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

This is a sponsored post in collaboration with InterSystems, Gold Sponsors of FinovateSpring, and Monica Summerville, head of capital markets, Celent, a division of Oliver Wyman.

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Financial institutions and data have had a love-hate relationship for many years.

On the one hand FIs and data are a match made in heaven. It is a symbiotic relationship where business functions create and consume data over and over until the result exceeds the sum of the parts. Ideally this partnering results in revenue or alpha-producing insights. On the other hand, siloed, unreliable or simply too much data creates frustration and risk as the business potential is teased, but ultimately unattainable as FIs struggle to extract value from their data (see figure 1).

Business use cases for leveraging data across financial services are plentiful, from management reporting, enterprise risk, liquidity and treasury management, and more recently, driving innovative customer experiences. More specifically within capital markets and banking, trends such as the embracing of multi-asset trading or the desire to simplify architectures have triggered a rethink of data approaches. There is also, now more than ever, the desire for cost savings – equally important to FIs whose margins are increasingly coming under pressure from increased regulation and competitive factors. Indeed, research by Oliver Wyman and Morgan Stanley found that the benefits from having clean, consistent, and automated data management could be a two-to-four percent reduction of infrastructure and control costs. When IT spend ranges into the billions of dollars, as is the case with larger FIs, every percentage point of savings is a big win.

No wonder then that cracking the data management challenge has long been considered the perfect marriage of technology achievement and business function. FIs have made repeated attempts and invested hundreds of millions of dollars through the years to get this right. From simple relational databases storing structured data, to data warehouses and more recently data lakes capable of holding all types of data, there has been no shortage of excitement that maybe (whisper it) this latest approach could be “the one.” Heartbreaks inevitably followed as the heady days of getting to know new technologies turn into frustrations and recriminations. A pristine data lake becomes a swamp.

The latest research by Celent discovered that leading FIs including Bank of America, Citi, Goldman Sachs, JP Morgan and RBC, to name a few, have lately been getting serious with a new data management approach called Smart Data Fabric. As these entities move from a process- to platform-driven organisation, their business focus has shifted to ensuring the best customer experience possible. This shift however requires mastering and leveraging data to generate insights at an enterprise level. The reality is that a history of disjointed business expansion common to financial services, means data is siloed across numerous platforms, tuned for very different use cases. There are multiple “single sources of truth,” and these vary depending on whose truth you are seeking.  

The right data management approach should empower FIs to become better versions of themselves, without fundamentally changing who they are. Unlike previous data management architectures, Smart Data Fabrics offer centralized access and a single unified view of data across the organization. Crucially, Data Fabrics do not require that copies of the data be created and stored outside its original location, so can offer a useful bridging solution between modern and legacy systems – the latter often holding the most business crucial data. In this way Data Fabrics can also avoid the creation of more data silos, which is especially important as FIs increasingly embrace cloud. A Data Fabric becomes “Smart” when it inherently supports advanced data analytics and aims to future-proof data management (see Figure 2).

Financial institutions, from asset managers to banks and brokers, have always known that they need to become smarter about data. Business end-users and clients are demanding better user experiences, targeted insights, and increased access to analytic capabilities which requires free access to accurate and harmonized data drawn from disparate sources across the entire enterprise. At the very core of modernization is the ability to innovate at scale, and this relies on freer access to data. Celent’s latest research report sponsored by InterSystems found that the business necessities and benefits of better data management is driving adoption of Smart Data Fabrics. This time it might just be for real. Read the full report here >>

This is a sponsored post by Quantum Metric, Gold Sponsors of FinovateSpring.

One of my favorite sayings about digital banking is that the largest branch in the world is now in your pocket.

The retail banking customer journey has become more complex than ever before. Each day, clients are moving between a number of devices, which means that banks need to find new ways to study, monitor, view, and study the cross-device journey, especially on mobile devices.

It goes without saying that, for traditional retail banks, Covid-19 accelerated the shift to digital. But in-person branch use was already declining before that.

The good news for retail banks? Current federal regulations mean that elements of the in-person experience will remain important, so branches aren’t disappearing entirely. In addition to finding ways to boost in-person engagement at branches, retail banks have the extra challenge of offering omnichannel digital experiences that are on par with those offered by the latest fintech startups, like Robinhood, as well as other household apps, such as Amazon, Airbnb, and Twitter.

