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Headless Banking and Banking-as-a-Service: Shaping the Future of Finance

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Headless Banking and Banking-as-a-Service: Shaping the Future of Finance

There are two transformative models currently reshaping how financial services are developed, delivered, and consumed across the globe – headless banking and Banking-as-a-Service (BaaS). From North America’s robust financial ecosystems to APAC’s innovation hubs, and EMEA’s regulatory frameworks to Latin America’s burgeoning fintech scene, understanding both of these models is crucial to navigating the scene effectively. Headless banking, where banks separate their front-end and back-end processes to enable greater flexibility and customization in customer interactions, contrasts with BaaS, where banks or licenced institutions offer their banking services to other (usually non-financial) businesses, allowing them to integrate financial services directly into their offerings. And when it comes to the risk decisioning software that supports both of these models, the challenges and opportunities that headless banking and BaaS provide can help to inform our approach to managing and mitigating risks – an approach that needs to innovate and evolve as rapidly as the regulations and new advancements that the industry offers.

Key Features and Benefits of Headless Banking

With headless banking, the traditional integration of front-end user interfaces and back-end banking processes is uncoupled. Taking digital, front-end experiences away from the core banking functions that happen in the background enables an unprecedented level of flexibility and customization, allowing financial institutions to easily (and quickly!) integrate new technologies and services, offering personalized experiences that are tailored to individual customer needs and preferences. This ensures maximum agility and helps to foster rapid innovation, allowing you to get ahead in a highly competitive market by more rapidly adapting to emerging trends and changing customer demands.

Additionally, headless banking can significantly impact your cost efficiency. By utilizing APIs to connect disparate systems and services, you can reduce the need for an extensive overhaul of the backend every time the front-end technology evolves or customer expectations change. This modular approach reduces development and maintenance costs, but also strengthens security protocols, enabling potential security breaches to be isolated and managed more effectively, and minimizing overall risk.

When it comes to regulatory compliance, headless banking offers an adaptable framework that simplifies the integration of compliance measures into both existing and new products. This flexibility is crucial for global expansion, and embracing open banking standards, allowing you to easily customize and localize your offerings to meet specific regional regulatory requirements as well as cultural preferences. The opportunity to expand your global footprint while enhancing your service delivery will help to drive business growth and customer satisfaction.

Key Benefits of Headless Banking

  • Customer-Centric Approach
  • Digital Integration
  • Customization and Personalization
  • Agility and Innovation
  • Cost and Operational Efficiency
  • Enhanced Security
  • Regulatory Compliance and Open Banking
  • Global Expansion and Localization

Banking via Non-Banks: Banking-as-a-Service (BaaS)

Banking-as-a-Service (BaaS) is a model that allows non-banking entities to offer financial services and products by leveraging the existing infrastructure of established financial institutions. While this approach has many benefits for the non-banks (and consumers) who wish to use it, it all hinges on the use of APIs that connect third-party companies (fintechs, retailers, tech giants) directly to the extensive banking services and systems of more traditional financial institutions. BaaS platforms are technically the intermediaries, facilitating seamless integrations between the banks and the non-banks, enabling those non-banks to offer a range of financial services and products (including payments, lending, insurance, and investment services) under their own brand that enable a frictionless, all-in-one experience for their customers.

The operation of BaaS through APIs ensures the basic functionality of ‘banking’ but it also offers the compliance and security that consumers expect when they interact with any sort of financial service or product. BaaS promotes extensive fintech partnerships, giving the opportunity for non-banks to design and deliver truly customized financial solutions that meet the (often very) specific needs of their customer base, without dealing with the burden of developing, maintaining, and regulating a complete banking infrastructure.

BaaS is often seen as a transformative model in the financial services industry, democratizing access to financial services and encouraging innovation and inclusion. Companies can diversify their offerings, improve customer engagement, and generate new revenue streams, all while relying on the track record of robust, secure, compliant banking frameworks and infrastructure provided by established banking partners. Ultimately, while this improves customer access to a variety of financial offerings, it also helps drive competition and innovation in the industry as a whole, enabling more choice and more personalized, frictionless experiences for consumers.

Both headless banking and BaaS emphasize the industry-wide drive towards more modular and flexible financial service delivery, yet technically they both serve as distinct functions within the larger ecosystem. While different in how they function and the infrastructure required, the two models can complement each other quite well. For example, a BaaS provider could adopt a headless approach to provide more customizable interfaces for clients, combining robust back-end services with more tailored front-end designs.

