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How Capital Markets Firms Can Mitigate Risk in Periods of Uncertainty

How Capital Markets Firms Can Mitigate Risk in Periods of Uncertainty
By Charlie Burgess Posted on
Categories: Sponsored

The following is a sponsored post from Michael Hom, Head of Financial Solutions at InterSystems, Gold Sponsors of FinovateFall Digital 2020, September 14 through 18, 2020.

Currently, external factors like the COVID-19 pandemic mean that the global economy has become increasingly volatile and capital markets firms are having to work harder than ever to make sure users, both retail and institutional, can continue to trade without interruption.

As these financial organizations look to mitigate risk in this period of uncertainty, gaining operational resilience, implementing risk mitigation strategies, and having the right technology in place will be crucial to continue to deliver value to customers, comply with regulations, get ahead of the competition – and, most importantly, maintain trust.

Given this, the pressure for incumbents to upgrade infrastructure is only increasing, but challenges remain in doing so. While the pandemic may have been the linchpin for organizations to start embracing new technologies there are still barriers to overcome and best practices to be put into play to not only mitigate risk, but also prepare capital markets for what’s to come in the future:

Replacing legacy technology

Critical to mitigating risk is ensuring data is available quickly and easily accessible. For many capital markets firms this is an area where they struggle due to a significant amount of legacy technology in their infrastructure and, consequently, data siloes.

Connecting these disparate systems will be vital to not only help them with performance issues they have today, adapting to situations such as mass remote working, for example, but also so they are capable of growing with them into the future.

This requires them to adopt solutions that can seamlessly run, scale, and expand into the cloud. By replacing legacy infrastructure, they will have the benefit of providing new technologies and innovations access to their wealth of valuable data.

These solutions should also be location agnostic to allow capital markets firms to be agile and take advantage of new technology and services and bring that into their existing infrastructure.

Investment in the future

As these institutions look to replace their legacy technology, they should focus their investments on two key areas.

First, they should invest in platform scalability as being able to scale up as the market spikes is crucial and can be a major differentiator. This scalability can even give firms a competitive edge with some firms having recently gained market share solely due their ability to scale up.

The second area of investment should be in analytics and automation that can support and, in some cases, reduce the manual-intensive workload. We’ve already seen increases in algorithmic trading and customer chatbot technologies, while many organizations within the financial services industry use AI to automate processes, such as fraud checks and compliance.

With less time spent on time-intensive manual tasks, capital markets firms will be able to direct their attention to more value-adding services for their clients. The use of AI will help to spot patterns and anomalies in those patterns much faster for fraud prevention, while also reducing the risk of human error.

Gaining access to real-time data

Is your data strategy keeping up in real-time?

Within capital markets firms, there is a growing requirement to be able to access real-time data so these organizations can simplify their stack and get access to transactions that are happening in the moment. This will allow them to produce more time-sensitive reporting so they can make appropriate business decisions and better comply with regulatory requirements.

Data fabric

Data fabrics are fast becoming a key trend within data management across the board, helping to reduce friction. Improving the accuracy, availability and accessibility of data and should also be a consideration as capital markets weather this period of uncertainty and beyond.

A data fabric that uses the latest technology will help organizations to better grasp data governance, ensure that their data is clean and accurate, to harmonize that data where appropriate, and make it more accessible. All of these will help them derive more value and better insights from their data to help drive their enterprises and those of their customers forward.

How can capital markets firms not only survive, but also thrive?

As capital markets firms look beyond this period of volatility to thriving long term, it’s vital they embrace agility by implementing modern technology with a focus on analytics and automation. This will allow them to quickly adapt to changing and new business needs by helping them to make use of their data, analyze it, monetize it, and turn it into actionable intelligence.

In an increasingly competitive landscape, where new market entrants aren’t weighed down by legacy technology and architectures, this will be a key differentiator and enable capital markets firms to take advantage of new opportunities within the market faster.

If you want to hear more about this subject, listen to this webinar in which InterSystems takes a deep dive into the challenges facing capital markets firms and how they can mitigate risk, alongside a panel of other industry experts from Northern Trust, Westwood Group, and SIX Securities & Exchanges. Or read InterSystems‘ latest blog posts on Data Excellence.

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Lending in the New Normal: The Digitalization Challenge

Lending in the New Normal: The Digitalization Challenge
By Charlie Burgess Posted on
Categories: Sponsored

The following is a sponsored blog post by Chris Papathanassi, Global Solution Lead, Lending with Finastra. Papathanassi discusses the two challenges facing lenders: data quality and ensuring a true “golden source” and leveraging real value through data connections. Find out more in the full report >>

Today, digital is the only way to do business. But even though everything they do can be expressed in ones and zeros, most financial service organizations simply aren’t set up to be truly digital. In the context of the current disrupted, volatile and remote-working global economy, doing digital brilliantly is now a matter of survival and urgency for many financial firms – no longer simply a ‘nice to have’. 

Digital transformation is difficult for even the simplest business models, and in lending in particular, there is a real challenge. When it can take up to three months to get cash out of the door, it’s hard to see how any bank can keep up with the digital shift. There is a continued dependency in lending on paper documentation and face-to-face contact.

