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Finovate Blog
Tracking fintech, banking & financial services innovations since 1994
Accessing and leveraging enterprise data in a timely fashion has become one of the most definitive ways to outpace the competition in the business world. In the financial services industry, financial firms must be able to use data to generate a complete view of the business and the customer at many levels of the organization.
Until recently, data-driven insights were the sole purview of leaders, stakeholders, and team members with the right technical expertise. Now, financial organizations are searching for ways to deliver insights across their organizations, from the board room to one-on-one interactions between customers and customer service representatives.
This is what’s known as data democratization, and it will be key to driving innovation in the financial services industry moving forward.
According to a recent study sponsored by InterSystems entitled “Empowering Line of Business Users Through Data Democratization,” one of the most important steps in democratizing the enterprise’s data is breaking down data siloes. The study, produced by WBR Insights and published by the Financial Information Management (FIMA) conference series, engaged 250 leaders from the financial industry to learn just how they intend to improve access to data over the next 12 months.
Data Access, Compliance, and Analytics Are Key Projects for the Future
Researchers concluded that any company that isn’t satisfied with its current ability to democratize data may need new data technologies. They may also need to consult with third-party experts to deploy enterprise-wide data governance processes and manage changes among staff members.
Indeed, 62% of the respondents said that providing improved access to siloed distributed data is among their top data priorities for the next 12 months.
Data Siloes Are the Biggest Barrier to Innovation
Innovation in the financial services industry has taken on a variety of forms. Self-service solutions for customers have become particularly attractive to organizations recently, as customers are demanding more ways to connect with their financial companies from home. Artificial intelligence and machine learning are also making inroads among financial firms due to their ability to make predictions and offer strategic insights.
But the most important asset for all these innovations is data. Without accessible and usable data, the organization can’t make use of advanced technologies or develop innovative applications for them. Too often, enterprise data is locked in silos due to systems that don’t communicate with each other.
According to the respondents to the FIMA and WBR Insights study, data siloes were among their top three biggest barriers to innovation.
Specifically, 54% of the respondents listed “data silos” as a top barrier to innovation. These organizations know that they have valuable data locked away in their systems, but because those systems can’t communicate with each other, there is effectively a barrier between the organization, its data, and the insights that data contains.
In the context of the financial services industry, it should be no surprise that unlocking the potential of that data is a top concern. Data is quickly becoming a new currency, and the ability to use customer data for insights is driving competition across the sector.
These are just a few of the insights offered by the new report by WBR Insights and FIMA. If you’d like to gain actionable insights into how you can democratize data at your organization, download the report today.
The financial industry has made significant investments in document lifecycle management solutions to enhance productivity, accuracy, and flexibility. There is broad recognition that paper-based processes are a huge source of waste and inefficiency, but simply transitioning away from paper often isn’t enough on its own to achieve true digital transformation. That’s because performing a digital-based process manually still presents many of the same problems. In order to leverage the true benefits of digital document management, fintechs need to implement data capture and document generation capabilities as part of a broader process automation solution.
A Quick History of Data Capture & Document Generation
To understand how fintechs can use data capture and document generation technology to enable their digital transformation, it’s helpful to take a moment to understand the history of these tools and how they’ve developed since their origins.
Data Capture
The financial industry was an early innovator in data capture technology with the development of the specialized OCR-A font in the 1960s. This simple monospace font is still used today for the account and routing numbers on an ordinary bank check. Early data capture technology relied on pattern recognition, so an exact pixel match was needed to read the characters electronically and match them to a corresponding character in a font library. While this worked well enough for scanning printed bank checks into a computer system to track transactions, reading anything else on the check with an automated system required further developments in data capture tools.
Modern character recognition technology utilizes a more sophisticated feature detection approach that uses the component elements of each character to distinguish them from one another. An “A,” for example, usually consists of the same basic elements (two angular lines that come to a point with a horizontal line crossing them) regardless of the font used. Breaking characters down into their component elements has even made it possible for software to read handwritten characters as well as machine-printed text.