Challenges and Barriers: Overcoming Obstacles in Headless Banking and BaaS

As with any innovation, incorporating headless banking or BaaS into your service offerings can come with unique challenges.

  • Legacy Systems: One of the most significant challenges facing the adoption of any newer technology in the financial services world is the integration of modern, flexible banking models/systems with outdated legacy systems that are often rigid and complex. These systems can make it extremely difficult to implement the agile and modular structures required by headless banking and BaaS (and often can’t efficiently handle the rapid changes to these products that the market and consumers demand). Additionally, it’s imperative to ensure that new, more modular systems can effectively communicate and operate with existing banking systems and third-party services, which can be challenging, especially when dealing with a wide range of standards and technologies. 
  • Strategy: To overcome the challenges of legacy technologies, adopt a phased approach to modernization, gradually replacing or encapsulating legacy components with microservices and APIs that offer greater flexibility. Ensure you have access to a Professional Services team or consultants that have deep expertise in systems migrations.
  • Regulatory Hurdles: Both models must navigate a complicated framework of financial regulations that vary by region and jurisdiction (and often industry – for example, if you’re offering any sort of banking services to the healthcare industry or government entities, there can be an added layer of compliance considerations). BaaS especially faces compliance challenges, as it involves third parties offering financial services – due diligence for regulatory oversight is key.
  • Strategy: Early and ongoing engagement with the right regulatory bodies is critical, and the use of regulatory sandboxes for testing can be helpful. Leverage expert legal and compliance teams to build and maintain a framework that adapts to regulatory evolution and new compliance demands.
  • Security: Security is crucial, as it is with all financial services, especially given the increased exposure to fraud and cyber threats that come with opening up banking systems through APIs and enhanced customer touchpoints.
  • Strategy: Adopt robust cybersecurity measures, including end-to-end encryption, regular security audits, and compliance with the most stringent international security standards to mitigate these risks.
  • Cultural/Organizational Resistance: Shifting to a new model requires buy-in across the organization and often necessitates a significant cultural shift, moving away from more traditional banking practices to more innovative, technology-driven approaches.
  • Strategy: Leadership needs to champion the change, and implement comprehensive training programs to ensure alignment company-wide. Be sure to illustrate the competitive advantages and potential for improved customer experiences and sustainable growth to help gain buy-in.
  • Integration Complexity and Lack of Expertise: While APIs facilitate integration between systems, managing a large amount of interfaces between the front and a variety of back-end services can quickly become complex.
  • Strategy: It can take significant effort to ensure stability, performance, and consistency across all of these interfaces – the key is deep expertise in integrating systems, tech migrations, and developing new infrastructure.

Leading the Headless Banking and BaaS Evolution

Who’s leading the charge? Those organizations who embrace agility, technological prowess, and new models for delivering financial services. Here’s a closer look:

Fintech Startups
Fintech startups are often the most aggressive in adopting headless banking principles due to their digital-native foundations and lack of legacy infrastructure. They are known for their rapid innovation, customer-centric designs, and use of modern technology stacks, making them natural leaders in this space. Examples include:

  • Challenger Banks: Digital-only banks like Revolut, Monzo, and N26, who can leverage headless architectures to offer innovative, user-friendly banking experiences.
  • Banking Platforms: Companies like Plaid and Stripe provide API-driven services that enable other businesses, including traditional banks, to offer fintech solutions seamlessly integrated with their existing offerings.

Traditional Banks
Banks that are investing in digital transformation initiatives, forming partnerships with fintech companies, or developing in-house solutions to modernize their banking platforms. Examples include:

  • Global Banks: Some of the world’s largest banks, such as JP Morgan Chase, Goldman Sachs (with its Marcus brand), and HSBC, are investing heavily in digital banking initiatives, including the adoption of headless and API-driven architectures to enhance customer experiences and expand their digital offerings.
  • Regional and Community Banks: Smaller banks are increasingly partnering with fintech and BaaS providers to leverage headless banking capabilities, allowing them to offer competitive digital services without the need for extensive in-house technology development.

