This is a sponsored blog post by Nick Kerigan, Head of Innovation, Swift.

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Working with Clearstream, Northern Trust, SETL and others, SWIFT plans experiments in 2022 to explore how it can support interoperability in the development of the tokenized asset market.

Relative to cryptocurrencies and stablecoins, the current market capitalization of tokenized assets is small, but momentum for these digital assets is expected to accelerate rapidly in the coming years. By some estimates, volumes could reach some 24 trillion USD by 2027.

Tokenization can be applied to stocks and bonds, but also to illiquid assets, including commodities, property or even art. For example, a share or bond with a high value per unit (say over $500) can be divided into digital pieces that each have ownership and value. This increases the liquidity of the overall asset, and accessibility, by enabling a wider demographic of people to invest in assets that may historically have been unavailable to them.

Banks and securities firms are responding to tokenization by developing services − including fractionalization, a process whereby assets are broken into smaller value digital tokens − amongst other digital asset servicing capabilities, such as private key safekeeping. Financial market infrastructures also are embracing tokenization by supporting the full lifecycle of digital securities.

As interest increases, SWIFT is exploring how it can enable and improve interoperability between participants and systems during the transactional lifecycle of tokenized assets. To this end, SWIFT plans a series of experiments throughout 2022 leveraging its trusted role as a central platform to explore the issuance, delivery versus payment (DVP), and redemption processes, to support a frictionless and seamless tokenized asset market. These experiments will use both established forms of payment and central bank digital currencies (CBDCs).

Asset tokenization − a trend and challenge for securities markets

Over the coming decade, tokenized and traditional assets will likely co-exist, and this poses potential challenges. One major risk is that a variety of technologies, platforms and regulatory environments will create a thicket of connections for securities market participants. This could result in inefficiencies and fragmentation, as well as rising costs and risks across the industry.

SWIFT is uniquely placed to help solve this challenge. As a neutral, global cooperative with a strong focus on ensuring interoperability and setting standards for the industry, we are able to interconnect market participants and simplify operations by completing activities centrally that otherwise would be performed bilaterally between institutions. This role relies on SWIFT’s strong identity and security frameworks, alongside our unparalleled reach and record of reliability.

With this in mind, we are looking at how we can support both traditional and tokenized assets flows, with a focus on regulated assets only. We would not become a crypto-custodian nor perform direct settlement of tokenized assets as a financial market infrastructure would. Rather, we see our role as helping to connect all entities as efficiently as possible and enabling our customers to provide better services to their end-users.

Collaborative innovation in action

SWIFT, Clearstream, Northern Trust, SETL and other industry participants are exploring the feasibility and benefits of SWIFT as an interconnector, linking up multiple tokenization platforms and various cash-leg payment types. This will build on SWIFT’s successes in achieving interoperability for CBDCs outlined in our whitepaper published last year.

In the experiments, Clearstream and Northern Trust, alongside other industry players, will represent key parts of the tokenized − and traditional − asset ecosystem, including securities market infrastructures, as well a local and global custodians. SETL and Northern Trust will support SWIFT and the participants in the integration between the various DLT environments and with transaction orchestrations using their respective capabilities. Results of the experiments will be shared with the financial community afterwards.

“As a neutral cooperative with a reach across 11,500 institutions in more than 200 countries, and oversight by central banks globally, SWIFT is uniquely placed to engage closely in the future of securities,” says Thomas Zschach, Chief Innovation Officer, SWIFT. “We look forward to this set of new experiments and innovating collaboratively with market participants on the emerging trend of tokenized assets.”

“Our vision for instant and frictionless transactions not only applies to traditional securities instruments but also to new asset classes as well,” adds Vikesh Patel, Head of Securities Strategy, SWIFT. “The insights from this exercise with leading capital markets participants will help us define and prioritize the concrete steps required to enable seamless processes for tokenized assets.”

Anthony Culligan, Chief Engineer at SETL, stated: “We are very pleased to be contributing to this important initiative. We see significant innovation in securities tokenization at the moment and these experiments have the potential to create broader accessibility and interoperability between the emerging networks.”