Despite this, the challenges of digitalization are more than balanced out by the potential benefits. You’re likely aware of a few of these already: 

  • Increased efficiency – removing repetitive, non-value-added work and moving towards real-time processing 
  • Personalization – delivering relevant customer service even in a socially-distanced context 
  • Improved credit management – providing integrated, rules-based systems for greater decision speed and transparency 
  • Proactive risk management – using APIs and platforms to “join up” the risk and sales processes
  • Self-service for corporates – providing a digital channel that empowers corporate customers 
  • Unlocking the value of data – bringing data together from disparate sources so its true value as a commodity can be leveraged

So, what needs to happen for lending to get there? 

One of the key issues is data quality and the “golden source”.  The bespoke nature of lending makes it hard to maintain data quality and consistency. Lenders have their own individual nuances and conventions. And corporate borrowers that have lending relationships with many different organizations will download and manipulate data so it’s in a format they can work with.

Can you trust the data?

As one major bank asked us: “How can we ensure what the source of truth is across different applications?”

What’s more, as data moves through different systems in a digitalized and connected world, it changes too.  

This points to the second challenge, which is that digitalized lending data is only valuable when it can be connected to the other pieces of the puzzle, to provide the big picture lenders and borrowers need. Right now, firms are still downloading data into Excel, manipulating it, and re-sending it.

Digitalization plus API capabilities, however, makes it possible for stakeholders to see the same pieces of data in the same state. It’s this connectivity that is key to realizing the full benefits of digitalization and addressing the “source of truth” issue. 

Digitalization also opens data to new technologies such as AI, machine learning, and robotic process automation, which can create new efficiencies and value for banks and customers. And for processes such as syndicated lending that have multiple players, it can be combined with cloud technology to enable more collaboration and better access to a single source of truth.

APIs in the cloud can make innovation more accessible to banks, overcoming the challenges of integrating in-house and external products. In essence, on platforms, banks have access to pre-integrated, interoperable solutions and better access to the broader financial services ecosystem, where they can explore innovations and consume them at speed. 

This potentially changes the shape of the lending industry, opening up interesting questions. What do banks want to be? Leaders in the lending business or providers of specialist products? With digitalization both options are possible, creating an opportunity for lenders to add value and build their lending businesses – or to disintermediate healthily. 

Interested in learning more? Download Finastra’s new report, Lending in the New Normal >>

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The Capital Needs of Small Businesses are Changing: Here’s How Lenders Should Respond

The Capital Needs of Small Businesses are Changing: Here’s How Lenders Should Respond
By Julie Muhn (@julieschicktanz) Posted on
Categories: Sponsored

The following is sponsored content from LendingFront.

With Covid-19 on the minds of businesses and lenders alike, conversations about the capital needs of small businesses have revolved—with obvious justification—around the Paycheck Protection Program (PPP) and other forms of relief provided under the CARES Act.

Yet the capital needs of many small businesses don’t begin and end with the PPP.

Let’s start with a few facts

According to the U.S. Federal Reserve’s 2019 Small Business Credit Survey:

  • 43% of small businesses sought external funding for their businesses in 2018
  • And more than half experienced a funding shortfall.

These funds—when small businesses can obtain them—are often used to purchase inventory, replace equipment, finance expansion, and hire new workers.

These needs will persist long after PPP lending has come to an end, yet even in a strong economy, up to 80% of bank-originated small business loan applications are rejected.

In the post Covid-19 environment, we can expect that percentage to be even higher

That’s because the conventional underwriting criteria for small business loans will no longer work. Traditionally, both bank- and non-bank lenders have relied on four criteria for underwriting small business loans:

  1. Tax/Financial Statements
  2. Credit Scores
  3. Collateral
  4. Owner Wealth

In a normal economy, these criteria are fine, but they’ll do little to show the true state of a business in the post Covid-19 environment. 2019’s tax/financial statements will be all but irrelevant. Credit scores will be damaged as a result of the inability to make payments during a forced closure. Collateral will have questionable value if bankruptcies spike. And owner wealth will have been tapped in an effort to keep many businesses afloat.

Are we headed towards a capital drought?

With traditional underwriting criteria no longer useful, are we headed toward a capital drought? We certainly don’t need to, but the answer largely hinges upon lenders doing two things:

  1. Adopting new criteria that are more appropriate for the post Covid-19 environment
  2. Adopting new product structures that enable the lender to manage risk

New credit criteria include information such as:

  • Real-time Cash Flow
    Cash flow helps you gauge how quickly the business is recovering from Covid-19. Is it in irreversible decline? Is it struggling but stable? Has it gotten back to normal? Insight into real-time cash flow helps lenders make better decisions about who to lend to along with the terms of any offers.
  • Consumer Sentiment
    Customers who vote with their reviews also vote with their wallets. Examine reviews from Google, Yelp, and other sources to answer, Is this a business that customers love? Businesses that are well-regarded by customers stand a much better chance of recovering than those that had problems before the pandemic shut them down.

New product structures also enable lenders to deliver capital efficiently while managing risk

Here’s how:

  • Shorter Terms
    First, lenders should emphasize shorter payback periods in the range of 6-12 months. Shorter terms get the lender paid back faster while enabling the business owner to show that he/she is creditworthy before seeking a larger amount of capital.
  • Daily ACH Payments
    Second, lenders should collect payments from the borrower on a daily—rather than monthly—basis. Monthly payments introduce unnecessary operational risk. Daily payments are smaller, consistent, and more predictable from the standpoint of the business’ cash flow.
  • Tie Payments to Performance
    Lastly, lenders should tie payment terms to current cash flow performance—and with visibility into cash flow, this is very easy to do.