Document Generation
Document generation technology emerged in the 1970s in the form of document assembly, which was originally used by lawyers to streamline contract creation. Contracts are highly structured and rules-oriented, which made it easy to build a decision-tree logic that could be understood by the software tools of that era. Early document assembly programs used a collection of document templates that incorporated conditional fields the software could replace automatically each time it generated a contract.
Modern document assembly is typically used as part of a more robust document automation solution. Software extracts information from a database and inserts it into a template to generate unique documents quickly, easily, and accurately. These programs are much more sophisticated and flexible than early document assembly tools, allowing organizations to programmatically generate a wide range of documents without ever having to look at the contents prior to the final review process.
Data Capture & Document Assembly in Fintech Today
Despite being an early innovator in OCR technology, the financial industry has been slow to implement more robust data capture capabilities throughout their operations. According to a recent study, 63% of banks are still collecting information from documents manually, a process that’s not only time consuming, but also incredibly prone to error. They’ve been slightly faster to adopt document generation, with 49% of banks still relying on manual processes to create documents.
Ironically, fintech organizations are even more dependent upon manual practices than traditional banks. When it comes to data capture, 75% of fintechs are reviewing documents and entering their data manually rather than using an automated solution. The story is largely the same for document generation, as 79% of them are still creating documents manually.
Understandably, most of these organizations are planning to implement some form of automated data capture and document generation solution within the next two to three years. That’s because they recognize that it will be difficult to achieve true digital transformation without them.
Why Data Capture and Document Generation Are So Important for Fintech
Fintech companies have developed a wide range of innovative financial tools that allow consumers to take better control of their finances and help organizations manage their resources more efficiently. In order to deliver those streamlined solutions, however, fintechs need to have the capabilities in place to make their own processes more efficient.
Data capture and document generation work together to help these organizations maximize the value and potential of their document management systems. Financial information can be submitted in many different formats, ranging from digital forms and fillable PDFs to images, flattened PDFs, and scanned documents. Extracting information from each of these formats requires a sophisticated understanding of data capture that few software developers possess.
Once that data is extracted, it can be routed anywhere it’s needed by workflow automation tools. That could be a new document that’s being generated, but more often it will be sent to a database. When the time comes to generate a new document, previously captured information can be inserted wherever it’s needed programmatically. Multiple documents (or just sections of them) can also be merged or split apart to create entirely new ones filled with information drawn from several sources.
All of this can be done in a matter of seconds with the right software integrations, which saves a tremendous amount of time for fintech teams who have many other priorities to focus on. By incorporating robust data capture and document generation capabilities into their platforms, they can provide faster, better functionality to their customers. Rather than uploading a document and waiting for it to be processed, information can be extracted and routed wherever it’s needed instantly to facilitate faster reviews and resolutions.
Another key benefit of data capture and document generation is accuracy. Between manually reviewing information, entering it by hand into a system, and then retrieving it to create new documents, there are plenty of opportunities for mistakes to be made. In a financial context, those errors often have the potential to be systemic, creating additional errors that are time consuming and expensive to remediate. Automated extraction and assembly remove the risk of human error, which enables fintechs to accelerate and scale their processes more effectively.
Integrating Data Capture and Document Generation with Accusoft
For over 30 years, Accusoft has been a pioneer in building software integrations that expand application functionality. We provide a variety of data capture and document generation solutions that meet the needs of today’s fintech platforms. Whether you’re incorporating functionality directly into your application with an SDK or deploying a cloud-based solution that connects to one of our APIs, we have the flexibility to help you integrate the features you need to complete your digital transformation. To learn more about how Accusoft can enhance your fintech application with data capture and document generation, talk to one of our solutions experts today.
Many systems for managing the document life-cycle process could be more efficient.
Banks and financial technology (fintech) companies commonly use document life-cycle management solutions to make their back-office functions run more smoothly. To take full advantage of these systems, organizations must be able to transform documents into a format they can work with.
However, this crucial first step in the process remains cumbersome for many organizations. Even after documents are in the system, organizations need to be able to do more than view them. “The key to managing back-office tasks more efficiently is capturing and extracting data from documents without bogging employees down with manual processes,” said Tracy Schlabach, Director of Marketing at Accusoft. The ability to work with documents and their data can help organizations realize the full efficiency of a comprehensive document management solution.
