and container management as a priority they plan to begin using within the next year.
Open source software gives customers the ability to spin up instances far more quickly and respond to rapidly changing scenarios effectively.
Containerisation also enables rapid deployment and updating of applications. Kubernetes, or K8s for short, is an open-source container-orchestration system for deploying, monitoring and managing apps and services across clouds. It was originally designed by Google and is now maintained by the Cloud Native Computing Foundation (CNCF). Kubernetes is a shining example of open source, developed by a major tech company, but now maintained by the community for all, including financial institutions, to adopt.
The data dilemma
The use cases for data and analytics in financial services are endless and offer tangible solutions to the consequences of uncertainty. Massive data assets mean that financial institutions can more accurately gauge the risk of offering a loan to a customer. Banks are already using data analytics to improve efficiency and increase productivity, and going forward, will be able to use their data to train machine learning algorithms that can automate many of their processes.
For data analytics initiatives, banks now have the option of leveraging the best of open source technologies. Databases today can deliver insights and handle any new sources of data. With models flexible enough for rich modern data, a distributed architecture built for cloud scale, and a robust ecosystem of tools, open source platforms can help banks break free from data silos and enable them to scale their innovation.
Open source databases can be deployed and integrated in the environment of choice, whether public or private cloud, on-premise or containers, based on business requirements. These database platforms can be cost-effective; projects can begin as prototypes and develop quickly into production deployments. As a result of political uncertainty, financial firms will need to be much more agile. And with no vendor lock-in, they will be able to choose the provider that is best for them at any point in time, enabling this agility while avoiding expensive licensing.
As with any application running at scale, production databases and analytics applications require constant monitoring and maintenance. Engaging enterprise support for open source production databases minimises risk for business and can optimise internal efficiency.
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Additionally, AI solutions have the potential to transform how banks deal with regulatory compliance issues, financial fraud and cybercrime. However, banks need to get better at using customer data for greater personalisation, enabling them to offer products and services tailored to individual consumers in real time. As yet, most financial institutions are unsure whether a post-Brexit world will focus on gaining more overseas or UK-based customers. With a data-driven approach, banks can see where the opportunities lie and how best to harness them. The opportunities are vast and, on the journey to deliver cognitive banking, financial institutions have only just scratched the surface of data analytics. But as the consequences of COVID-19 continue and Brexit uncertainty once again moves up the agenda, moving to data-first will become less of a choice and more of a necessity.
The number of data sets and the diversity of data is increasing across financial services, making data integration tasks ever more complex. The cloud offers a huge opportunity to synchronise the enterprise, breaking down operational and data silos across risk, finance, regulatory, customer support and more. Once massive data sets are combined in one place, the organisation can apply advanced analytics for integrated insights.
Uncertainty on the road ahead
Open source technology today is an agile and responsive alternative to traditional technology systems that provides financial institutions with the ability to deal with uncertainty and adapt to a range of potential outcomes.
In these unpredictable times, banking executives need to achieve agility and responsiveness while at the same time ensuring that IT systems are robust, reliable and managed effectively. And with the option to leverage the best of open source technologies, financial institutions can face whatever challenges lie ahead.
The unsteady nature of this sector pushes banking institutions to stay on top of their game to ensure business continuity and their most important asset – the customer – remains satisfied. In particular, in the last few months the ongoing pandemic has placed unprecedented strain on customers and the companies that seek to support them. As brick-and-mortar locations and offices closed down, or vastly curtailed their face-to-face operations, nearly everyone was doing business from home.
As a result, like many industries, banks had to completely restructure the way they do business, with scores of bank branches either closing or restricting opening hours due to the virus. Therefore, new methods had to be adopted to serve customers and to ensure that the experience they have doesn’t suffer. This is where digital collaboration comes into play. Ryan Lester, Senior Director of Customer Experience Technologies at LogMeIn, examines how digital collaboration can help banks rise to the challenge of meeting customer demands in unprecedented times.
24/7 expectation and frictionless service
At the height of the pandemic, people were encouraged to use online banking, as telephone contact was under increasing strain with long waiting times becoming the norm. According to Fidelity National Information Services (FIS), which works with 50 of the world’s largest banks, there was a 200% jump in new mobile banking registrations in early April, while mobile banking traffic rose 85%.