Technology and BaaS Providers
Technology companies and BaaS providers offer the infrastructure, platforms, and tools that enable both fintech startups and traditional banks to implement headless banking solutions. These providers are crucial enablers of the trend, offering the APIs, development platforms, and cloud infrastructure necessary to build and scale headless banking services. Key players include:

  • BaaS Platforms: Companies like Solarisbank, Banking Circle, and Galileo offer banking-as-a-service platforms that enable other businesses to launch financial products quickly and efficiently using headless principles.
  • Cloud Service Providers: Major cloud providers such as Amazon Web Services (AWS), Google Cloud, and Microsoft Azure offer the infrastructure and services that support the scalability, security, and flexibility required for headless banking.

Future Outlook

At Provenir, we’ve been on the forefront of tech innovation for financial services for the past twenty years – and it looks like the next twenty hold just as much potential! So what does the future hold for both headless banking and BaaS? Both models are set to significantly influence wider industry dynamics, driving further transformation in financial services, enhancing customer experiences, and driving operational efficiencies. Some key things to keep in mind:

  • Technology and Innovation: Cutting-edge tech (like AI/ML) is crucial. These technologies enable more personalized banking experiences, less friction in the customer experience, improved security measures, and greater operational agility. Integrating artificial intelligence allows for smarter, data-driven decisions that can be scaled as needed, transforming customer touchpoints to more meaningful, tailored experiences.
  • Seamless Integration: Headless banking and BaaS can help encourage more seamless integration of financial services into the daily lives of consumers, enhancing the customer journey with BaaS services like integrated payments, lending, and insurance. Headless banking will empower more banks to rapidly innovate and customize offerings, reducing the time-to-market for new products and services, and reducing friction along the journey.
  • Cloud-Based Platforms: Holistic, end-to-end, cloud-native risk decisioning platforms can play a pivotal role in the tech transformation of the industry. Platforms like Provenir’s AI-powered decisioning solution can provide the necessary infrastructure to manage vast amounts of data security and safely, and comply with regulatory requirements, while supporting real-time risk assessment and decisioning across fraud and credit.
  • Traditional Bank Response: Prominent tech companies and fintechs are leading the way in BaaS, while larger players like Stripe and Square are providing platform services that enable other businesses to offer financial services. Financial institutions like DBS and BBVA are delving into headless banking by separating their customer-facing interfaces from core banking services. More traditional banks are increasingly responding to these trends by either partnering with fintechs, investing in their own BaaS or headless banking solutions, or acquiring promising tech startups to bring these innovations in-house.

The BaaS market size is estimated at USD 5.32 billion in 2024, and is expected to reach USD 14.72 billion by 2029, growing at a CAGR of 26.60% during the forecast period (2024-2029).

As with all tech trends in the past twenty years (remember your first mobile payment?), anything truly innovative is poised to fundamentally change how financial products and services are developed, delivered, and consumed. As the focus on consumer experience continues to grow, tech that shifts the industry towards more integrated, customer-centric, frictionless experiences will be golden – especially because it can also improve operational efficiency and encourage sustainable business growth.

For more information on how holistic, end-to-end decisioning can help you launch your headless banking or BaaS products:

Contact Us

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Maximizing AI/ML for Fraud and Risk Mitigation

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Maximizing AI/ML
for Fraud and Risk Mitigation

  • Jason Abbott, Senior Product Manager, Fraud Solutions
  • May 6, 2024

How to Harness Artificial Intelligence and Machine Learning for Comprehensive Fraud Protection

The battle against fraud and risk in financial institutions is complex, and it’s always changing. And fraud doesn’t start and end with the onboarding of applicants – it’s a continuous challenge that demands evolving strategies. This is why it’s critical to look at risk decisioning solutions, including artificial intelligence and machine learning, that can access real-time data across the journey – tackling fraud screening not just at the application stage, but throughout the entire customer lifecycle.

Real-time data for real-time decision making

Artificial intelligence and machine learning (AI/ML) play a pivotal role in detecting and preventing fraudulent activities. With financial fraud methods becoming more and more sophisticated, one key way to stay ahead of fraudsters is accessing real-time data, integrating it into your risk decisioning solutions, and automating the use of that data with AI/ML. In this way, you can react swiftly (and accurately) to ever-evolving fraud threats. 

