This is a sponsored post from Tim FitzGerald, EMEA Financial Services Sales Manager, InterSystems.

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Innovation undoubtably will help firms keep up with market volatility, changing customer demands, and the competition – not just today, but in the future. This is reflected in the thoughts of financial services leaders themselves as almost three-quarters (73%) believe innovation is vital to their survival as a business. Yet, despite widespread recognition of the critical nature of innovation, financial services firms are facing difficulties in successfully executing their innovation initiatives.

In particular, firms cite skills gaps and integrating disparate data sets as significant barriers to innovation. With the uncertainty and upheaval of the last few years showing no signs of slowing down as we head into 2023, finding ways to better leverage their people and data to further innovation, therefore, must be front of mind.

Obtaining a 360-degree view

Data has a vital role to play in innovation initiatives. Being able to access and use accurate, real-time data from all business units to obtain a holistic 360-degree view of the enterprise and its customers will enable firms to better identify and respond to growth opportunities, address challenges in an agile manner, and make more informed, in the moment decisions. This requires firms to address the data integration challenges they are currently facing and connect their myriad data and application silos.

One way of doing this is by adopting a smart data fabric which accesses, transforms, and harmonizes data from multiple sources, on demand, to make it usable and actionable for a wide variety of business applications. Ideal for complex data environments, the smart data fabric eliminates delays which lead to errors, missed opportunities, and decisions based on stale or incomplete data.

This approach allows existing legacy applications and data to remain in place, thereby enabling firms to maximize the value from their previous technology investments, including existing data lakes and data warehouses, without having to “rip-and-replace” any of their existing technology.

By obtaining this instant insight into their organization and customers, financial services firms will be able to make better, more accurate decisions to drive innovation, improve customer experiences, and get ahead of the curve.

Power to the people

Implementing new technology alone is not enough to help firms overcome the barriers that are currently standing in the way of successful innovation. People also have a significant part to play in innovation initiatives, so giving them the capabilities to conquer current skills gaps and to use data effectively to drive innovation are also key. Firms can achieve this by implementing a holistic innovation strategy which brings together all the critical elements required for successful innovation – people, processes, and technology – and identifies how to empower business users with data.

By putting data directly into the hands of business users, firms will be able to mitigate some of the impacts of skills gaps and help people to actively contribute to innovation initiatives. Self-service analytics capabilities embedded within smart data fabrics will provide immense value here. These capabilities will enable business users to freely explore the data, ask ad hoc questions, and drill down via additional queries based on initial findings.

In doing so, not only will firms be able to leverage their data more fully, but also they will be able to mitigate the impact of skills gaps by empowering employees to read and interpret data and make the data-driven decisions needed for successful innovation. This also will reduce reliance on IT teams to surface and interpret data, while avoiding the need for business users to learn a whole host of new skills and tools.

New year, new approach

As firms look to 2023, likely with a mix of excitement and trepidation about what the year may bring, ensuring they address the barriers currently standing in the way of innovation success is essential to help them respond to whatever comes next. By addressing issues with data integration and skills gaps head on, financial services organizations will be able to make more effective use of both their data and people to drive forward innovation initiatives.

Arming themselves with a clear innovation strategy and a team of empowered and data-enabled employees will give firms the capabilities overcome any challenges that may arise, but also critically, to grow their offering, future-proof their organization, and meet changing customer demand. Ultimately, adopting this approach will help firms to set themselves up for long-term innovation success, not just for 2023, but beyond.

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This is a sponsored post by Tim FitzGerald, EMEA Financial Services Sales Manager, InterSystems, Gold Sponsors of FinovateFall 2022.

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In today’s fast-moving landscape, financial services firms are under increasing pressure to remain competitive and generate more revenue by developing new products and services faster, while still leveraging their existing resources.

In recent years, this has seen many financial services organisations turn to external fintech solutions to help accelerate innovation and quickly obtain new digital capabilities. And so, fintech partnerships have become critical components of financial institutions’ growth strategies, rather than the technology experiments they started out as.

