Sponsored

How Fintechs Can Use Smart Data Fabrics to Achieve Record Growth

How Fintechs Can Use Smart Data Fabrics to Achieve Record Growth
By Charlie Burgess Posted on
Categories: Guest Post, InterSystems, Sponsored

This is a sponsored post, by Michael Hom, Head of Financial Services Solutions, InterSystems. InterSystems are Gold 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.

Photo by Min An from Pexels

Share this:

Send Post Twitter LinkedIn Facebook

Work From Home, Identity Crime, and the Two Biggest Threats to FIs in 2022

Work From Home, Identity Crime, and the Two Biggest Threats to FIs in 2022
By Charlie Burgess Posted on
Categories: Interview, List series

Finovate Research Analyst David Penn sat down with Simon Marchand, Chief Fraud Prevention Officer at Nuance to talk about the current state of financial crime, what banks are particularly worried about, and the benefits of using voice as a key biometric identifier in the authentication and verification process.

“What I focus on is making sure that Nuance’s voice biometrics technology can be applied very specifically to track down fraudsters. One of the main challenges when you try to stop any kind of fraud is finding the human beings that are pretending to be someone else. What we do is identify the human beings (which) allows fraud teams to find the fraudsters themselves and prevent fraud much more easily and much more effectively. I’m here to make sure that Nuance’s expertise is applied in the best possible ways to stop and prevent any kind of identity crimes.”

On the top concerns for financial institutions when it comes to identity crime in 2022.

“The first is that we’re still going to have a lot of employees working from home … If you’re working from home, you’re not only easier to manipulate and socially engineer from a fraudster’s perspective, but also you’re alone, unsupervised, and have access to a lot of very sensitive information. Banks are very concerned about how they can protect their customers privacy and personal information as effectively in a work from home environment as they would do in an in-person environment.”

“The other big threat is that fraudsters are quite significantly shifting to account takeovers and subscription frauds – very identity-focused crimes. They have adapted very, very rapidly during the pandemic and they have seen that it’s very profitable to focus on those specific attack vectors. They are moving away, especially in the U.S., from those card-not-present kinds of fraud, card skimming, and all these things that we have been fighting for a couple of years, and it looks as if 2021 is on track to be the worst year in the past 20 years when it comes to the number of identity theft victims in the U.S. So fraudsters are moving toward (the new crimes) and we need to move quickly if (we) want to make sure that we’re protecting our customers.”

Watch the full interview below.

Find out more about Nuance and the work they do >>

Photo by Shelby Waltz from Pexels

Share this:

Send Post Twitter LinkedIn Facebook

InterSystems and Unqork on Increasing Speed to Productivity and Making the Most of Data

InterSystems and Unqork on Increasing Speed to Productivity and Making the Most of Data
By Charlie Burgess Posted on
Categories: Finovate Webinar, InterSystems, Interview, Webinars

“Banks are recognizing that there is a wealth of data and predicative analytics that can be used to curb future risks, but it’s all about how easily their teams can get access to it.”

Christian Lewis, Client Director of Financial Services, Unqork and Joe Lichtenberg, Global Head of Product and Industry Marketing, InterSystems, join Finovate Analyst David Penn to discuss how to cut down on latency in getting information and data to the right people, how to help organizations become more agile, and how to accomplish both goals while using fewer development resources than you might expect.

Watch the full discussion below and find out more about the work InterSystems and Unqork do >>

Share this:

Send Post Twitter LinkedIn Facebook

How Netflix Is Saving Cybersecurity: Embracing the Membership Economy to Advance Innovation

How Netflix Is Saving Cybersecurity: Embracing the Membership Economy to Advance Innovation
By Charlie Burgess Posted on
Categories: Sponsored

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.

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.

[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.

Photo by Clay Banks on Unsplash

Share this:

Send Post Twitter LinkedIn Facebook

Data-Driven Decision-Making with InterSystems

Data-Driven Decision-Making with InterSystems
By Charlie Burgess Posted on
Categories: Sponsored

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.