But it’s critical to balance fraud mitigation with the customer experience. While admittedly powerful technology, AI/ML requires more than just advanced algorithms and risk models – it needs a comprehensive understanding of the overall decisioning operations, customer experience, and the regulatory and compliance landscape of financial services organizations in the regions you operate. An effective fraud decisioning model needs to not only intercept fraudsters, but it needs to be sure that it doesn’t introduce more friction for legitimate customers. Tightening the net on fraudsters isn’t the most optimal answer – we need to ensure that embedded intelligence is working efficiently to keep out the bad actors while still extending the right products and offers to a growing number of creditworthy customers.

Intelligent use of data throughout the customer journey

A common challenge that financial institutions face is the underutilization of valuable customer data that gets collected during the application process. Rather than discarding this data, it should be integrated into ongoing monitoring programs and used to enhance risk mitigation strategies, especially during high-risk events. For example, take the case of mule account detection, where initial application data contains the right indicators that help approve an applicant. But with ongoing monitoring as new data becomes available, financial institutions could intervene later if new suspicious activity is tracked. With a set-it-and-forget-it mindset and the lack of ongoing monitoring, fraudsters can more easily slip through the cracks. As fraud methods become more evolved, the risk models needed to prevent fraud need to evolve as well. Many times, actors with ill-intent will use legitimate credentials to gain access to products and services and then pull a bait-and-switch when onboarded. Without the use of ongoing monitoring and the continuous intelligent, optimized use of risk data across the journey, these sorts of situations become difficult to catch until it’s too late. 

This is why adapting quickly to new threats is so critical. Flexibility and responsiveness are key things to look for in a fraud/risk decisioning solution, because with the adaptability to add new data sources, optimize risk models based on intelligence, and change decisioning processes easily, you are able to respond to threats more effectively. AI/ML models act like the central nervous system of a modern sports car, where every component must communicate and function in unison to effectively respond to changing conditions – in the case of a car it’s road conditions, weather conditions, engine temperature, etc. In the case of fraud mitigation, you need to ensure that you can adapt quickly without being bogged down by manual processes or IT backlogs to make changes.

Efficient data integration

Not all financial institutions have the ability to integrate extensive datasets into a smart, unified model or data lake. Whether it’s technical restrictions, resource issues, IT backlogs, or the challenges of merging disparate systems, there are many factors that can hinder efficient data integration. What’s needed is an effective fraud orchestration layer, combined with low-code or no-code capabilities, allowing you to adapt and innovate as quickly as threats do, giving you a significant competitive advantage (and again, helping to maintain a positive customer experience with limited friction). 

So what are the key things to consider when it comes to enhancing your fraud mitigation strategy by harnessing AI/ML? Think of the following:

    • Does your AI/ML model for application fraud provide reliable scoring and clear explainability?

    • Can you integrate fraud-rich data into your application fraud infrastructure?

    • How easily can you integrate new data sources in response to emerging fraud trends?

    • Are you able to leverage available data to address potential post-application fraud?

    With cutting-edge technology designed to empower financial institutions to not only respond to threats in real time, but also anticipate them before they can cause harm, decisioning technology that incorporates robust AI/ML solutions will ensure your organization (and your customers) remain secure and satisfied.

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    Successful Digital Transformation in Financial Services

    Q&A with Industry Experts

    Successful Digital Transformation
    in Financial Services

    • 01

      Digital transformation is critical for financial services organizations who want to thrive in our increasingly digital age. As consumers demand more and more from their financial services interactions, those organizations that don’t evolve will be left behind. But what are the keys to a successful journey?

      We recently hosted a webinar focusing on the intricacies of this transformative process, looking at key challenges and guidance for financial institutions looking towards a digitally empowered future. And from that discussion, a number of insightful audience questions were addressed – so we wanted to share some of them here with you!
    • 02

      With digital transformation came digital banking which made life easy for both consumers and would-be thieves. How can we mitigate the increasing hacking risks associated with digital  banking, from both the customer side and the bank side?

      Digitalization is increasing – and yes, so is fraud. This is where client authentication becomes so important, and truly understanding and knowing your customer is key. Device authentication for example can be critical, as well as collecting the required data to be sure we are understanding our customers without impacting the customer journey. That level of discipline needs to sit with the financial institution, without necessarily being seen or experienced by the customer. Identity theft is quite prevalent, especially in certain regions like the Nordics, so it’s critical to balance the need and desire to have strong fraud and identity management in place, without adding friction to the process for your consumers.

    • 03

      How is generative AI impacting decisioning?