To ensure innovation success, it’s vital that financial services organizations can easily leverage and provision new fintech services and applications by seamlessly integrating with their existing production applications and data sources. But the true value and potential of fintech solutions can’t be unleashed until integration is quick and easy.

As many firms will attest, arduous and costly integration can see the value of such initiatives dwindle before their very eyes – sometimes to be lost altogether. Common challenges can range from unforeseen issues tying up precious IT resources, to costs spiraling out of control and timescales sliding drastically from what was planned or what is desirable. Ultimately, these delays can result in the loss of any competitive edge as rivals launch similar solutions much faster.

Ensuring successful integration

Fintechs have become increasingly attractive as they incorporate the latest technologies, modern application methodologies, and deployment platforms. However, for banks to make effective use of these opportunities, those technologies need to be woven into its existing infrastructure, much of which is likely to be based on legacy technology.

Consequently, successful integration requires an understanding of the intricacies and idiosyncrasies of those legacy systems. It also demands knowledge of the underlying data architecture and how to connect the new technology to systems that weren’t built to be connected to in such a way. While this isn’t an unsurmountable problem, getting it right will take resources, budget, and time.

Careful consideration is also needed when undertaking the integration to ensure that the resulting architecture doesn’t become overly complex. After all, if it comprises multiple technology layers from different vendors, all with differing versions and releases, any future change could impede the bank’s ability to take advantage of the benefits they set out to achieve.

Next will be to determine how data from existing systems will be fed into the new system and in what format. To get around this, it’s all too easy to layer extraction tools upon a myriad of other tools, including transformation tools, data lineage, master data management, databases, and data lake technologies. However, what firms are then left with is a multi-headed monster that no one person truly understands. This approach to data integration is also complex and costly to design, deploy, manage, and maintain. Fortunately, adopting a smart data fabric approach, a next generation architecture, can provide a way for financial services organizations to overcome these challenges.  

Achieving bidirectional connectivity

By leveraging a smart data fabric, it is possible for institutions to connect and collect real-time event data and obtain unmatched integration capabilities using just one holistic platform. This approach eliminates the complexity and inefficiencies of manual integrations and other legacy approaches to integration and enables firms to integrate applications faster and more efficiently. It does this by essentially creating a dynamic real-time, bidirectional gateway between cloud-based fintech applications and their own production applications and data assets.

The smart data fabric integrates real-time event and transactional data, along with historical and other data from the large number of different back-end systems in use by financial services organizations. It transforms the data into a common, harmonized format to feed cloud fintech applications on demand, thus providing seamless, real-time, bidirectional connectivity and integration with the bank’s existing legacy enterprise data, production applications, and data sources.

Not only does this help firms to realize faster time to value and achieve simpler implementation that is easier to maintain, but it also gives financial services institutions the agility needed to innovate faster and keep critical initiatives on track. Additionally, it helps to futureproof their architecture by making it easier to incorporate any fintech applications and technologies available in the marketplace, thereby empowering them to react to new opportunities and changes in their environments.

Ultimately, there is immense value to be unlocked from fintech solutions and applications. However, that is only possible through swift and simple integration. By implementing a smart data fabric-enabled data gateway, financial services organizations can quickly and easily integrate new solutions within their existing infrastructure to ensure they are able to keep pace in a rapidly evolving landscape.  

This is a sponsored post by Ann Kuelzow, Global Head of Financial Services at InterSystems.

A staggering 86% of financial services firms globally are concerned about using data to drive decision-making within their organizations, according to the latest research from InterSystems of 554 business leaders within financial services companies, including commercial, investment, and retail banks, across 12 countries globally. This lack of confidence largely stems from an inability to access data from all the needed sources and the time taken to access data. Given the wealth of data financial services firms have, this is a major concern, with the potential to open organizations up to risk and severely impede key business initiatives. In fact, more than a third of firms in the survey cite the primary impact of these challenges as being difficulty in gaining a 360-degree picture of customers.