A new economy needs new rules for lending

If the Great Recession taught us anything, it’s that opportunities exist for lenders to increase their assets, gain market share and, of course, to meet the capital needs of their borrowers. In the post Covid-19 environment, lending is only as risky as the information used to make decisions. With better underwriting criteria and more appropriate product structures, the most forward-thinking lenders will position themselves for success and reap the rewards.

Photo by David Emrich on Unsplash

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A Strategy to Accelerate Adaptability Through Infrastructure Automation

A Strategy to Accelerate Adaptability Through Infrastructure Automation
By David Penn Posted on
Categories: Guest Post, Sponsored

Today we feature a sponsored post on best practices in automation from leading open source solution provider Red Hat.

While many things have changed over the past six months, the need remains for financial services companies to increase speed and efficiency, and deliver a differentiated customer experience, all whilst complying with complex regulations and requirements.

To overcome current and future challenges, IT organizations are working to increase the flexibility of their infrastructure and operations. With security at the forefront, regulatory and compliance controls adherence requirements, digital products, and services must be efficiently developed, deployed, and managed. Often this means that infrastructure and processes require updates to support digital offerings and protect against costly security breaches and cybercrime-related risks. 

An automation framework can help organizations achieve this transformation, improving agility, flexibility, and speed to adapt to changing requirements. Optimization of resources and increased efficiency to control costs allows not only innovation but also the delivery of digital customer experiences with less risk. Organizations seeking to automate infrastructure to should consider the following best practices.

Deliver Results with People, Tools, and Processes

An effective approach to automation includes people, processes, and tools.

Start with your people

All initiatives, including automation, start with people. Begin with the following actions:

  • Build consensus to gain cultural buy-in. Ensure a successful start to your project by building consensus among all stakeholders. Failure to do so can result in well-intentioned, but isolated activities, or the continuation of time-consuming manual activities which would reduce the benefits possible with a standardized automation approach. 
  • Define the scope. Determine the extent of your automation and explain the strategy, IT benefits, and business benefits at both the organizational and individual job levels. 
  • Encourage participation. Solicit technical advice from staff who will implement, administer, and use the automation technology from the start. People will avoid using a solution if they believe it to be inadequate, regardless of its actual capabilities. 
  • Inspire collaboration. Create a culture of automation by unifying teams and technical domains for tooling that can be used by the entire organization.

Select appropriate processes

Not all processes are candidates for automation. When planning automation projects:

  • Be instinctive. Prioritize automation use cases that involve repeatable, time-intensive processes with predictable outcomes. If automating a process requires significant customization or is a single delivery to an external team, automation may not be at the top of this list, or even appropriate. 
  • Focus on benefits. Automate processes that provide benefits that scale as your adoption and scope increases. 
  • Plan for maintenance. Plan for quick and efficient ongoing maintenance of your automation activity to keep up with the business, process, and technical changes.

Choose the right tools

The right – or wrong – tools can greatly impact the success of your automation project. Look for the following capabilities:

  • Adaptability. Needs and services will not remain static. Choose tools that can adapt to change and prepare you for the future. 
  • Flexibility. Use tools that can automate infrastructure and IT processes without complex configuration or customization. Find tools that easily integrate and operate with other automation and management solutions. 
  • Simplicity. Look for tools that are easy to install, configure, manage, and maintain at scale. Analyzing and understanding the results of an automated process should be simple and straightforward. 
  • Usability. Select tools that are easy to learn. Hard-to-use tools will not be adopted by most of your team and can result in a small, segmented group of subject matter experts. 
  • Accessibility. Adopt tools that feature simple, human-readable syntax and graphical user interfaces (GUIs) to help users without advanced coding skills contribute to automation projects.

Automate for success with Red Hat

Red Hat helps financial services organizations move forward with higher performance and advanced automation. In a recent study*, Red Hat Ansible Automation Platform was shown to increase the efficiency of application environment management teams by 41%, and IT security teams by 21%.

  • Gain business and IT agility and speed through cross-organizational automation and collaboration. 
  • Boost efficiency and focus on new initiatives by eliminating manual, repetitive tasks. 
  • Innovate and deliver digital customer experiences with less risk and at a lower cost by using modern platforms that meet today’s needs and easily adapt to tomorrow’s requirements.

* Red Hat Ansible Automation Platform Improves IT Agility and Time to Market – An IDC White Paper, Sponsored by Red Hat, June 2019.

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How Accusoft’s FormSuite for Invoices Puts Machine Learning and RPA to Work

How Accusoft’s FormSuite for Invoices Puts Machine Learning and RPA to Work
By Charlie Burgess Posted on
Categories: Sponsored

This is a sponsored post by Accusoft. For more information on sponsored contributions please email sponsor@finovate.com.

Machine Learning continues to dominate conversations across the fintech ecosystem, but one aspect that rarely gets into the limelight is where the data to train the algorithms actually comes from.

Finovate sat down with Tracy Schlabach, Senior Manager, Product and Customer Marketing at Accusoft to discuss the company’s latest technology, the data challenges they overcame, and why having a symbiotic relationship with their clients drives their strategy.