Photo by Norbert Kundrak on Unsplash

Share this:

Send Post Twitter LinkedIn Facebook

Winning Top-of-Wallet with a Digital-First Strategy

Winning Top-of-Wallet with a Digital-First Strategy
By David Penn Posted on
Categories: Fiserv, Sponsored

This is a sponsored post in collaboration with Amanda Glincher, Director of Marketing, Fiserv

It’s no surprise that a digitally issued card shortens the time frame between when a consumer receives a new card and when they begin using it for spend. Yet, digital issuance is just one step on a digital-first journey and without a full strategy, that newly issued card might not bring with it the added spend issuers are expecting.

Yes, consumers want digital-first cards, but they are also in search of digital-first options when it comes to all of their other banking activities. From the first engagement someone has with a new financial institution, each traditional activity should have a digital counterpart.

Applications that win

The beginning of a banking relationship often begins with a consumer applying for an account. Creating an application process that is seamless and reduces barriers is the best way to start the cardholder’s digital experience. As noted in The Financial Brand, when an application takes more than five minutes to complete, abandonment rates increase to as high as 60%. To reduce abandonment and improve the customer experience, applications can be limited to the necessary data.

Add to the convenience by allowing applicants to switch between devices to complete an application without losing their place in the application flow, especially in situations where any documentation or uploads are being requested.

Immediate access

Once you’ve approved a new account, increase usage rates by providing immediate access to a new card. In a world where our groceries are delivered within the hour and the world’s library of movies and music is available to stream in seconds, time really is of the essence with today’s consumer.

70% of digitally issued cards are used within five days, compared to a physical card that won’t even be delivered for 7-10 business days.

Make usage a breeze

“Manually entering my card details and verifying my identity is so fun” is a statement that has never been uttered. Once a card has been digitally issued, make using the card simple by enabling push-to-wallet. There are many benefits to giving cardholders this ability and it is among the most essential parts of a successful digital-first strategy. In addition to the seamless experience for the cardholder, push-to-wallet provides more opportunity for you to capture top-of-wallet for both the physical and digital wallet, as well as bypassing the marketing of competing cards.

Top-of-wallet opportunity

When a card is pushed directly into a Google or Apple Wallet from your app, it provides immediate access and the ability to spend in-person, online, and in-app. With over 85% of U.S. retailers accepting Apply Pay, a digitally issued card that is pushed to wallet is available for use nearly everywhere.

In addition to the availability of the card, the ease-of-use enables consumers to go about their regular spending and utilize your card without missing a beat.

Bypassing the competition

While push-to-wallet is the more convenient way to add a card for a consumer, it’s also the simplest way for an issuer to avoid competition. A customer who chooses to manually add a card to Apple Wallet will be greeted by an offer to apply for an Apple Card. When a card is directly provisioned to a digital wallet, the cardholder bypasses the manual entry point at which they would be offered another product.

Sweetening the deal with offers and rewards

A list of retail discounts, benefits pamphlets, and APR offer checks are among the many mailings we receive from financial institutions. These offers are more accessible and beneficial to digitally savvy cardholders when they are offered, visible, and available in-app.

Not only is this a preferred way for customers to access offers, but a digital-first model allows financial institutions to make personalized offers in the moment – special financing opportunities and location-based discounts – enhancing the cardholder experience and capturing even more spend.

Give insight into all the places a card is stored

For existing cardholders, instant issuance of a replacement card can be made even more valuable by providing information on all the places the old card was stored. A list of existing retailers where their card is on file or is being used for recurring purchases allows cardholders to make sure the card is updated everywhere it needs to be – providing a smoother journey with uninterrupted spend.

Control in the palm of their hands

While card controls and alerts are a standard today, they are also an essential part of a digital journey. Allowing individuals to set limits on transaction types, locations, and amounts – and receive alerts – reduces fraud, minimizes inbound call center activity, and gives cardholders the security of managing their cards 24 hours a day. Controls can include the ability to turn cards on and off, set spending limits, create location boundaries, and report a missing card. Alerts allow cardholders to create notifications for a variety of scenarios, and to keep a close eye on the transactions charged to their account.

The importance of a fully digital journey

While all of these features are beneficial on their own, it is when they come together as part of a full digital strategy that they provide the most value to both the cardholder and the financial institution. Digital issuance is a key part of going digital-first, but it is the combination of this suite of digital-first tools that provide the best cardholder experience.