Keep an eye out for the results of our experiments – we’ll be publishing them later in 2022. In the meantime, to find out how your firm could collaborate with us, get in touch at innovate@swift.com. We can’t wait to hear from you.

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Photo by Alina Grubnyak on Unsplash

This is a sponsored post by Paul Higgins, EMEA Banking Lead, Mendix, Silver Sponsors of FinovateEurope, March 22 – 23 in London.

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Innovation in the banking sector has proven its value to society during the COVID-19 crisis. For example, during times of physical distancing, enabling contactless banking and offering bank employees the possibility to work remotely were particularly relevant. Looking to the future at a post-COVID, post-Brexit world, it’s time to reflect on how the sector has adjusted, the sweeping changes ahead and the challenges those changes present.

The burden of legacy tech

The number of regulators and ever-changing regulations can make the financial services industry a daunting place. Changes must be implemented quickly to ensure compliance and avoid significant fines. This means that IT delivery in a financial institution is often more complex and nuanced than in less regulated industries. Many organizations, particularly the more traditional banks, run on legacy monoliths that aren’t easy to make changes to. Such changes carry the risk of causing outages that can damage the reputation of the bank and can also incur fines. Just last month, Nationwide received negative press because of a payments outage around the time that many get paid and pay their bills.

Can a financial institution risk being left behind by not migrating off legacy systems?

Many banks try to reduce the risk of such outages at critical times of year, usually end of month, quarter, and year, by establishing “frozen-zones” that limit changes to IT systems to only those deemed as essential to the stability of the systems. Additionally, the appetite to replace legacy systems is very low due to the huge complexity and inherent risk involved – often the famous adage applies “if it isn’t broken, don’t fix it”. But you have to ask, can a financial institution risk being left behind by not migrating off legacy systems?

Seeing off nimble fintechs

The pandemic showed how vital digital transformation is for every industry – people needed remote access to services, products, and their jobs. In the financial industry, the consumer-facing part is generally quite far in the digitalization journey, with most customers able to access online and mobile banking. Not so with corporate banking and internal employee access to systems. But according to McKinsey, in the case of remote working, companies moved 40 times more quickly than they thought possible before the pandemic. And the expectation is that the digital transformation journey will continue this acceleration.

In the past, accelerating digital transformation has required large teams of developers working non-stop on a single project for months. The pandemic highlighted that this was simply not sustainable. Tech teams need to be able to juggle between projects, adjusting their priorities as and when required. To do so, they require a different approach to their delivery.

Nine out of 10 IT leaders in financial services believe their firm will need to invest in digital projects over the next two years just to survive in a rapidly changing market.

Low-code provides a compelling answer to this new problem. Low-code platforms enable even the most traditional banks and financial services companies to compete with nimbleness of their fintech rivals. The time to act is now: recent Mendix research found that nine out of 10 IT leaders in financial services believe their firm will need to invest in digital projects over the next two years, just to survive in a rapidly changing market.

The value of low-code

Many banks in Europe have turned to cross-functional, agile teams to provide the collaboration needed to develop the solutions that answer customer needs and drive revenue growth. This requires providing both developers and non-developers with tools that enable them to operate together. And financial institutions that haven’t implemented such agile methods still recognize the value of close collaboration between business and IT.

The Mendix low-code platform is a recognized market leader because it fosters this collaboration by providing two integrated development environments: one for non-technical people, often from the business side, and another for pro developers. This enables non-technical staff to work hand in hand with the development team in creating applications.

Both the technical and non-technical teams use the same visual development language to develop apps, bringing together those that understand the business problems with those that understand the IT landscape, core systems, and services to contribute to the vision of a product. And IT stays in control through built-in governance and guardrails that ensure compliance with the established standards of the organization.

It seems set that low-code will play a vital role in the financial services industry in accelerating digital transformation and increasing the speed of innovation.

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Photo by Essow from Pexels

This is a sponsored post by Carol Hamilton, Senior Vice President, Global Solutions at Provenir.

New survey data reveals uncertainty in the accuracy in credit risk modeling, underscoring the need for AI, machine learning, and alternative data.