Finovate: Give us an overview of what FormSuite for Invoices does.

Tracy Schlabach: FormSuite for Invoices is a toolkit for developers that are building invoice processing software solutions. FormSuite for Invoices does the heavy lifting of invoice processing, solving the hard part of finding and extracting data, such as invoice number, purchase order number, total due, line item quantity, line item description, and other data. It is configurable by the developer to extract the data specific to their needs.

Finovate: What are the technical differences between FormSuite for Structured Forms and FormSuite for Invoices?

Schlabach: FormSuite for Structured Forms deals with fixed forms, where the location of the information doesn’t move, such as a tax form, while FormSuite for Invoices deals with what we call semi-structured forms since the locations of certain values might move around the page based on the data.

For example, the “Total Due” field would move down in an invoice that has more line items. While FormSuite for Structured Forms does use AI to identify which form was passed in and to extract the data, the AI is more limited than what is required to process more dynamic content such as invoices.

FormSuite for Invoices uses some of the latest machine learning (ML) to be able to extract data from the line item tables found in invoices. This type of ML is what you hear about most often these days; deep learning with supervised and unsupervised training of a custom ResNet convolutional neural network. This technology “learns” from the changes that users make to the output results. For example, if the Total Due information on ABC Company’s invoice is located in a different quadrant on the document, the user will correct the output information. The ML technology in FormSuite for Invoices learns from these corrections, ultimately increasing confidence values.

A lot of our customers are dealing with both types of forms, structured and semi-structured, so we see people using these toolkits in combination to solve their overall forms processing challenges.

Finovate: What role does Robotic Processing Automation (RPA) play in FormSuite for Invoices?

Schlabach: Both FormSuite for Invoices and FormSuite for Structured forms have been used to serve as a data input source for RPA. When companies are using RPA to automate data entry on legacy systems, that data has to come from somewhere. Before RPA, a data entry person might key data from a piece of paper or from a computer screen into another screen that has the legacy application running on it. RPA performs the typing in place of that person, but now that data has to come from somewhere. If the data isn’t digital, for example, it is on a piece of paper, that paper can be scanned and the data extracted with one of our FormSuite products allowing the RPA robot to type that data into the legacy application.

Document capture and RPA make great partners in this way, automating what was previously a tedious and time-consuming job. Having that data available in systems quicker allows people to have quicker access to the data and make decisions faster. And the people doing the data entry are freed up to do more valuable work.

Finovate: What was the biggest challenge your team had to overcome in launching FormSuite for Invoices?

Schlabach: Line item tables are particularly challenging on multiple fronts. Their format varies a lot. Some have graphic lines surrounding each cell, but some are what we call white space tables which just use spacing to align the rows and columns. All the variation makes it really hard.

In addition, in order to use any ML, you have to have a lot of data to train with. We tried to solve the table detection and recognition using data from the leading research papers in this space, those that were winners of various ML competitions. But, we found they always fell short in some subset of our test data. 

Eventually, after working with various algorithms, one of our Principle Engineers identified a way to make a significant improvement in the ML algorithm, and the results are quite impressive. To solve the data challenge, we used a number of unique ideas to source the invoice images and used raw manpower (internal crowdsourcing) to create the “ground truth,” the correct values that are used in training and testing the machine learning.

It was an impressive effort that had the entire Accusoft organization contributing to our training data. We even had our CEO helping with the data creation at one point.

Finovate: Aside from the obvious benefit of saving time on data entry, what other benefits does FormSuite for Invoices bring to an organization?

Schlabach: There are several benefits. With Accusoft specializing in solutions for content processing, conversion, and automation solutions since 1991, developers can focus on their core strengths and let Accusoft handle the heavy lifting of content capture. As a toolkit, FormSuite for Invoices helps developers solve the most challenging aspect of the invoice process: data extraction. By embedding FormSuite for Invoices, developers significantly shorten their product’s time to market.

On the end-user side, automating invoice processing has been shown to contribute many benefits. The data entry, as mentioned, is the obvious benefit. However, companies also see dollar savings by paying invoices sooner and recognizing early payment discounts. In addition, with the speed of business today, having visibility to data is important. Invoice processing automation helps companies see a more accurate picture of their cash flow much quicker.

Finovate: So, what do you see as the next evolution of this technology?

Schlabach: As customers provide feedback, sometimes in the form of challenging images, we make improvements to the technology. That is the symbiotic value we have seen in many of our partnerships for document capture products. When partners report challenging images, we incorporate improvements into our products to better handle those images. We see this in our forms processing solutions, our barcode recognition product, our OCR and PDF products, and our viewer. We continually evolve our products, and as the exposure to documents in the wild increases, our products improve. 

We also see this technology expanding into other semi-structured forms use cases. Credit card statement processing, bills of lading, and purchase orders are just a few of the documents that could be processed using this technology. There are some different challenges in those types of documents, but there are also a lot of similarities to invoices that we can take advantage of.

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Improving Payable Processes: An Implementation Primer

Improving Payable Processes: An Implementation Primer
By Charlie Burgess Posted on
Categories: Accusoft, Sponsored

This is a sponsored post by Accusoft. For more information on sponsored contributions please email sponsor@finovate.com.