Over the past two years, enterprise leaders around the world have had to respond to disruption, unpredictability, and unprecedented challenges. The way the world interacts and transacts has changed, and across millions of businesses using Stripe, we’ve noticed that the capacity for businesses to adapt has been a major determinant of resilience and growth.
An adaptive business initiates change; an agile business reacts to it. The next generation of industry leaders will be companies that anticipate and take action to capture emergent opportunities, using their flexibility as a competitive advantage. They execute on strategies to find new revenue streams, pursue global expansion, and partner to scale faster. According to a recent study from Forrester, adaptive businesses grow at more than three times the industry average.
Stripe worked with The Economist Impact (formerly known as The Economist Intelligence Unit) on a research study that takes a deeper look into the core characteristics that make enterprises adaptive, the strategies leaders are pursuing as online commerce expands, and how the ability to navigate change is an enduring competitive advantage.
Report overview
The analysis in the report is based on a survey of 600 C-level executives, and around a third of the respondents (34%) are based in Europe, with another third (33%) in North America, and the balance in Asia-Pacific. Their companies are distributed across a wide range of industries, with the largest representation from the financial services (15%), technology (15%) and retail (11%) sectors. Just over half (53%) of the respondents work in companies earning annual revenue of over US$500m, with the rest earning between US$100m and US$500m. Most of the companies represented (83%) are no older than 20 years, and 44% have existed for fewer than ten years.
Executive summary
The Covid-19 pandemic brought about profound change, affecting long- standing consumer behaviours and preferences, and in some cases permanently changing competitive landscapes. Businesses had to make consequential decisions in short order—rapidly modifying business models, accelerating digital transformation, seeking out new revenue streams, moving or re-thinking supply chains, entering new product or geographic markets, and improving online customer experiences.
The past two years have created an inflection point for enterprises—one that is likely to define business success for the next decade. Risks to business are considerable, yet organizations that are able to successfully navigate disruption while positioning themselves for growth can be a competitive advantage in today’s global economy. The findings in this report detail characteristics of an adaptive enterprise.
Key findings from the study
Adaptability is decisive. Businesses able to maintain or grow revenue under the difficult conditions of the pandemic appear to have made proactive choices in adapting to widespread change. When asked about chief factors enabling success, CxOs point to their firms’ ability to change or adopt new business models, serve customers online, and scale in short order to shifts in customer behavior and demand. Companies suffering revenue declines, by contrast, highlighted struggles with some of these same areas.
Going for growth. The pandemic has not slowed, but instead seemingly accelerated businesses’ pursuit of growth or new revenue streams. Survey respondents indicate a strong intention to boost investment in technology and show little support for cost-cutting. Rather than contract their businesses, a majority of CxO respondents—80%—believe global expansion is central to their business viability. Over half—52%—plan to increase the number of countries they trade in over the next year. Only 13% said they would decrease.
Digital is integral. The flight of consumers to digital channels was dramatic in 2020, and CxOs in the survey expect the consumer trends that accelerated during the crisis to gain additional momentum. Among the surveyed companies, 28% say half or more of their company sales came via online channels before the pandemic, 46% indicate the same was true during the pandemic (as at October 2020), while 54% anticipated half of their revenue to come from online channels by the end of 2021. A majority—82%—believe that their customer’s shift to online purchasing during the crisis will continue, even after the pandemic is over.
Anticipation is key. Far from all companies were ready for a digital acceleration: 69% of CxOs say their firms under-invested in online strategies before the pandemic. A majority—53%—say they now plan to boost investment in digital transformation over the next 12 months, aiming to improve processes or operations, innovation and customer experiences. The maintained or increasing digital budgets imply a CxO outlook that it’s never too late to adapt.
Stripe is a financial infrastructure platform for businesses. Millions of companies—including financial organisations like Hargreaves Lansdown, Klarna, and AJ Bell—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet. Check out Stripe’s website to learn more, and contact sales when you’re ready to have a conversation.