Photo by Jahangeer Bm from Pexels

Share this:

Send Post Twitter LinkedIn Facebook

How Smart Data Drives Agility in Financial Services

How Smart Data Drives Agility in Financial Services
By Charlie Burgess Posted on
Categories: InterSystems, Sponsored

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

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.

Photo by The Lazy Artist Gallery from Pexels

Share this:

Send Post Twitter LinkedIn Facebook

Preparing For the Unprecedented: How Lenders Can Effectively Manage Commercial Credit Risk in an Ever-Changing World

Preparing For the Unprecedented: How Lenders Can Effectively Manage Commercial Credit Risk in an Ever-Changing World
By Charlie Burgess Posted on
Categories: Sponsored

This is a sponsored post in collaboration with Sean Hunter, CIO at OakNorth

When it comes to commercial lending, banks rely on risk models to make decisions. These models have been built up internally over decades of lending across thousands, if not tens of thousands of loans, but COVID-19 has exposed unexpected flaws in them. As a result, lenders are re-assessing how best to manage commercial credit risk in the future when other unprecedented events will inevitably occur.

Challenges

The first challenge is that traditional risk models are based on historical data, but in a rapidly changing world, extrapolating from the past is an approach that is no longer fit for purpose. Events such as trade wars, pandemics, natural disasters, and climate change are by their very nature situations that are hard to predict or plan for. We can make assumptions based on what we have seen with similar crises in the past, but no two are the same. Therefore, any data needs to be supplemented with a forward-looking view, which takes into account future challenges that may arise and that provides the much-needed foresight to make more informed credit decisions.

The second challenge is that most banks’ risk models tend to lump all businesses into one of a dozen or so categories – all restaurants, bars and hotels for example, are classified as “hospitality”. This disregards the fundamental differences in how these businesses operate, and makes it harder for lenders to identify the most vulnerable businesses in their portfolio. The experience of a pizza delivery / takeaway chain in New York City throughout the pandemic will have been very different to a Michelin-star fine dining restaurant in The Hamptons for example. Under lockdown, the Michelin-star fine dining restaurant is unlikely to have experienced any business, whereas the pizza chain may have seen an increase in trade as people were spending more time at home. When lockdown eases, however, and restaurants are allowed to reopen (but with strict social-distancing and cleaning measures in place), the situation could be quite different. The formerly empty Michelin-star fine dining restaurant may experience a surge in reservations as many diners would have saved money from a lack of socializing for several months, and look to make their first meal out “special.” Meanwhile, the pizza chain may see demand for deliveries shrink as people rush to enjoy the outdoors and take advantage of their freedom. 

In a fast-changing world, a timely change of course informed by insight and foresight is much preferred to 20/20 hindsight when it’s too late to avoid a problem.

– Sean Hunter, CIO at OakNorth

Unprecedented events such as the pandemic can also lead to structural changes which have permanent or long-term implications for the sector. Take a paper and board packaging business for example – during the pandemic, it will likely have seen revenue from paper sales decrease as businesses moved to remote work and instituted digital solutions such as DocuSign. However, on its balance sheet, year-on-year sales for the entire business in 2020 may not seem too different than in 2019. This is because the decrease in demand for paper has been offset by an increase in demand for cardboard as people under lockdown shop online and order items to their home. While the move away from heavy paper use is likely a permanent change from the pandemic, the increase in online shopping is unlikely to stay at peak pandemic levels once people are able to return to in-store shopping. Therefore, if the business fast forwards six to 12 months, it could see a decrease in revenue that it hadn’t been expecting and therefore, hadn’t planned for.

In this example, the lender, armed with this data, can take an informed, consultative role and share this analysis with the borrower, suggesting that they think carefully about any changes that will add to their cost base. Equally, the business’ management team can now be better prepared for changes further down the line. In a fast-changing world, a timely change of course informed by insight and foresight is much preferred to 20/20 hindsight when it’s too late to avoid a problem.

The third and final challenge is that traditional risk models don’t take into account how quickly the situation changes day to day. The approach taken by the Trump administration to address the impact of climate change for example, were completely different to the steps being taken by the Biden administration. Lenders therefore need the ability to re-run analyses and stress test on an ongoing basis in order to determine how governmental or socio-economic changes are impacting their loan book.