As competition intensifies within the financial services sector, customer 360 is something that all firms must confidently be able to obtain. Doing so will empower firms to provide clients with the products, services, and hyper-personalized, real-time experiences they have come to expect across all aspects of their lives. But this relies on gaining access to accurate, consistent, and real-time data encompassing all touchpoints. Consequently, firms must first address underlying issues with their data architecture.

Solving data challenges

Gaining a holistic view of the customer requires firms to pull together all available information on each customer. As customers are likely to interact with a variety of different departments and personnel within the firm, this information can be spread across multiple systems and silos, including trading, savings, credit cards, loans, insurance, CRM, support, data warehouses, data lakes, and other applications and silos, as well as data from external sources and suppliers. The data is often in dissimilar structures and formats and follows different naming conventions and metadata. Therefore, making sense of this dispersed data typically requires significant effort and expense, and using it to make informed, accurate, and fast decisions is a major challenge.

As organizations look to solve these problems, data fabrics, a next-generation architectural approach, have emerged to provide financial services firms with a way to speed and simplify access to data assets across the entire organization. It does this by connecting to existing systems and data silos containing relevant data, both inside and outside the organization, and ingesting the relevant data on demand as it’s needed. It accesses, integrates, and transforms the data as it’s being requested, providing a real-time, consistent, harmonized view of the data from different sources, all from a single view. This allows firms to gain a complete 360-degree view of the customer.

Going a step further

A smart data fabric takes this approach a step further by providing built-in analytics capabilities which enable business users to understand customer behaviors and actions better and even to predict the likelihood of future behaviors, such as purchase of new services, churn, or response to targeted offers. It also provides the business with self-service analytics capabilities, so line-of-business personnel can drill into the data for answers without relying on IT, eliminating the usual delays associated with adding custom requests to the IT department’s queue.

This next generation approach also helps solve latency issues, as smart data fabrics lets the data reside in the source systems, where it’s accessed on demand, as it’s required.

Adopting this approach will help to restore firms’ trust in their data, ensuring that they can quickly access consistent, reliable, and accurate information on which to base decisions, fuel data initiatives, and build up a comprehensive view of the customer.

Elevating the customer experience

Being able to leverage the wealth of customer data inside and outside of the organization for customer 360 will empower firms to offer a vastly improved customer experience. For instance, with a single view of the customer, advisors, help desk, and support teams will be able to provide customers with the immediate answers and recommendations and thereby enhance their interactions with the organization.

Armed with customer 360, firms will also be able to increase revenue streams by predicting customer behavior to maximize cross-sell and up-sell opportunities. For example, incorporating and analyzing dozens of data points from different systems enables firms to determine which customers are likely to respond to a premium credit card offer and least likely to default on payments. This allows firms to identify which customers to target with particular offerings and services.  Similarly, firms will be able to predict which customers are at risk of churning and take appropriate corrective actions in advance to reduce churn.

Together, these capabilities will help to elevate the experience and services being offered to customers, while also helping financial services firms to create and cement a competitive edge.

Restoring trust in data

Ultimately, by adopting smart data fabrics, firms will be able to overcome the data challenges that are currently preventing them from using their data to make better decisions by leveraging a more complete and more current 360-degree view of each and every customer. With a complete and trusted 360-degree view of the customer, firms will be in a strong position to fuel new customer initiatives, enhance the customer experience by delivering cohesive and personalized interactions and offerings across departments, and set their institution apart.

Find out more, and read the full InterSystems here >>

This is a sponsored post by InterSystems, Gold sponsors of FinovateSpring 2022.

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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.

Download the Report and Empower Your Business with Data

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.

This is a sponsored post in collaboration with InterSystems, Gold Sponsors of FinovateFall

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Delivering reliable, clean, timely data into the hands of decision makers is vital for financial institutions. While this has been true for quite some time, data is becoming more important than ever. The events of the past year have irrevocably demonstrated this point, with financial intuitions realizing just how powerful accurate data is when it comes to making pivotal decisions.