With branches remaining closed, customers were continuously being urged to limit the amount of calls they made to the most urgent cases and consider whether they could solve their answers through mobile online banking or checking the company website. Although already being adopted in pockets of the industry, this was a real catalyst that spurred banks to up their game on digital channels and with self-service tools.
According to Fidelity National Information Services (FIS), which works with 50 of the world’s largest banks, there was a 200% jump in new mobile banking registrations in early April, while mobile banking traffic rose 85%.
Banks are challenged with precariously balancing customer needs with the cost of personalised support. With the demographic of customers changing over the last few years, customers are becoming increasingly younger and more comfortable with technology. Influenced by the “Amazon Effect”, their expectations have risen to an all-time high, placing record strain on the sector.
Customer experience isn’t just about support anymore, it’s about serving your customer at every point in the journey. Companies have an opportunity to elevate the experience they provide by moving beyond one-and-done interactions to create continuous engagements with their customers. It is starting to become a primary competitive differentiator in the market and one that doesn’t have a lot of variation. Deploying AI chatbot technology will be able to strategically help banks improve customer experience and raise the level of support that agents provide.
Digital collaboration: The best way forward
By emphasising the importance of adopting digital channels and self-service tools like chatbots, fuelled by conversational AI, banks will be able to help serve a wide range of customer queries and ensure they are protected from fraud and scams.
Conversational AI is exactly what it sounds like: a computer programme that engages in a conversation with a human. When it comes to service delivery, conversational AI can be deployed across multiple channels to engage with customers in ways that effectively address evolving customer needs. At a time defined by COVID-19, self-service tools such a conversational chatbots can work around the clock to solve customer queries in a concise and timely way. Of course, self-service tools won’t completely replace human agents in the banking industry, but they will help companies redistribute customer traffic and workflows in ways that enhance customer experience. Self-service tools fuelled by conversational AI can also improve employee experience because service employees can handle fewer, but higher-level service tasks that chatbots might escalate to them.
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Adopting new tools to help facilitate consistent and concise answers and help maintain customer experience is on the forefront of many industry minds. Banks such as the Natwest Group have seen this first-hand and are testament to the benefits that a good digital experience can provide. Simon Johnson, Capability Consultant, Digital at NatWest Group highlights NatWest’s use of digital tools during lockdown, “Over the last few months, we’ve learnt how to use digital tools to help our employees remotely. From a banking perspective, there have been a lot of changes including base rates, waive fees and the best ways of contacting our vulnerable customers, ensuring we keep them protected from frauds and scams.
“By introducing our Bold360 chatbot interface, Ella, we’ve been able to get relevant information out quickly, apply the best practice and ensure that our customer journeys are being developed correctly. Due to the volume of questions, some of our customers were finding themselves waiting longer than usual. So digital channels become essential to helping reduce the wait time. Using Bold360, we were able to mitigate issues and answer questions in a more timely way through our chatbot.
“Moving forward, as we open more digital services, we are analysing our data to see if customer will return back to their usual way of banking, now that they’ve seen what a good digital experience can provide. Either way, with Ella, we are ready.”
AI chatbots and humans supporting each other
Ultimately, banking institutions have realised the benefits that digital collaboration can bring to their industry and how it can increase profits, while holding customer experience at the forefront of their minds. By providing 24/7 service, readily available information, consistent and concise answers across channels with behind the scenes support from member services representatives, digital collaboration will prove to be an essential component to the banking industry which will change it in the long term, for the better. While not every institution is ready to place chatbots high on their priority lists, the potential of its adoption should not be ignored.
Yet the use of such emerging technologies also continues to grow exponentially across a host of industries, according to McKinsey. However, financial services organisations are likely to be the biggest beneficiaries with the adoption of such technologies in terms of actual bottom-line business value.
A critical reason for this is that these companies already have access to extremely complex and large datasets, which are a requirement to create different predictive models from this type of technology. Such models are also hugely powerful. They can be applied across a wide variety of financial products and situations, helping these organisations to better understand everything from the possibility and probability of defaults on loans, to customer purchasing intention to detecting fraudulent transactions.