Solutions

At OakNorth, we’ve created the ON Credit Intelligence Suite to enable banks to lend smarter, lend faster and lend more to businesses. In order to ensure lenders can obtain an incredibly granular, bottom-up view of every business in their portfolio, we’ve split the economy into 262 different sub-sectors. The software is made up of three components:

  • ON Credit Analysis: which provides lenders with a 360-degree view of borrowers with instant financial forecasting, sector insights and peer analysis.
  • ON Portfolio Monitoring: which enables lenders to easily track sub-sector industry trends and set early warning alerts for potential covenant breaches.
  • ON Portfolio Insights: enables lenders to instantly segment their portfolio and rate loans based on level of vulnerability.

Find out more and join the upcoming webinar with OakNorth to dive deeper into this topic, featuring Jeremiah Norton, former FDIC; Bruce Richards, former Federal Reserve Bank of New York; and Mark Levonian, former OCC. Register now >>

Share this:

Send Post Twitter LinkedIn Facebook

Is Smart Data Fabric the Approach Financial Institutions Have Been Dreaming About?

Is Smart Data Fabric the Approach Financial Institutions Have Been Dreaming About?
By Charlie Burgess Posted on
Categories: Sponsored

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.

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 >>

Share this:

Send Post Twitter LinkedIn Facebook

Fast Money: The Innovation Race Between Established and Upstart Financial Services Firms

Fast Money: The Innovation Race Between Established and Upstart Financial Services Firms
By Charlie Burgess Posted on
Categories: Sponsored
Runner crossing finishing line on track

This is a sponsored post from Michael Hom, Global Head of Financial Services Solutions, InterSystems, Gold Sponsors of FinovateSpring.

The banking and finance industry has always been capable of adapting. But as the world recovers from the pandemic, banking and financial services face a new disruption from fintechs and “neobanks.” With lower cost bases and a very different, technology-driven approach to customer experience, these newcomers have been developing fast.  

The financial services sector has also experienced a massive rise in digital banking usage caused by the Coronavirus pandemic. For institutions with healthy infrastructure, this was a big positive, whether it was in high net worth advisory or remote banking. It also showed the centrality of high-quality digital user experience to today’s customers.

We must not assume, however, that all is well on the disruptor/innovator side. Some internet-only banks were laying off staff during the pandemic because their ramp-up costs are high – and their paying customer bases are still growing. They also have market share and profit margin challenges through stiff competition from other fintechs.

Established finance institutions, on the other hand, have huge numbers of customers and significant revenue streams. Their challenge: to innovate and make their legacy systems and data management strategies swift enough to keep up with their new upstart challengers. These legacy systems and problems with data management have hampered innovation.

The challenger banks and fintechs, by contrast, are far more agile: they have perhaps two-thirds lower technology costs and offer the interfaces and functionality younger consumers and companies want. They also have investors who support them. Yet they don’t have the scale of the big banks, nor the data. In banking, success is all about scale and achieving it is not easy. Each side also has different cost-pressures. While the fintechs concentrate on the cost of getting a new customer through the door, banking industry incumbents want to be more efficient and reduce the cost of execution.

How the industry will evolve

Large banks know if they get the connection right with consumers and corporations, they will be in a much better position in the next five or ten years. To do this, however, they need the fintechs’ agility. They must simplify their data management so they can adapt to changes in demand rapidly and scale as workloads increase. They must be capable of building and deploying data-intensive AI applications faster so they can transform the user experience for consumers. There needs to be a wider recognition that simpler approaches can be highly effective.

Fintechs and neobanks, on the other hand, need a compelling value proposition to attract consumers and generate meaningful revenues.

This is why the incumbents and the fintechs will draw closer through collaboration or acquisition. By collaborating with incumbents, fintechs and neobanks can use their digital skills and innovation to make niche areas of the established institutions’ operations far more profitable while benefiting from access to a massive customer base it would otherwise take them years to acquire.

Modern data management technology such as microservices, APIs and API management, have lowered barriers to publish and consume services, creating a dynamic ecosystem that allows organizations to focus on their core competencies and differentiation. They can rely on the ecosystem for commoditized, non-core, and non-differentiating capabilities.