Adding to this complexity is the explosion in the amount of data we’re creating. You only need to revisit this mind-bending stat from TechJury to realize just how much we’re producing: “1.7MB of data (was) created every second by every person during 2020. In the last two years alone, an astonishing 90% of the world’s data has been created. 2.5 quintillion bytes of data are produced by humans every day.”

What does this increased focus on data mean for financial institutions?

1. The cost of managing data is only going to increase: The amount of data is growing, and with that comes growing costs associated with accessing, ingesting, processing, and storing that information. More data means more throughput and more storage, both of which you’ll pay for. And if you haven’t got systems in place to handle the increase in throughput, you’re going to experience delays. This can not only cause reputational damage, but can also have regulatory and compliance impacts if you don’t have appropriate systems in place to meet your obligations.
2. It’s becoming harder to compete with emerging players: There’s certainly a benefit to having an established business in that you’ve got insights at scale. With that comes the weight of managing legacy systems and architecture. The more information we pour into our systems, the harder we have to work to be agile.
3. Customers now expect smart insights: We’re all driven by the technology that powers our lives. And today’s customers expect financial institutions to mirror the intelligent insights that our smart watches and apps deliver to us. There’s a growing expectation that if our watches can tell us the how we can improve our health through personalized exercise goals, sleep reminders, and mindfulness breaks, then surely our banks can tell us how and when to optimize our portfolios, how to increase savings, or how to maximize lines of credit.
4. Data is essential for people to do their job: In the workplace there’s an expectation, particularly among those coming out of business school, that people will have access to the information they need to do their jobs. Data has become an integral part of doing business. We are rapidly moving beyond just making sure we have the data, and it’s now more about how reliable and accessible it is that makes the difference to employees.

Beyond breaking silos

There are many views on how organizations can improve movement and quality of information. However, some of these approaches can create their own issues.

Financial institutions need to move beyond breaking silos and focus on timely, clean, quality, solutions around data catalogues. This will allow them to map out the entire data needs of the organization. In short, they need to consider the connectivity of their information — how their data can be shared seamlessly across the whole data ecosystem. It’s what we refer to as “data fabric”.

What is data fabric?

Data fabric is an architecture and set of data services that provide consistent capabilities across a choice of endpoints spanning multiple on-premises and cloud environments. Gartner describes it as “frictionless access and sharing of data in a distributed network environment.”

How smart data fabric is driving agility in financial services

Implementing a smart data fabric allows financial institutions to make better use of their existing architecture because it allows their existing applications and data to remain in place. It then integrates, harmonizes and analyses the data in flight and on-demand to meet a variety of business objectives.

Having a smart data fabric allows financial institutions to remain agile in a number of ways:

Allows businesses to make smarter decisions faster

Banking is seeing new market entrants like gaming companies, retailers, transports and telcos, all clambering to get in on the financial services game. A well-constructed data fabric empowers executives and lines of business to monitor and anticipate changes, both positive and negative, in internal and external environments.

Helps identify new segment opportunities

One of our customers anticipated the impact of distressed debt amongst their credit card consumers and utilized their data fabric to proactively contact potentially affected clients. By offering extended payment terms they fostered stronger customer loyalty and mitigated a potentially large bad debt situation. This same process of customer segmentation can be used to identify new market opportunities.

Enhances customer experience

A smart data fabric allows faster processing of clean reliable data which financial institutions can use to share insights with their customers. By sharing these insights, financial institutions can foster loyalty and drive spend in a highly competitive environment.

Drives efficiency and cost savings

Finally, making decisions based on timely, accurate data allows financial institutions to reap all the benefits just described. Without the certainty that comes with reliable data, none of these decisions can be made efficiently or cost-effectively because the time and effort associated with managing data simply outweighs the benefits.

Leading financial services organizations are leveraging smart data fabrics to power a wide variety of mission-critical initiatives, from scenario planning, to modelling enterprise risk and liquidity, regulatory compliance, and wealth management.

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Photo by The Lazy Artist Gallery from Pexels