Even the BoE and FCA believe that ML technologies can “make financial services and markets more efficient, accessible and tailored to consumer needs”.
Despite such advantages, to really harness the power of AI and ML and put in place for projects that make an impact with everyday consumers, organisations within the sector do still face some very specific and sizable challenges.
Firstly, financial services is a highly regulated industry whereby personally identifiable information (PII) is required to be protected. Yet this does hinder collaboration as a huge amount of time is necessary to clean and compliance check this information. Due to this, a project’s timescale can really lengthen.
Secondly, despite collecting and managing such a wealth of data, financial organisations face some limitations with the information they have. Even when data has been prepared to develop AI solutions, the actual dataset itself may be under-representative and such limitations are the most cited major barriers that prevent finance organisations from utilising their data assets. up to three quarters (73%) of data actually goes unused for analytics by companies, according to Forrester.
In fact, it is actually quite common that the most valuable information for an organisation is hidden in an under-representative customer category. A biased dataset means the insights gleaned will also be biased. The knock-on effect of this can be quite damaging. It can lead to false assumptions about customer segmentation that leads to higher costs for the acquisition of customers (banks already spend over £279 each year on acquisition per bank account), inappropriate offers being made to customers, which ultimately makes them less likely to purchase, or worse.
Its biggest impact could come in the area of personalisation of financial products to everyday consumers.
Advanced approaches using AI and ML are helping to tackle these challenges. Synthetic data generation technologies have emerged as a highly credible method of protecting PII, while also eliminating the limitations that organisations are facing with their data. The technology, underpinned by AI and ML, constructs a new, entirely synthetic dataset from the original information, one that is highly statistically accurate (up to 95%) but crucially does not reveal individuals’ PII.
It could be transformative for the financial services industry, with organisations like JP Morgan already touting its potential.
Its biggest impact could come in the area of personalisation of financial products to everyday consumers. Undoubtedly such personalisation has improved from tactics such as the ‘Fresno Drop’ which saw over 60,000 pre-approved credit cards mass-mailed to consumers in the Californian city in 1958. However, AI and ML technologies are built specifically to extract insights from data which encapsulates consumers' preferences, interaction, behaviour, lifestyle details and interests. Not only this, but the technology is also developing to such a stage that it can spot and, in effect, ‘rebalance’ biased datasets.
When this approach is implemented accurately, research has found that synthetic data can give the same results as real data. Yet crucially the key benefits include full data privacy compliance and a major reduction in the time needed for product development and testing.
While the successful personalisation of offers, policies and pricing makes a large contribution to the revenues of the business, it also keeps customers happy as they aren’t being bombarded by irrelevant information. This matters hugely as McKinsey found that highly satisfied customers are two and a half times more likely to open new accounts and products with their existing bank.
Having access to such deep insights into all segments is not something that can be put off much longer as consumer behaviour, across generations, is undergoing radical changes already. Research from PwC found that half of younger consumers (those under 35) will open a primary bank account based on a trusted referral from friends or family, by contrast, however, one out of two consumers over 35 will choose a primary bank based on the local presence of a branch or ATM. Such generational differences need to be spotted quickly to keep a financial organisation in step with rapidly changing preferences.
While it is encouraging that more and more financial organisations are using AI and ML technologies, any approach to maximise data’s value must have a coherent strategy behind it. Used in the right way and with the right strategy in place, the opportunity from these technologies offers unlimited potential to financial services organisations.
Matthew Leaney, Chief Revenue Officer at Silent Eight, examines the issue that correspondent banking poses to the financial sector.
On the one hand, it has long been a key mechanism for integrating developing countries into the global financial system and giving them access to the capital they need. On the other hand, correspondent banking relationships are inherently risky for the global banks that grant access to the respondent bank’s customers without being able to directly conduct Know Your Customer/Customer Due Diligence (KYC/CDD) checks on them.
It’s not a small problem: make access too easy and you risk allowing billions of illicit funds through your door; cut off the relationships and you starve emerging markets of capital and drive their transactions into the shadows.