      There is a potential for a large impact on decisioning with the use of generative AI tools. We’re in the early adoption stages, because from a regulatory and compliance standpoint, there is a nervousness about using these tools to push businesses forward. Institutions are risk averse, cautious, and measured in the terms of the policies they implement. Corporate governances are challenges for many banks, particularly when dealing with a variety of regional regulations. In part, it comes down to explainability. While AI tools can certainly help from a risk decisioning standpoint, and should be fully explainable in that regard, there is not enough known about the control and regulation of generative AI tools to ensure that data is being used and stored properly. Ultimately, we’re early on in this journey and they will play a fundamental role in our industry over the next few years.
    • 04

      What is the importance of being able to adjust business lending and fraud rules quickly given the rate of change in the macro-economic landscape, customer behavior and MO of fraudsters? Why are organizations, particularly in the financial services industry, struggling to keep up with these rates of change?

      Often, organizations struggle to keep up with the rate of change due to the technology infrastructure in place. Being able to make changes quickly to respond to market demands and evolving threats is key to not only accurate fraud prevention, but also simply ensuring that you’re meeting the needs of your customers. If you have to wait six weeks for sign-off on a policy change, and then wait additional time for a vendor or your IT team to make iterations in your decisioning processes, you’ve left your organization susceptible. Having self-sufficiency in times like these is critical – being able to use advanced analytics to optimize decisioning strategy, quickly, and then make those changes just as quickly is key. But you need the right technology in place to support that flexibility and agility.
    • 05

      When the bank is undergoing a full digital transformation, many projects and developments are done at the same time with limited resources. What does management need to pay attention to when making decisions on priorities?

      The first step is making sure that all projects have been categorized and prioritized with the entire group, and that those priorities are aligned with the overall group/organizational strategy. Alignment is key. It is very difficult to have competing projects fighting for resources (time, money, human) and this is a common challenge among financial services institutions. Allowing for a level of flexibility and adaptability is crucial – often what helps is reevaluating priorities at set intervals, every quarter for example. The largest priorities may not change often, but the smaller, more nimble priorities can (and often do), and your project management structure should be flexible enough to accommodate that.
    • 06

      Given the increasing flow of information, number of processors and variety of processors within the competitive landscape, what is the importance of increasing the number of data connections to enhance decisions towards better business outcomes?

      Increasing data connections can be helpful, but it’s worthwhile to note that we don’t want to connect to so many that it’s overwhelming. It’s not just about more data, it’s about the right data at the right time, in order to see the real value of those data sources. Getting the right level of customer data that you need to adequately support your decisioning processes is crucial. Having a broader spectrum of data available, in terms of types of data sources and variety, as well as quality, is more important than just continually adding new data sources that won’t provide any additional value to the view of your customers (and may in fact add more friction to the journey). Data sources that allow for a strong level of automation in your decisioning processes will also be more valuable than those that require manual intervention or human oversight (which add complexity and slow down the process).
    • 07

      Will the current path of digital transformation that banks are on (locally and globally) lead to more financial stability or more future crisis scenarios (like Silicon Valley Bank)?

      Financial stability is important – we weathered this during the financial crisis in 2008, and there are continual efforts to combat any instability. One of the things that led to that instability is the fracturing of the value chain. When you have new players who are so specialized and who don’t see the whole banking picture, there are inherent risks. On the other hand, when you have large incumbents who do everything in-house, they see the whole picture, but they can often be very rigid and slow to move or make changes, which has different risks and implications on financial stability.

    Balance risk with opportunity across the customer lifecycle.

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    Transforming the Customer Journey: How Unified Technology Can Enhance Experience and Efficiency

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    Transforming the Customer Journey:
    How Unified Technology Can Enhance Experience and Efficiency

    • Mark Collingwood, Vice President Sales and Managing Directof Europe, Provenir

    As consumer duty mandates higher transparency and fairness, many large organisations face the pressing challenge of modernising their complex and costly legacy systems. These traditional systems, characterised by siloed architecture, not only inflate operational costs but also impede the development of a seamless customer experience. To stay competitive and compliant, businesses must simplify their technological frameworks to better understand and serve their customers throughout the entire journey.

    The Problem with Siloed Architectures

    Legacy systems in large organisations often operate in silos — separate, and sometimes incompatible systems that handle different aspects of the business. This fragmentation leads to several issues:

    • Inefficiency and High Costs: Each silo may require separate maintenance and integration efforts, which increases overall operational expenses.