Accounts payable (AP) processes remain a sticking point for many organizations. Caught between the efficiency issues of paper-based solutions and the potential complexity of adopting technology-driven services, stagnation often results. Accusoft explores its top five tips to smooth out your system and reap the rewards.

Businesses now recognize the necessity of change, but many aren’t sure where to start. When it comes to new permutations of payable processes, a roadmap is invaluable. Here’s a look at five key forms completion and invoice processing improvements to help companies account for evolving AP expectations.

  1. Identifying errors

Staff remain the biggest source of AP errors. There’s no malice here; humans simply aren’t the ideal candidates for repetitive data entry. In this case, effective implementation of new processes depends on customizable software tools capable of accurately capturing forms data and learning over time to better identify and avoid common errors. The benefit? Staff are free to work on time-sensitive AP approval and reviews rather than double-checking basic forms data.

2. Improving invoice routes

Invoice routing is time-consuming and often confusing for AP staff. To avoid potential oversights, most companies use two to three approvers per invoice, creating multiple approval workflows. While the process reduces total error rates, it also introduces new complexity. What happens if invoice versions don’t match or approvers don’t agree on their figures? In the best-case scenario, your company needs extra time to process every invoice. Worst case? Double payment of AP invoices or payments result in missed critical deadlines. Here, a single-application approach to invoice processing helps improve invoice routes and reduce redundant approval steps.

3. Integrating data location

Where is your accounts payable data located? For many companies, there’s no easy answer; some invoices are paper, others are digitally stored on secure servers, and there are still more trapped in emails and messages across your organization. Instead of chasing down AP data, implement an invoice rehoming process. Solutions like Accusoft’s FormSuite for Invoices support thousands of invoice formats and keep them all in the same place.

4. Innovating at speed and scale

Complexity holds back many accounts payable programs. If new technologies complicate existing processes, employee error rates will go up and there’s a chance they’ll avoid digital deployments altogether in favor of familiar paper alternatives. In this case, automation is the key to implementation; speedy solutions capable of scanning paper forms, identifying key data, and then digitally converting this information at scale. 

5. Increasing visibility

You can’t fix what you can’t see. Paper-based invoice processing naturally frustrates visibility by making it difficult to find key documents and assess total financial liabilities. Integrated APIs that work with your existing accounts payable applications can help improve inherent visibility by creating a single source of AP data under the secure umbrella of your corporate IT infrastructure.

Want to learn more about the potential pathways available for companies to improve their AP processes and reduce total complexity? Check out Volume 1 of our Accounts Payable eGuide series, No Pain, No Gain?

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Webinar: Move Banking from Product-Centric to Customer-Centric

Webinar: Move Banking from Product-Centric to Customer-Centric
By Charlie Burgess Posted on
Categories: Finovate Webinar, Sponsored, Webinars

Featuring:

Is your bank keeping pace with escalating customer expectations shaped by their mobile experiences? How are you addressing the perception that all banks are the same? 

It’s tough when you have a product focus and outdated technology is holding you back. You know you need to modernize to win and retain demanding, empowered, and fickle customers. Customer loyalty and company revenue are at risk if you don’t.

In this webinar, featuring OutSystems and guest speaker Alyson Clarke, Principal Analyst at Forrester, you’ll learn how leading firms like Amazon, Nordstrom, USAA, and Zappos have made the shift to customer-centricity and are delivering world-class customer experiences.

These insights will help your bank follow suit.

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Mission-Critical, Concurrent Transactional, and Analytic Processing at Scale

Mission-Critical, Concurrent Transactional, and Analytic Processing at Scale
By Charlie Burgess Posted on
Categories: Sponsored

This is a sponsored blog post by InterSystems, a financial data technology company based in Cambridge, Massachusetts.

Successful financial services organizations today must be able to simultaneously process transactional and analytic workloads at high scale – accommodating billions of transactions per day while supporting thousands of analytic queries per second from hundreds of applications – without incident. The consequences of dropped trades, or worse – a system
failure – can be severe, incurring financial losses and reputational damage of the firm.

InterSystems’ IRIS Data Platform is a hybrid transactional/ analytic processing (HTAP) database platform that delivers the performance of an in-memory database with the reliability and built-in durability of a traditional operational database.

InterSystems IRIS is optimized to concurrently accommodate both very high transactional workloads and a high volume of analytical queries on the transactional data. It does so without compromise, incident, or performance degradation, even during periods of extreme volatility and requires fewer DBAs than other databases. In fact, many installations do not need a dedicated DBA at all.

An open environment for defining business logic and building mobile and/or web-based user interfaces enables rapid development and agile business innovation.

For one leading global investment bank, InterSystems data platform is processing billions of daily transactions, resulting in a 3x to 5x increase in throughput, a 10x increase in performance, and a 75% reduction in operating costs. The application has operated without incident since its inception.

Traditionally, online transaction processing (OLTP) and online analytical processing (OLAP) workloads have been handled independently, by separate databases. However, operating separate databases creates complexity and latency because data must be moved from the OLTP environment to the OLAP environment for analysis. This has led to the development of a new kind of database. In 2014, Gartner coined the term hybrid transaction/analytical processing1, or HTAP, for this new kind of database, which can process both OLTP and OLAP workloads in a single
environment without having to copy the transactional data for analysis.