Consumer credit markets have changed dramatically over the past two years during the Covid-19 pandemic, translating into economic uncertainty for millions across the globe, and it seems for the fintechs and financial services organizations that serve them.

After all the disruption we’ve seen over the past 24 months, how sound are credit risk models? This was the question we sought out to find the answer for with a global research study that surveyed 400 decision makers in the industry. The results were more than a little unsettling — only 18 percent of fintechs and financial services organizations believe their credit risk models are accurate at least 75 percent of the time.

That’s pretty astonishing — especially given the fact that the rest of the respondents indicated they believed their credit risk models were accurate less than 75 percent of the time.

Credit risk modelling is at the heart of every fintech and financial services company and this financial fault line in credit risk decisioning should send chills down the spine of the entire sector.

This “risky business” uncertainty in credit risk modelling accuracy may be why real-time credit risk decisioning was respondents’ No. 1 planned investment area in 2022, as organization’s work to resolve this financial fault line in credit risk decisioning. The survey underscored the growing appetite for AI predictive analytics and machine learning, data integration, and use of alternative data as the means to improve credit risk decisioning.

Aside from improving credit risk modelling accuracy, organizations are also employing credit risk decisioning platforms to help address the key priorities of fraud detection/prevention and financial inclusion. And increasingly these credit risk analysis strategies employ the use of alternative data.

Fraud continues to grow for financial services and lending firms, both before and during the pandemic, with identity fraud being a key factor.

Sixty-five percent of decision makers in our survey indicated they recognize the importance of alternative data in credit risk analysis for improved fraud detection. Additionally, 51 percent recognize its importance in supporting financial inclusion. Alternative data is a more varied way for lenders to evaluate those individuals with a thin (or no) credit file put together a more holistic, comprehensive view of an individual’s risk. This vastly benefits those who can’t be easily scored via traditional methods, while also benefitting financial institutions, by expanding their total addressable market.

To level-up credit risk decisioning, organizations need more data, more automation, more sophisticated processes, and more forward-looking predictions. And to do that, businesses need AI that can provide immediate impact to the decisioning process. AI-enabled risk decisioning is seen as key to usher in improvements in many areas, including fraud prevention (78%), automating decisions across the credit lifecycle (58%), improving cost savings and efficiency (57%), more competitive pricing (51%), and improving accuracy of credit risk profiles (47%).

For unbanked and underbanked consumers, AI gives organizations the opportunity to support those consumers’ financial journeys. Financial services organizations typically struggle to support these consumers because they don’t come with a history of data that is understandable by traditional decisioning methods. However, because AI can identify patterns in a wide variety of alternative, traditional, linear, and non-linear data, it can power highly accurate decisioning, even for no-file or thin-file consumers.

While AI and machine learning, and alternative data may have been on the credit risk decisioning “nice to have” list a few years ago, fintechs and financial services organizations are quickly realizing legacy technology and methods simply are not up to today’s task of credit-risk decisioning. By deploying new technology such as AI and machine learning, and embracing alternative data, organizations are on their way to improved confidence in the accuracy of their credit risk models – moving to remediate their credit risk “risky business.” In doing so, they will be more prepared to react to changes moving forward, while supporting inclusive finance.

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Carol Hamilton is Senior Vice President, Global Solutions at Provenir, which helps fintechs and financial services providers make smarter decisions faster with its AI-Powered Risk Decisioning Platform. Provenir works with disruptive financial services organizations in more than 50 countries and processes more than 3 billion transactions annually.

This is a sponsored post, written by Tracy Schlabach, Director of Marketing at Accusoft.

Fintechs, ISVs, big banking corporations, and SaaS solutions all have immediate needs in common, they all need to bring forth financial technologies that improve both the customer and employee experience. The challenge is building and launching these technologies quickly, efficiently, and within a scalable, sustainable model. Product managers and development teams are all evaluating options to assist with meeting stakeholder demands for quality, while also meeting the need for speed to market. Enter the hidden value of third-party software integrations.

The secret life of APIs

Digital transformation is an ever-increasing priority for all businesses as well as an initiative that is seeing a surge in funding. In a recent State of the API Economy 2021 report by Google, 56% of enterprise leaders say APIs help them to build better digital experiences and products. Leaders are also finding value in focusing on an API-driven strategy and 52% say APIs accelerate innovation by enabling partners to leverage digital assets at scale.