This is a sponsored blog post by Nick Kerigan, Head of Innovation, Swift.
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.
This is a sponsored post by Paul Higgins, EMEA Banking Lead, Mendix, Silver Sponsors of FinovateEurope, March 22 – 23 in London.
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.
The digital economy is rapidly growing. With the pandemic accelerating the urgency for agility, adaptability and transformation, traditional business models are being disrupted. It’s estimated that over the next 10 years, 70% of new value created in the economy will be based on digitally-enabled platform business models.
Meanwhile, research regarding global GDP is forecasting that digitally transformed enterprises will reach 53.3 trillion USD by 2023, making them account for more than half of the overall nominal GDP. As the digital economy continues to revolutionize the way we do business, companies are looking to optimize their onboarding workflows for a seamless user experience while continuing to meet Know Your Customer, Anti-Money Laundering and other regulatory and fraud prevention requirements.
With blue ocean opportunities for global growth and prosperity on the horizon, it’s clear that digitally-enabled business models will soon reign supreme in the global economy.
Elevating identity programs with advanced orchestration
By next year, it’s estimated that 75% of organizations will be using a single vendor with strong identity orchestration capabilities for identity proofing and affirmation, which is up from less than 15% in 2021. At a time when securing digital identities is a greater challenge than ever before, this sharp increase in demand for all-in-one vendor solutions is a testament to the pains businesses and their customers are experiencing with current workflows.
Typically, most legacy identity and authentication solutions require companies to cobble together different technologies as their needs and regulations have evolved. As a result of this siloed approach, Frankensteined technology setups put a strain on businesses as they are costly and time-consuming to maintain while also requiring an immense amount of heavy lifting from customers.
Say hello to Trulioo GlobalGateway Orchestration
For the past 10 years, Trulioo, the global leader in identity verification, has been on a mission to build a leading end-to-end identity platform that will enable everyone, in every country, to participate in the digital economy in real-time.
As consumers increasingly interact and transact online, the demand for reliable and robust identity verification services and technology continues to surge.
With this in mind, it only made sense for Trulioo to partner with HelloFlow — an innovative no-code, drag-and-drop builder of client onboarding and monitoring digital workflows.
Through the recent acquisition of HelloFlow, Trulioo is able to bolster its position as a trusted global platform for verifying businesses and individuals while offering advanced orchestration with unmatched capabilities. With a best-in-class, intuitive workflow builder, it will be even easier for customers to customize and deploy its global identity API — Trulioo GlobalGateway.
Backed by advanced orchestration from Trulioo, businesses will be able to seamlessly create multi-product verification workflows and smooth onboarding experiences for their customers, all while keeping their data secure. By bringing together several aspects from the employee and customer journey, businesses can alleviate the pains that are often associated with:
Registrations and logins
Identity verification
Ongoing authentication
With the ability to verify identities, businesses and documents, GlobalGateway Orchestration will combine user onboarding and verification to make it easy to:
Build and launch workflows At the heart of GlobalGateway Orchestration, the flow builder will allow you to build an integrated workflow that connects verification solutions.
Monitor and optimize workflows GlobalGateway Orchestration allows for high-level monitoring and testing of workflows by providing in-depth performance metrics including verification rates, country data and even deeper case-by-case reviews of client data.
Are you ready to future-proof your business?
As your business grows and your needs evolve, it’s important to work with a company that can grow alongside you.
No matter the size of your business, where you’re located or where you’re looking to go, Trulioo has the customizability to get you there. With experience in multiple markets and multiple countries, Trulioo has a team of growth specialists ready to help you future-proof your business, this year and beyond.
To find out how your business can begin leveraging an identity verification platform that’s built for change, visit the Trulioo website or you can see them at FinovateEurope 2022 in booth #37.
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.
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 Michael Hom, Head of Financial Services Solutions, InterSystems. InterSystems areGold Sponsors of the upcoming FinovateEurope in London, March 22-23.