At the core of InterSystems IRIS is the industry’s only comprehensive, multi-model database that delivers fast transactional and analytic performance without sacrificing scalability, reliability, or security. It supports relational, object-oriented, document, key value, and hierarchical data types, all in a common persistent storage tier.

InterSystems IRIS offers a unique set of features that make it attractive for mission-critical, high-performance transaction management and analytics applications, including:

  • High performance for transactional workloads with built-in guaranteed durability
  • High performance for analytic workloads
  • Lower total cost of ownership

InterSystems IRIS is enabling financial services organizations to process high transactional and analytic workloads concurrently, without compromising either type – using a single platform – with the highest levels
of performance and reliability, even when transaction volumes spike.

Founded in 1978, InterSystems is a privately held company headquartered in Cambridge, Massachusetts (USA), with offices worldwide, and its software products are used daily by millions of people in more than 80 countries. For more information, visit: Financial.InterSystems.com

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Synthetic Data Can Conquer FinServ’s Fear of Data Security and Privacy

Synthetic Data Can Conquer FinServ’s Fear of Data Security and Privacy
By Charlie Burgess Posted on
Categories: Sponsored

This is a sponsored blog post by Randy Koch, CEO of ARM Insight, a financial data technology company based in Portland, Oregon. Here, he explores what synthetic data is, and why financial institutions should start taking note.

You’ve heard it before – data is invaluable. The more data your company possesses the more innovation and insights you can bring to your customers, partners and solutions. But financial services organizations, which handle extremely sensitive card data and personally identifiable information (PII), face a difficult data management challenge. These organizations have to navigate how to use their data as an asset to increase efficiencies or reduce operational costs, all while maintaining privacy and security protocols necessary to comply with stringent industry regulations like the Payment Card Industry Data Security Standard (PCI DSS) and the General Data Protection Regulation (GDPR).

It’s a tall order.

We’ve found that by accurately finding and converting sensitive data into a revolutionary new category – synthetic data – financial services organizations can finally use sensitive data to maximize business and cutting-edge technologies, like artificial intelligence and machine learning solutions, without having to worry about compliance, security and privacy.

But first, let’s examine the traditional types of data categorizations and dissect why financial services organizations shouldn’t rely on them to make data safe and usable.

Raw and Anonymous Data – High Security and Privacy Risk

The two most traditional types of data categorization types – raw and anonymous – come with pros and cons. With raw data, all the personally identifiable information (PII) fields for both the consumer (name, social security number, email, phone, etc.) and the associated transaction remain tagged to data. Raw data carries a considerable risk – and institutional regulations and customer terms and conditions mandate strict privacy standards for raw data management. If a hacker or an insider threat were to exfiltrate this type of data, the compliance violations and breach headlines would be dire. To use raw data widely across your organization borders on negligence – regardless of the security solutions you have in place.

And with anonymous data, PII is removed, but the real transaction data remains unchanged. It’s lower risk than raw data and used more often for both external and internal data activities. However, if a data breach occurs, it is very possible to reverse engineer anonymous data to reveal PII. The security, compliance and privacy risks still exist.

Enter A New Data Paradigm – Synthetic Data

Synthetic data is fundamentally new to the financial services industry. Synthetic data is the breakthrough data type that addresses privacy, compliance, reputational, and breach headline risks head-on. Synthetic data mimics real data while removing the identifiable characteristics of the customer, banking institution, and transaction. When properly synthesized, it cannot be reverse engineered, yet it retains all the statistical value of the original data set. Minor and random field changes made to the original data set completely protect the consumer identity and transaction.

With synthetic data, financial institutions can freely use sensitive data to bolster product or service development with virtually zero risks. Organizations that use synthetic data can truly dig down in analytics, including spending for small business users, customer segmentation for marketing, fraud detection trends, or customer loan likelihood, to name just a few applications. Additonally, synthetic data can safely rev up machine learning and artificial intelligence engines with an influx of valuable data to innovate new products, reduce operational costs and produce new business insights.

Most importantly, synthetic data helps fortify internal security in the age of the data breach. Usually, the single largest data security risks for financial institutions is employee misuse or abuse of raw or anonymous data. Organizations can render misuse or abuse moot by using synthetic data.

An Untapped Opportunity

Compared to other industries, financial institutions haven’t jumped on the business opportunities that synthetic data enables. Healthcare technology companies use synthetic data modeled on actual cancer patient data to facilitate more accurate, comprehensive research. In scientific applications, volcanologists use synthetic data to reduce false positives for eruption predictions from 60 percent to 20 percent. And in technology, synthetic data is used for innovations such as removing blur in photos depicting motion and building more robust algorithms to streamline the training of self-driving automobiles.

Financial institutions should take cues from other major industries and consider leveraging synthetic data. This new data categorization type can help organizations effortlessly adhere to the highest security, privacy and compliance standards when transmitting, tracking and storing sensitive data. Industry revolutionaries have already started to recognize how invaluable synthetic data is to their business success, and we’re looking forward to seeing how this new data paradigm changes the financial services industry for the better.

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What is the California Consumer Privacy Act and How Should You Prepare?

By Charlie Burgess Posted on
Categories: FinovateFall 2019, Sponsored

In this sponsored blog post, Akshatha Kamath, Content Marketing at MoEngage, breaks down new privacy legislation which could impact financial institutions across the states.