The boom in fintech, and especially the rise of neobanks like Chime and Ally, means that more clients are choosing banks that don’t offer in-branch services, where customers get the typical one-on-one service from a teller. Popular peer-to-peer and peer-to-business payments services such as Venmo, PayPal, Square, and CashApp have put additional pressure on retail banks to offer standout mobile experiences.

As traditional banks look to remain competitive with fintech startups, they will need to offer digital experiences that streamline everyday banking processes. Clients want to open new accounts, apply for credit cards, and deposit mobile checks with as few clicks as possible, and directly from their mobile devices.

Fintech startups have a leg up on retail banks because they offer fewer services and leverage the most advanced cloud technology. Many retail banks are burdened by legacy platforms, outdated processes that slow things down, and poor alignment within the organization.

Many banking clients miss the benefits of in-person engagement, especially seeing a friendly face at their local banking branch. Retail banks can approximate the friendliness of in-person service by doubling down on their digital channels, which means offering applications with intuitive user interfaces and user experiences. Above all, people want simplicity, transparency, and speed.

Banks and other financial institutions have the added burden of navigating complex federal regulations. These institutions are responsible for safeguarding clients’ money and remaining compliant with both local and federal laws. A few small errors can not only break trust with clients, but lead to millions of dollars worth of fines.

As banks double down on digital channels, they need to introduce the perfect amount of user friction for tasks such as opening accounts, filling out loan applications, and transferring funds. One small click can lead to major problems or misplaced funds, so making clients re-enter passwords or confirm transactions can build major trust.

On the other hand, too many steps in a workflow leads to abandoned applications, lower conversion rates, and frustrated customers. Worse yet, clumsy designs and technical errors often make it impossible for clients to complete tasks without assistance from a call center. There will always be technical errors, and to solve this, banks can put clients in contact with agents by providing pop-ups that include a direct phone number or a chat window when a problem arises.

Once banks have the basics down, they can invest in hyper-personalization, which helps clients feel more connected to their products. Erica, Bank of America’s Voice Assistant, has helped revolutionize the mobile banking experience. The AI-powered chatbot helps clients answer pressing questions about their banking needs, making it easier for them to find answers for common questions.

As retail banks rebound from the Covid-19 pandemic, they will need to engage in data-driven design thinking to ensure that each digital product decision benefits clients. That is why we have built the Quantum Metric platform, which helps retail banking teams act with more agility. Our methodology, known as Continuous Product Design, helps teams from across an organization align on the product decisions that will have the greatest impact on customers and the business’s bottom line.

In today’s digital-first world, retail banks need to identify problems before they impact a large segment of users, as well as anticipate potential issues as before they happen. That’s why our platform offers real-time analytics and anomaly detection technology. Our platform can help digital teams at retail banks pinpoint a broken button that causes conversion rates to plummet, pinpoint fraudulent activity from bots (e.g., too many login attempts), and much more.

Once retail banking teams get a handle on their omnichannel experience, they can begin expanding into other services and offering additional resources, such as financial education resources. The move to digital provides ample opportunities for diversification. Now banks need to use data-driven design thinking to determine what’s next.

Learn more >

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Photo by Marvin Meyer on Unsplash

This is a sponsored post by Accusoft.

While 2020 made its mark on the financial industry by causing tremendous disruption, 2021 is shaping up to be a year remembered for transformation and adaptation. Companies are hard at work building new digital strategies that will help them to thrive in an increasingly volatile economy.

Fintech developers are taking up the challenge to meet the functionality and performance demands of the financial industry as firms embrace true digital transformation. Their ability to build applications that deliver new features and integrate new capabilities into legacy solutions will be critical for helping firms reshape existing technology infrastructures.

Top 5 Fintech Trends to Watch in 2021

1. Customer-First Solutions

With so many fintech applications to choose from, financial organizations must take the time to consider which solutions are best suited for the needs of their customers. Banks and investment firms once put their own needs at the center of their processes, but in an increasingly competitive marketplace, they have realized that providing a high-quality user experience is paramount to success. They can begin transforming processes by eliminating friction to allow customers to access the services and products they need more quickly.

Fintech developers can help them to eliminate manual processes, reduce external dependencies, and automate common tasks by designing unified digital solutions that address multiple challenges and streamline workflows. By integrating features like document viewing, file conversion, and form data capture into their applications, innovative developers are finding ways to strengthen the connection between firms and their customers.