Acquisition, on the other hand, brings its own problems, since the pace of innovation often slows once a young organization has been bought by an established competitor.

For these reasons, we may see a hybrid model between collaboration and acquisition, in which the big incumbents develop through consolidation into aggregators, becoming open banking marketplaces and acting as the nexus between customers and services. A new digital retail bank may, for example, use a major player’s credit expertise, risk and control mechanisms while designing a new user experience from scratch.

Whichever model of cooperation it is, the new offerings devised together by incumbents and fintechs will have to stand out. With so much competition, differentiation through excellence in technology, customer experience and support will be essential.

What does the future require?

Agility is vital to the future of banking and should be a major aim for all ambitious financial organizations. Mindsets must change as well as technology.

From now on, senior management in banks must think like their counterparts at software companies. That means constantly gleaning what is going well or wrong and acting on it. When there are problems, they should be fixed before customers are fully aware. Many neobanks are leading the way on this, updating their apps weekly. Big banks, by contrast, are much slower, updating apps yearly or quarterly, with a few in the four-to-six week timeframe. This has to change.

When deciding how to transform, incumbent organizations must ask themselves how they are addressing client and employee needs in terms of products, services, and information. They must build a picture of where banking is going and be confident they are heading in the same direction. Established banks must become product-oriented organizations just like digital native rivals, abolishing internal boundaries and creating cross-functional teams under product owners.

Keep the organizational DNA alive

Scale, innovation, and agility have become vital attributes in banking. Yet as incumbent institutions adapt and assess which newcomers to partner with or acquire, it is essential they do not lose sight of what it is that makes them special or forget what their goal is. Banks are still about people, processes, and technology, and the people side of the business is where high levels of service and distinctiveness enable the organization to stand out and build profitable long-term relationships.

If organizations lose their DNA, they will crumble. Incumbent banks have a larger and more diverse customer base that is difficult to please and, in today’s world, less likely to tolerate low levels of service from loss of organizational focus.

Established banks must be as nimble as possible and collectively approach their work as if their business model is at risk every day. It is not only digital transformation that is necessary, but also a mental mind-shift. Only then can banks believe they are on the path to digital transformation, resilience, and long-term profitability.

Find out more about the future of financial services and why the ability to see around corners will offer the most advantage in this webinar hosted by The Economist and sponsored by InterSystems >>

Share this:

Send Post Twitter LinkedIn Facebook

The Future of Banking in a Digital-First World

The Future of Banking in a Digital-First World
By Charlie Burgess Posted on
Categories: Sponsored

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 >

Photo by Marvin Meyer on Unsplash

Share this:

Send Post Twitter LinkedIn Facebook

The Evolving Role of the CDO at Financial Organizations

The Evolving Role of the CDO at Financial Organizations
By Charlie Burgess Posted on
Categories: Sponsored

This is a sponsored post from InterSystems

Over the past several years, the role of the chief data officer (CDO) has evolved from being security-and compliance-oriented to being strategic and innovative. Not only are chief data executives of all stripes taking on a more progressive role in key business decisions, but the position itself is becoming an essential staple of forward-thinking organizations, especially at financial services organizations. According to a 2019 study conducted by Forrester, 58% of organizations had appointed a chief data officer and another 26% were planning to do so.

Moving forward, data executives must focus not only on securing data and ensuring their organizations meet rigorous data regulations but also on new strategies for leveraging Big Data and their organizations’ proprietary data to generate business value. This will require new strategies in data management, as well as the deployment of new data solutions like data fabrics, automated governance, machine learning, and blockchain.

Primarily, it will require data leaders to focus more on offensive data management—a data strategy that supports key business objectives, such as boosting profitability and improving customer outcomes—in addition to defensive data management, which refers to the strategy of securing data and maintaining compliance with regulations.

Read Intersystems’ latest report on The Evolving Role of the CDO at financial organization, which provides benchmarking information about how CDOs are fairing in a rapidly shifting regulatory landscape and exploration of CDOs’ and other data professionals’ opinions on enabling an offensive approach to data management and their best practices.

Read now >>

Photo by Tobias Fischer on Unsplash

Share this:

Send Post Twitter LinkedIn Facebook