Last year was a record breaking for the global fintech sector, with investment reaching $102 billion – an annual increase of 183%. This growth was in large part spurred on by the pandemic which brought about major changes in consumer banking and spending habits, with eight in 10 people in the U.K. alone now using fintech products for banking and payments. At the same time, demand for fintech is also growing due to increased digitization among incumbent banks as these institutions try to keep pace with evolving customer demand for digital services and applications.
However, despite this growth, fintechs, much like more traditional financial services institutions, face a range of technical challenges which if not addressed could stall their progress. This was evidenced in recent research from InterSystems, which found that a staggering 81% of fintechs globally see data issues as their biggest technical challenge. Therefore, with data vital to everything from making informed decisions to delivering personalized services, addressing these challenges needs to be a priority for fintechs if they are to sustain the momentum of 2021.
The implications of fintechs’ data struggles
The data challenges being faced by fintechs fall under two distinct issues. Firstly, 41% of fintechs globally say they are unable to leverage data for analytics, machine learning (ML), and artificial intelligence (AI), while 40% of fintechs experience difficulties in connecting to customers’ applications and data systems. This indicates that not only are fintechs often unable to use their data effectively, but also they are struggling with data silos and integration.
These issues can have implications for fintechs such as hindering their ability to make informed decisions about the types of products and services they should be offering customers, and how they can continue to innovate to meet evolving customer needs. Additionally, for B2B fintechs in particular, integration challenges will make it more difficult to sell their applications to enterprise customers who need solutions that fit seamlessly within their existing infrastructure and that allow them to obtain the much-needed flow of bidirectional data.
On top of this, the data challenges cited by fintechs could hinder their ability to comply with financial regulations. Not only is this a concern from a regulatory standpoint, but it also may put the 93% of fintechs that hope to unlock the opportunities of partnering with incumbent banks at a disadvantage. After all, security and regulatory compliance are essential for banks and are key considerations when making decisions about which fintechs and firms to work with.
Time for a change of data architecture
Consequently, to build on the growth they have experienced over the last year and to be in the best position to capitalize on lucrative relationships with incumbent banks, fintechs globally must begin to address the problems with their data management. The starting point must be to find a way to bridge data silos and make integration easier.
Within the wider financial services sector, traditional firms, such as JPMorgan, Citi, and Goldman Sachs, are turning to data fabrics to solve these data challenges and provide a consistent, accurate, real-time view of data assets. A new architectural approach, data fabrics access, transform, and harmonize data from multiple sources on demand. By weaving together different data sets, from both within and outside the organization, and providing easy and uniform access to data, a smart data fabric can help fintechs to generate insights that can be used to get to know their customers better and gain complete visibility to accelerate business innovation.
This type of data architecture will also allow fintechs to create a bidirectional gateway between their applications and their enterprise customers’ production applications, legacy systems, and data silos. This approach will help those fintechs to ensure that their solutions can be quickly and easily integrated within their customers’ existing environments, which is particularly beneficial for fintechs looking to collaborate with banks.
‘Smart’ or enterprise data fabrics elevate this approach further by embedding a wide range of analytics capabilities, including data exploration, business intelligence, natural language processing, and ML directly within the fabric. This makes it faster and easier for organizations to gain new insights and power intelligent predictive and prescriptive services and applications.
As such, smart data fabrics address both the data integration challenges facing fintechs and their currently inability to use data with more advanced technologies such as AI and ML to extract valuable insights. As smart data fabrics allow existing legacy applications and data to remain in place, thereby removing the need to “rip-and-replace” any of their existing technology, this approach also enables fintechs to maximize their previous technology investments.
With so much potential within the global fintech sector, implementing a smart data fabric will allow fintechs to address their most pressing data challenges. They will have the ability to make more informed decisions based on accurate information and insights, deliver the products and services their customers need, and collaborate with other institutions. Ultimately, this will ensure fintechs are in the best possible position to make 2022 an even more successful year than the last.
This is a sponsored post by Cyvatar, Gold Sponsors of FinovateFall 2021. Written by Craig Goodwin & Corey White.
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.
[1] Baxter, Robbie Kellman. “The Membership Economy: Find Your Superusers, Master the Forever Transaction, and Build Recurring Revenue.” McGraw-Hill Education. 2015, p. 26.
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.