How API integration works

At a very simple level, an API consists of code that allows two separate technology systems to communicate and interact with one another. It functions as a translator and messenger; delivering user requests and data from one system to a completely separate system. This effectively allows an application to utilize the features and data of other applications without having to build out that functionality from scratch.

For example, the Uber ride-sharing app connects customers to available drivers within a specific area. It does this with a combination of smartphone geolocation and accurate maps, but the Uber app doesn’t have mapping capabilities. To get those features, it connects to Google Maps by way of an API that allows it to access the relevant navigational data and use it to connect customers to drivers.

Purchasing new software doesn’t mean throwing out existing tools, which substantially reduces the risks associated with technology investments and upgrades.

Another key function of APIs is their ability to automate key processes and connect legacy infrastructure to newer technology systems. Data can be collected in one system, for instance, and “pushed” into another system automatically. This not only eliminates the complicated (and error-prone) task of manually transferring data between different systems, but also allows users to build a workflow in an application they’re already accustomed to, without having to learn an entirely new system.

More importantly, since APIs allow newer technologies, devices, and legacy applications to talk to each other, they provide firms with substantial flexibility when it comes to adding new platforms. Purchasing new software doesn’t mean throwing out existing tools, which substantially reduces the risks associated with technology investments and upgrades.

The cost savings with API integrations

When you purchase a third-party API integration you’re gaining more than additional functionality for your application. You also gain access to a team of developers and support specialists who are here to assist you from POC to deployment and beyond. Leaning on the specialization of a third-party vendor allows your developers to focus on application enhancements and release your product to market faster. This ultimately saves your company valuable development time and realizes product revenue faster.

Interested in learning more?

Could your business benefit from an API-led digital transformation strategy? Schedule a consultation today to learn more about the document management API integration options available from Accusoft.

This is a sponsored post by Cyvatar, Gold Sponsors of FinovateFall 2021. Written by Craig Goodwin & Corey White.

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In case you missed it, we’re losing the battle against hacks and breaches. Even though more and more security tools come online every year, personal information and other sensitive data doesn’t get better protected.

We buy more products. We get breached.

We adhere to compliance standards. We get breached.

Why can’t we do better?

Increasingly sophisticated and relentless attacks and high-profile breaches, like the one at Solarwinds, spur the purchase of more and more tools, but companies rarely (if ever) have the right people and processes in place to ensure the tools they purchase are installed–installed and configured correctly–to say nothing of the ongoing assessments, remediation, and maintenance needed to achieve a solid return on their cyber investments.

The industry’s response has long been to build newer, shinier products, knowing that buyers will come; when the technology fails to defend against a breach, managed services providers step in to remediate after the fact and “manage” the customer’s environment against future incursions.

Then a Solarwinds or an Equifax or a Marriott happens.

It’s a vicious cycle–a cycle companies can break by stepping away from traditional notions of ownership (i.e., buying or “owning” a security tool, platform, or solution) and embracing the Membership Economy.

What is the Membership Economy?

The Membership Economy, coined by Robbie Kellman Baxter in 2015, includes any organization whose members — what another company might call customers or clients — have an “ongoing and formal stake” in that organization.^[1] The human desire to belong, to be part of a community or affiliated with an exclusive organization, is fulfilled in the Membership Economy, and Netflix is one of its best-known acolytes.

Key components of the Membership Economy include:

• Continually focusing on the needs of members
• Understanding your members’ frustration as well as their satisfaction
• Embracing a willingness to forge new paths to meet member desires or address their concerns–flexibility, innovation, and evolution are all part of this process
• Communicating a strong, clear value proposition
• Investing in the membership experience

Cybersecurity companies, like many technology organizations, still focus on transactional sales. Customers buy a software or services package for a period of time–typically two to three years–and are largely left to fend for themselves until their contract comes up for renewal. Also like other technology deployments, security installations can be complex, costly, and time consuming, often making it difficult for customers to change or add products in their production environments. Even when a customer is unhappy with a product, swapping it out for something new may be more trouble than the customer thinks it’s worth, which leaves little incentive for transaction-driven security companies to foster meaningful innovation in their offerings.