To its credit, the Financial Action Task Force (FATF) understands the dilemma and has provided continued guidance to clarify the issue. In its October 2016 Guidance on Correspondent Banking Relationships, it explicitly stated that its standards “do not require financial institutions to conduct customer due diligence on the customers of their customer (i.e., each individual customer)”. Rather, they require the correspondent bank to conduct sufficient due diligence on the respondent bank’s processes to understand the risk they present and whether the risk is acceptable within their risk management framework.
Still, many global institutions have decided over the past few years to “de-risk” by shutting down or curtailing their correspondent banking relationships in many countries. It’s easy to see why. It makes sense to exit a relationship when the risk associated with it exceeds your risk tolerance. But the solution doesn’t need to be this drastic. After all, correspondent relationships aren’t inherently bad, they just present a higher level of risk than the bank is willing to accept. Lower the risk and you’re back in business.
It makes sense to exit a relationship when the risk associated with it exceeds your risk tolerance. But the solution doesn’t need to be this drastic.
The solution is straightforward, at least in concept: lower the risk by increasing the effectiveness of respondent banks’ AML/CTF programs. This approach is exemplified by our partner Standard Charter’s “De-Risking Through Education” strategy, featuring regional Correspondent Banking Academies to help raise awareness of best practices and emerging technologies.
Heidi Toribio,Managing Director, Global Head Financial Institutions, Global Banking,at Standard Chartered Bank said that the initiative was key to preserving correspondent banking relationships, and removing ambiguity from compliance standards through partnership. “Correspondent banking goes to the heart of facilitating cross-border trade and financing growth, which is central to our DNA and our purpose as a bank,” she said.
A key element to preserving these relationships is improving the controls within the respondent bank by leveraging emerging technologies like Artificial Intelligence. Silent Eight understands this and has developed solutions to meet this need. With its AI-driven screening system, banks in developing countries could demonstrate a data-driven AI process that learns and improves its output as it addresses alerts. The process gives reliable results, resolving each alert and documenting the reason for the action. The whole AI process is systematic, reliable, consistent and auditable, and provides the analyst clear information on which to make a final determination.
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Leveraging AI solutions into AML/CTF programs is a priority for banks in developing countries so they can demonstrate that their programs are up to global standard. It should also be a priority for global institutions that are or were acting as correspondents, since it allows them to diversify into a broader range of markets at an acceptable level of risk. Together with initiatives like De-Risking Through Education, the adoption of technology like Silent Eight can help developing economies once again gain access to global financial markets and help keep their financial transactions out of the dark.
This AI ‘arms race’ is being driven by two tech superpowers: the United States and China. The US is barrelling ahead, with Washington recently signalling its intentions to promote AI as a national priority. Last year, President Donald Trump launched a national AI strategy – the American AI Initiative – which orders funds, programmes and data to be directed towards the research and commercialisation of the technology.
Government involvement and long-term investment in AI has paid off: US companies have raised more than half (56%) of global AI investment since 2015. China, meanwhile, is catching up quickly and is now vying with the US to become the dominant force in the area. In 2017, it laid out a roadmap to become the world leader in AI by the end of the decade – and create an industry worth 1 trillion yuan (or the equivalent of $147.7 billion). As part of the three-step strategy, China has announced billions in funding for innovative startups and has launched programmes to entice researchers.
Achieving economic and political prowess is the ultimate goal. Indeed, AI is a vast toolbox of capabilities which will give nations a competitive edge in almost every field. However, the question beckons: where does Europe stand in this race, and what is at stake? Nikolas Kairinos, founder and CEO of Soffos, offers his analysis to Finance Monthly.
Europe is falling behind
Thanks to great access to home-grown talent and an inspiring entrepreneurial spirit, Europe is still a strong contender in this race. According to McKinsey, Europe is home to approximately 25% of the world’s AI startups, largely in line with its size in the world economy. However, its early-stage investment in the technology is well behind that of its competitors, and over-regulation risks stifling further progress.
Thanks to great access to home-grown talent and an inspiring entrepreneurial spirit, Europe is still a strong contender in this race.