2. Enhancing Digital Collaboration

In response to the COVID-19 pandemic, much of the financial industry has embraced remote work arrangements for the foreseeable future. The transition has created significant demand for digital tools that can facilitate effective and secure collaboration. Not only must physical documents be converted into digital form, but firms also need ways to make those files available to remote employees without threatening data security or causing version confusion.

Organizations frequently turn to a variety of incompatible software solutions and improvised workarounds to meet their viewing, editing, and document management needs rather than implementing a dedicated, all-in-one solution. Unfortunately, these ad hoc measures create inefficient third-party dependencies, expose data to unnecessary risk, and make human error more likely. Fintech developers can integrate these features into a single application through the use of SDKs and web-based APIs.

3. Managing Big Data

Financial services firms gather massive quantities of data on a regular basis. Although much of that data is unstructured and needs to be filtered through sophisticated algorithms to bring notable trends and risks to the forefront, the industry also collects a great deal of data from structured forms. Structured documents such as loan applications, tax filings, and financial statements all provide valuable data insights that organizations can use to make more informed strategic decisions.

Fintech applications with the ability to extract and process data from structured forms accurately is essential for improving the performance of powerful analytics tools deployed by today’s financial firms. Software integrations can further enhance fintech solutions with image cleanup, document alignment, and form recognition features that make the data collection process more efficient and accurate.

4. Disaster Mitigation

After seeing how the COVID-19 pandemic caused massive disruption to global markets and supply chains, financial organizations are reviewing the way they do business to reduce the impact of similar disasters in the future. One of the key steps in this process will be the rapid transition to paperless workflows and an expansion of electronic data capture capabilities to reduce the reliance upon manual processes.

Solutions that incorporate streamlined document viewing, file conversion capabilities, and data extraction tools will be essential to these “disaster proofing” efforts. By automating previously manual tasks, such as data entry, document assembly, and signature authentication, Fintech solutions can help financial companies protect their business processes from future disruptions.

5. Expanded Partnership Opportunities

Although traditional financial institutions like banks have been skeptical of many fintech solutions, the rapidly-changing market has caused them to reassess their technology in order to reach a new generation of customers. Collaboration between banks and innovative fintech startups was already on the rise before the pandemic reduced longstanding barriers to digital transformation. The challenge they now face is how to integrate their operations and data while also launching innovative services across multiple channels.

Fintech developers can streamline this process by building flexible software applications capable of handling a variety of file formats without the need for any burdensome third-party dependencies. In some cases, that may mean building entirely new solutions, while in others it might call for integrating additional features into firmly entrenched legacy applications. The fintech companies with the ability to get innovative software platforms to market more quickly will be able to make the most of their partnership opportunities.

Building Better FinTech Solutions with Accusoft

Accusoft’s diverse library of SDKs and APIs allows developers to easily integrate robust content processing, conversion, and automation capabilities into their solutions. Whether they’re using PrizmDoc Suite to give their web applications the ability to natively view, edit, and convert documents, extracting data from multiple form types with FormSuite for Structured Forms, or building image cleanup, OCR, and PDF annotation features into their on-prem applications with ImageGear, FinTech companies can trust Accusoft to help them overcome the challenges of 2021 and the years to come.

The below is a sponsored post, from Gold Sponsors of FinovateEurope Digital 2021, InterSystems.

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The COVID-19 crisis has thrown a spotlight on the inefficiencies underlying many functional areas of financial firms and caused executives to reevaluate operational resilience in light of increasing volumes and volatility. There’s been a lot of industry discussion about the potential of Machine Learning and Artificial Intelligence (AI) to tackle challenges ranging from regulatory change management to improving the client experience.

AI has huge potential to augment and transform current market practices, but organizations need to make sure they are laying the groundwork for successful implementation by considering the underlying data infrastructure required to turn these technology ambitions into reality.

In this white paper, Firebrand Research discusses how to tackle the complex issue of data management and shares key reasons to invest in a smart data fabric, including:

• Building the data foundation for next-generation initiatives
• Enabling a firm to adapt to volatile markets via real-time analytics
• Connecting and harmonizing data on demand from across a firm’s many silos
• Keeping firms out of the regulatory hot seat by ensuring high data quality
• Providing accurate and real-time insights and new innovative services to keep ahead of the competition

Read the full whitepaper here >>