Stronger privacy protection and greater data transparency online are growing global trends. The Cambridge Analytica scandal, in which the Facebook data of at least 87 million people were misappropriated, and other instances like this have brought attention to how businesses collect, use, and sell consumer data. Concern over the use and misuse of this data is widespread. 

In many global jurisdictions, the response has been privacy legislation which forces businesses to comply with sometimes onerous regulations regarding consumer data and privacy. One of these pieces of legislation is the California Consumer Privacy Act. In its second section it lays out how pervasive privacy concerns have become and how “it is almost impossible to apply for a job, raise a child, drive a car, or make an appointment without sharing personal information.”

All of this data can be great for marketers, but businesses need to comply with privacy laws in order to avoid fines and stay up to date with consumer demand for privacy and data transparency online.

The California Consumer Privacy Act (AB-375)

The California Consumer Privacy Act of 2018 (CCPA) is by far the strongest privacy legislation enacted in the United States at this time. Businesses must be in compliance by January 1, 2020 (the starting date on which the state can bring enforcement actions involving noncompliance).

For marketers there are three major things to be aware of. First is that wherever personal information is collected businesses must disclose what information they collect and how they will use it. Secondly, businesses have to provide consumers with the ability to “opt out” of having their information sold to third parties. Thirdly, businesses must allow consumers to view and delete the information that has been collected about them.

Is My Company Affected by the CCPA?

If your business (or for-profit entity) is located in California and meets any of the following criteria, it has privacy requirements that need to be met under the law. The criteria are:

  • Your business’ annual revenue is over $25 million
  • Your business receives information of over 50,000 consumers, households, or devices annually
  • At least half of your business’ annual revenue comes from selling personal information

The law doesn’t differentiate between brick-and-mortar and online companies. This means that even a company with no physical presence or employees in California could still do business there and therefore has obligations under the law. So your business doesn’t even need to be located in California for the California Consumer Privacy Act to apply to you. Like the GDPR, CCPA will affect businesses outside the law’s jurisdiction.

Consumer’s Rights Under the CCPA

Consumers have new rights under the CCPA that companies need to be aware of. These rights fall into three broad categories:

  1. The Right to Knowledge – Under the CCPA, businesses must allow consumers to obtain, twice per annum at zero cost, all the information that the business has about them, how that information was collected, and who else has been given said information.
  2. The Right to be Forgotten – The CCPA stipulates that consumers must be able to request the deletion of all of their personal information from a company. If the information has been shared with third parties then those parties must also delete said information.
  3. The Right to Control who has Access to their Information -Businesses must allow consumers to be able to opt out of the resale of their information. Consumers under the age of 16 must affirmatively opt in to allow the resale of their data. Consumers under the age of 13 must have written permission from a parent or guardian in order to allow the resale of their data.

What Marketers Need to Do

First of all, marketers need to review their current procedures and understand their policies and procedures regarding the collection, storage and use of subscribers’ data and mailing preferences. They need to know how a user’s preferences about their data can be stored and how documentation would be provided if a user requests it.

Second of all, marketers need to think in the long term about how they set up their systems. For example, even though GDPR only applies to EU visitors, many companies have opted to implement the same higher standards across their entire platform in order to proactively prepare for similar legislations. In the same vein, marketers who prepare for the CCPA will have a leg up if privacy bills that are making their way through the legislature pass in New York, Mississippi, and Massachusetts.

Penalties for Non-Compliance of the CCPA

If, because of a business’ negligence, a consumer’s information is improperly disclosed, the CCPA makes it easier for consumers to sue (even if there is no evidence that the data breach caused the consumer harm!).

What could be very costly for businesses is the potential for class-action lawsuits due to a data breach. Companies could be on the hook for between $100 and $750 per incident (or even more if the actual damages exceed $750).

Conclusion

The California Consumer Privacy Act will go into effect on January 1, 2020. Marketers should prepare in advance to make changes to comply with the regulations. At the same time, CCPA presents marketers with an opportunity to strengthen the relationship between consumers and your business. Educate consumers on the data you are collecting and how you make use of it. Be sure to tell them their rights under the CCPA and how you are compliant. This can build trust with consumers and help you use the CCPA to your advantage.

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Challenges of Enterprise Marketing Teams and How to Solve Them

By Charlie Burgess Posted on
Categories: Sponsored

Akshatha Kamath, Content Marketing at MoEngage, looks into the common challenges for enterprise marketing teams and asks whether automation is the answer.

Marketing for a large enterprise company is challenging. It is often the case that big organizations have multiple teams working on marketing that are each in their own silo. The data is segmented, the campaigns are segmented and the teams do not talk to one another. This can cause friction in your organization when your marketing messages may be broadcast to hundreds of thousands or even millions of consumers.

When your marketing teams are working in silos your brand suffers. One customer might receive multiple different disjointed marketing communications from your brand and this impacts the customer experience negatively, as well as being a waste of your marketing resources.

Expansion to New Frontiers

Another current challenge of enterprise marketers is creating a seamless customer experience on and offline. For brick and mortar brands building out digital is an imperative (87% of executives say it is a “matter of survival”).

This is an especially taxing challenge for large enterprise brands who may have to juggle supporting local marketers with limited resources – be they a dealership or franchisee. Often, it may be that these local marketers do not have the same marketing experience as those working at corporate headquarters. They execute their campaigns without much background in marketing while also dealing with human resources, bookkeeping, inventory and all the other headaches that come with running a business.