In other words, ownership in cybersecurity is a liability.  The thousands–even millions–of dollars organizations spend on tools and platforms tied to those multiyear licensing agreements effectively hold them hostage regardless of product efficacy. In the event of a breach, they’re still stuck in their contract and may even feel the need to buy more tools to bolster their security posture. Security product companies are hamstrung by the model too: Once they create products to deliver their solutions, they become limited by the scope of their own design, for good or ill, and innovation remains stalled.

Groundbreaking innovation through experimentation, development, and even dumb luck has enabled significant economic growth–and has toppled entire organizations that were upended by the thoughtful and rapid advancement of others,^[2] as Blockbuster was by Netflix. As the pace of technological change continues to accelerate with force, so too does the cyber attack surface.

Taking the next step

Membership–the Netflix model–is just such a foundational change. It can be every bit as disruptive and transformational to the cybersecurity industry as Netflix itself was to the movie rental and streaming industries. Here’s how.

Subscriptions alone do not a Membership Economy make.

Subscriptions are a good first step. Subscriptions make it easy for members to select the pricing and options that are best for them, and consistent and predictable revenue streams benefit shareholders and users alike. But subscriptions alone do not a Membership Economy make. It’s important that security companies understand the need behind each package they develop so they can grow members into new offerings and ensure value is continuously delivered.

Additionally, the Membership Economy can’t work without high levels of member engagement, which is why Baxter recommends that a good membership program be beneficial for members as well as the company that serves them. Benefits stemming from loyalty create bonds, even emotional connections, between members and the companies they associate with, which in turn create vibrant communities of influencers and evangelists that become a continual source of innovation for Membership Economy organizations. By staying close to your members and active in the communities you share with them, you’re always a part of the feedback loop, enabling you to continue to evolve your offerings to meet member needs.

Cybersecurity-as-a-service, or CSaaS, brings all of these concepts to life. CSaaS is inherently a member-driven model, allowing providers to focus on access rather than ownership. Instead of selling transactional point solutions or fee-for-services to create what we used to call customer “stickiness,” security companies can use the membership model to level the playing field and democratize cybersecurity, making the best protection accessible and affordable for every size organization, even those with no cybersecurity expertise in house.

The CSaaS membership model offers a new, innovative paradigm for successful protection from today’s advanced cyber-attacks by pairing skilled security advisors with proven processes and best-of-breed technologies to deliver guaranteed business outcomes. Importantly, CSaaS handles the heavy lifting associated with evaluating and recommending solutions from more than 4500 security vendors so that members can focus on scaling their businesses without worrying about securing the sensitive data and information that make those businesses successful.

CSaaS also ensures that recommended solutions are installed and configured completely–and correctly–in addition to providing ongoing remediation of cyber threats and vulnerabilities and regular maintenance of security tools. By selling membership rather than ownership in the CSaaS model, members can achieve faster compliance to standards like NIST CSF, SOC 2, PCI, and HIPAA.

The CSaaS membership model is Netflix for cybersecurity: inherent innovation and bespoke solutions at scale. Begin your free CSaaS membership and start your journey to cybersecurity confidence today.

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^[1] Baxter, Robbie Kellman. “The Membership Economy: Find Your Superusers, Master the Forever Transaction, and Build Recurring Revenue.” McGraw-Hill Education. 2015, p. 26.

^[2] Harkins, Malcolm, et.al. “The R(e)volution of Web Application Security.” Cymatic, Inc. 2021.

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Photo by Clay Banks on Unsplash

This is a sponsored post from InterSystems, Gold Sponsor of FinovateFall 2021. By Carmen Logue, Product Manager, InterSystems; commentary on survey report Embracing embedded analytics and a comprehensive data analytics platform >>

Data-driven decision-making is something most businesses aspire to. However, for the majority, significant data silos across the enterprise often means that the data they are using is delayed and inconsistent – resulting in decisions that are neither timely nor accurate. Instead, what organizations need is real-time access to their data and a consistent enterprise view. Fortunately, this is where a data fabric with both embedded analytics and self-service business intelligence (BI) can be extremely powerful.