Early last year, for instance, the European Commission announced a pilot of ethical AI guidelines which offer a loose framework for the development and use of AI. The guidelines list seven key requirements that AI systems must meet in order to be trustworthy; amongst the chief considerations are transparency and accountability.
The intentions behind such proposals are pure, albeit counter-productive. Proposing a new set of standards to be followed risks burdening researchers with excessive red tape. After all, AI remains a vast ocean of uncharted waters, and introducing ever-changing hurdles will only impede progress in R&D. Innovative new solutions that have the capacity to change society for the better might never come to light if developers do not have the freedom to explore new technologies.
Meanwhile, a European Commission white paper recommends a risk-based approach to ensure regulatory intervention is proportionate. However, this would only serve to deter or delay investment if AI products and services fall under the loose definition of being too ‘high-risk’.
Upholding human rights through proper regulation is of paramount importance. However, Europe must be careful to find the right balance between protecting the rights of its citizens and the needs of technologists working to advance the field of AI.
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The risk of ignoring AI solutions
What is at stake if AI development falls behind? The risk of ignoring AI solutions is immense, particularly for sectors like the financial services industry which must keep pace with evolving consumer habits.
AI has given the world of banking and finance a brand new way of meeting the demands of customers who want better, safer, and more convenient ways to manage their money. And with populations confined to their homes for long periods of time in the face of the coronavirus pandemic, the demand for smart digital solutions that allow people to access, spend, save and invest their money has peaked.
Those who fail to adapt by leveraging AI are at risk of losing their competitive advantage. The real value of AI is its automation potential; AI solutions can power more efficient and informed decision-making, taking on the data processing responsibilities that would normally be left to humans. If used wisely, smarter underwriting decisions can be made by delegating the task of assessing loan and credit applications to AI. Not only is this markedly faster than performing manual checks, but the chances of making risky decisions will also be reduced: AI software can be used to build accurate predictive models to forecast which customers have a higher likelihood of default.
Accurate forecasting is needed to ensure the continuity and success of a business. Again, those businesses that utilise the AI toolsets at their disposal stand to benefit from advanced analytics. Machine learning – a subset of AI – is adept at gathering valuable data, determining trends, anticipating changing customer needs and identifying future risks. Those who turn their back on AI risk losing out on sound risk management, leaving their profits and reputation vulnerable.
Accurate forecasting is needed to ensure the continuity and success of a business.
At the heart of any bank or financial firm, however, lies the customer. Traditional bricks and mortar banking is no longer the favoured option when money can instead be managed online. Yet, while online banking is by no means a new phenomenon, AI offers the hyper-personalised services that customers seek. Indeed, a global study conducted by Accenture recently found that customers today “expect their data to be leveraged into personalised advice and benefits, and tailored to their life stage, financial goals and personal needs.” Meanwhile, 41% of people said they are very willing to use entirely computer-generated advice for banking.
There is clearly an appetite for innovation from the consumer side, and financial institutions must step up to enhance their offering. Enhanced, real-time customer insights generated by AI will optimise recommendations and tailor services to each individual. AI-powered virtual assistants that offer personalised advice and tools which can analyse customers’ spending to help them meet their financial goals are just some of the ways that financial institutions can create a better customer experience.
These are just a few of the many incredible applications of AI within the financial services sector. Not only can it enhance a business’ core proposition, but the cost-saving potential and operational efficiency is becoming difficult to ignore.
AI technologies are transformative, and those who fail to invest in new solutions risk losing out on the multitude of benefits on offer. I encourage business leaders to think carefully about the about the outcomes that they want to drive for their institution, and how AI can help them achieve their goals. I hold out hope that Europe as a whole will ramp up AI development in the coming years, and I hope to see governments, businesses and organisations working together to continue to push forward the AI frontier and pursue innovative applications of this technology.
Nikolas Kairinos is the chief executive officer and founder of Soffos, the world’s first AI-powered KnowledgeBot. He also founded Fountech.ai, a company which is driving innovation in the AI sector and helping consumers, businesses and governments understand how this technology is making the world a better place.