Supporting these local marketers is also a challenge for brand managers. They can also be resource-strapped and often may not have enough to do all they need to accomplish. There’s a chance they also don’t have the campaign budget to produce all that they need and brand managers often don’t have dedicated staff to verify in-store compliance.

For an enterprise brand manager to overcome these challenges and successfully implement their marketing strategy, communication with local marketers is key. Brand managers must encourage success at the local level. Those who have high local marketer satisfaction have an active dialogue with local marketers to better appreciate how they are struggling. These brand managers also invest in easy-to-use tools in process, design, and technology. The higher quality the communication is, the better the outcome.

Solving Geographic Difficulties

A brand manager’s job is to make local marketing easy for affiliates. In a distributed organization it takes a lot of stakeholders to run just a single campaign. Something as simple as printing up a poster to be hung in a storefront window may require input and approval from design, brand management, compliance, and local marketers.

This is a natural part of enterprise distributed marketing as one’s business model is distributed so workflows are going to be complex. Despite the complicated approval processes and multiple stakeholders involved, these systems can be made more efficient with the right tools. Streamlining workflows for distributed enterprise marketing involves documenting the process of what needs to be done in order to make it easier for all involved to follow it. Often companies find it beneficial to use technology to do this.

Multi-geographic brands can also rarely monitor all field execution of marketing in person. This can generate concern that brand messaging is being modified in a way that is out of line with the brand’s standards.

Consumers typically do not distinguish between enterprise-owned and locally-owned businesses – they see just one thing: brands. 60% of millennials in the United States expect consistent experiences when dealing with brands whether online, in-store or by telephone. This highlights how important it is for distributed enterprise brands to keep their message consistent.

Education and knowledge about a brand are critically important for all stakeholders. Many distributed brands have affiliate on-boarding and training processes that place branding as a core subject. Other brands are finding value in marketing asset management technology in order to scale consistently. They use template tools for executing their local marketing strategies which allows brand management teams to “lock” certain design characteristics or messages and allow local marketers to input their information (such as address or local offers) in order to maintain brand consistency.

Is Automation the Solution?

What enterprise marketers may need is a system that streamlines their marketing channel in order to bring together marketers, campaign managers, and product managers under one system to efficiently manage marketing campaigns with input and collaboration between all of those involved.

MoEngage has developed some tools for enterprise marketing teams using extensive feedback from stakeholders. This unified approach to enterprise marketing can send out a clear signal amidst the noise. MoEngage Teams and MoEngage Campaign Approval Workflow are two such tools that enable brands to eliminate the silos within their teams and ensure a smooth flow of customer data and insights between teams. This can help enterprises eliminate the challenges that stem out large teams spread across geographies or multiple owned brands that need a unified customer view, and many more. Talk to MoEngage’s experts for a personalized walk-through of these enterprise-ready marketing tools from MoEngage.

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MoEngage’s Evolution into a Mobile Marketing Platform for Big Brands

MoEngage’s Evolution into a Mobile Marketing Platform for Big Brands
By Charlie Burgess Posted on
Categories: Sponsored, Uncategorized

The following guest blog post is written and sponsored by MoEngage.

MoEngage, an Intelligent Customer Engagement Platform built for the mobile first world, has been featured in the 2019 Gartner Magic Quadrant for Mobile Marketing Platform for the second time in a row. It is the youngest company to be featured in the report and has made the biggest leap in improvement in its position as compared to all the other vendors. You can read the complimentary copy of the report here. 

In its initial years, MoEngage’s platform saw rapid adoption from mobile-first startups and mid-market brands. As these brands grew, with some even becoming unicorns, MoEngage’s platform also improved to match the growing complexity and scale of their customers. Building on this momentum, MoEngage made significant investments in customer experience and product innovation. Today, MoEngage has evolved into a robust mobile marketing platform that has seen significant adoption by enterprises across Asia, the U.S., and Europe. In the last 12 months, the company has added several large enterprise clients such as Future Retail, Deutsche Telekom, Mashreq Bank, Travelodge, Samsung, and more. Enterprise clients contribute nearly 50% of MoEngage’s total revenues, while mobile first brands and unicorns contribute the rest.

“Our progression in Gartner’s Magic Quadrant and adoption by large enterprises is a testament to our investments in product innovation and customer success. Consumer brands in 35 countries trust MoEngage to power their cross-channel customer engagement campaigns to improve adoption, retention, loyalty, and customer LTV. This recognition reinforces our vision to be the most trusted customer engagement platform for the mobile-first world. We place customers at the heart of everything we do and our customer obsession is reflected by not just our renewal rates, but also by the reviews on Gartner Peer Insights websites” said Raviteja Dodda, CEO and founder, MoEngage.

Designed for the mobile-first world, MoEngage provides one dashboard through which consumer brands can analyse user behavior, engage across channels and personalize every touchpoint. Processing over 45 billion user interactions and delivering over 25 billion messages to 400 million users every month, MoEngage is one of the fastest-growing companies in this space. To know more visit www.moengage.com

Gartner Magic Quadrant for Mobile Marketing Platforms, Mike McGuire, Charles Golvin, 15 July 2019 GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used here with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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