The use of embedded analytics and self-service BI in combination with a data fabric allows organizations to give a wider range of users the ability to visualize and explore data more freely, empowering employees, partners, and customers with accurate information. Yet, while most organizations recognize the value of actionable analytics, currently most struggle to provide critical metrics and access to ad hoc analysis. In fact, our research shows that only 7% of organizations say more than half of their employees have access to a data analytics platform.

With a staggering 93% of organizations revealing that the majority of their employees don’t have access to analytics, let’s look at how they can set themselves up to become a more data-driven organization.

Bridging data silos with embedded analytics tools

To gain the most benefit from their data and analytics platform, businesses should look to start prioritizing and bridging data within their organization. While they are likely to be faced with a large number of silos, prioritizing key metrics and iteratively connecting data sources will allow companies to reduce redundant data and provide a common language across data sources.

Implementing a smart data fabric, a new architectural approach, will also help to remove silos and help organizations to gain a common semantic view of the data, even if that data remains distributed. Businesses that have grown through mergers, acquisitions or organic expansions benefit from both local and organization-wide visibility. A common semantic view will also enable performance comparisons over time – day to day or year over year, and allow for analysis of patterns and trends.

Vitally, this enterprise view will give businesses a firm foundation to introduce analytics capabilities.

Figure out what needs to be measured

Once they have started taking incremental steps to unify their data, organizations should seek to understand where the real business problems lie and the questions they need to answer. As part of this, they should consider what issues or challenges their CEO and business counterparts, such as the CIO and COO, currently face and what will help them characterize and measure improvements.

Using this as a starting point and working back will allow the IT teams who will be undertaking the implementation to understand what data and insights they need to provide to answer the questions those leading the business have. It is also important to leave capacity for additional metrics because once they are being used effectively, there will be a need for future measurements and answers.

This approach will ensure the organization is clear about where to apply analytics to derive the most value and to impact the most change. Following this method, they can then build out the capabilities across different parts of the organization.

Success lies in collaboration

While likely to be driven by IT teams, implementing analytics platforms isn’t just an IT initiative. Instead, it requires collaboration from individuals across the organization.

To guarantee success, different teams should work together iteratively and constantly assess the contributions being made by the introduction of analytics platforms and continue to refine the use cases and required metrics to understand whether they are providing value and what changes might be needed to measure progress.

Taking this approach will help to iron out any issues as they occur and ensure that all users are extracting real value from the platform.

Simplifying the complex

For most businesses, obtaining a single source of truth from which they can gain insights can be extremely complex. Not only do organizations tend to have a large number of data silos, but they already have a range of different technology in place, from data warehouses, data lakes and data marts, to integration platforms and BI tools. As such, the majority are ideally looking to simplify their technology infrastructure, but without having to rip and replace.

Smart data fabrics make this possible, helping businesses to unlock the true potential of their data by speeding up and simplifying access to data assets across the entire business. This is all while allowing existing legacy applications and data to remain in place, to enable organizations to maximize the value from their previous technology investments.

Realizing the value of embedded analytics

The benefits of embedded analytics capabilities span across all industries, allowing businesses to make more informed decisions and enabling a variety of business users to have access to actionable insights. A data platform like InterSystems IRIS which includes embedded analytics and ad hoc analysis tools, also forms an integral part of a smart data fabric architecture. InterSystems IRIS can provide organizations with access to live data on-demand, integrated from multiple applications such as trades, equity and fixed income positions, or treasury.

This technology ensures that businesses are able to make decisions on current data, including live transactional data, and eliminates latency from source systems. Additionally, it supports business user self-service analytics, enabling drill down and ad hoc capabilities and can also help to automate time consuming tasks such as ongoing integration and interoperability – freeing up the IT team to focus on more value-adding tasks.

With access to more comprehensive, accurate, and timely information, employees across businesses will be better placed to make informed decisions and measure the success of new initiatives needed to drive their organization forward.

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Photo by Norbert Kundrak on Unsplash