    • Impaired Customer Insights: Siloed data and systems obstructs a unified view of the customer, making it difficult to tailor services effectively and personally.

    • Delayed Time to Market: The lack of agility inherent in legacy systems can slow down the introduction of new services or updates, hindering responsiveness to market changes.

    Consumer Duty as a Catalyst for Change

    Recent regulatory trends emphasising consumer duty call for greater levels of transparency and fairness. These regulations are not just legal requirements but also opportunities to redefine the customer experience. They press businesses to:

    • Enhance Understanding: By simplifying interactions and communications, making them easier for customers to understand.

    • Increase Transparency: By clearly explaining terms, conditions, and processes associated with the services offered.

    To align with these needs, re-architecting the technological and data landscape is crucial. This involves:

    • Eliminating Redundancies: Stripping away overlapping functionalities to reduce clutter and costs.

    • Adopting a Common Component Architecture: Shifting towards a unified decisioning platform that supports a broad range of customer needs, simplifying training, maintenance, and enhancement.

    • Fostering Reusability: Developing modular systems that can be quickly and easily adapted or expanded to meet emerging demands without the need for extensive customisation.

    Benefits of More Unified Technology

    By overhauling their IT architecture, organisations can reap significant benefits:

    • Eliminating Redundancies: Stripping away overlapping functionalities to reduce clutter and costs.

    • Reduced Operational Costs: Streamlined and simplified IT infrastructure lowers the total cost of ownership and operational expenses.

    • Improved Time to Market: A more agile and adaptable technology stack enables quicker rollout of new features and adjustments to customer needs.

    • Enhanced Customer Satisfaction: Timely and relevant interactions, powered by a comprehensive understanding of the customer, boost satisfaction and loyalty.

    • Improved Business Efficiency: Deploying a more simplified re-useable component-based architecture can help improve business efficiency and support an improved customer experience.

    Case Study: Implementing Unified Technology

    Consider a hypothetical financial institution plagued by dated, siloed systems. By transitioning to a unified decisioning platform, the institution could:

    • Consolidate Customer Data: Integrating all customer data into a single repository, providing real-time insights, and enabling proactive service adjustments.

    • Automate Service Delivery: Utilising common components to automate and standardise processes, reducing manual errors and operational delays.

    • Enhance Customer Interactions: Deploying advanced analytics to personalize customer interactions, thereby increasing engagement and trust.

    As consumer duty reshapes the business landscape, the push towards transparency and simplicity can no longer be ignored. By embracing a simplified, re-useable component-based architecture, organizations can not only meet regulatory demands but also set new standards for customer experience. The journey towards technological simplification is not just a compliance measure, but a strategic move that can lead to substantial competitive advantage and operational efficiency.

    For businesses ready to embark on this transformative journey, the path forward involves embracing innovation, discarding outdated practices, and viewing regulatory compliance as an opportunity for holistic improvement. Simplified technology is not just the future; it is the foundation upon which lasting customer relationships are built.


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    Breaking BaaS:
    The Sponsor Bank-Fintech Relationship On The Straight And Narrow By Taking a Page From Franchising

    • Michael Fife, Vice President – Sales & Consulting, U.S., Provenir

    The financial services industry is undergoing a profound transformation, with technology-driven innovations reshaping traditional banking models. Among these innovations, Banking-as-a-Service (BaaS) has emerged as a pivotal enabler, allowing fintech companies to leverage the infrastructure and regulatory framework of established banks to offer a wide range of financial products and services. However, the success of BaaS partnerships hinges not only on technical integration but also on fostering a collaborative relationship between sponsor banks and fintechs akin to the dynamic between franchisors and franchisees.

    Franchising as a Model of Business Standardization

    Franchisors provide franchisees with a well-defined blueprint for conducting business operations, encompassing everything from brand identity to operational processes. While brand identity may not be as critical in BaaS, the importance of standardized processes cannot be overstated. Similarly, sponsor banks must offer fintech partners a structured framework for conducting banking activities to ensure regulatory compliance and mitigate risk.

    Applying Franchise Principles to BaaS

    Sponsor banks must go beyond merely providing access to core banking systems and lending licenses; they must actively engage with fintech partners to establish standardized procedures for loan origination, risk assessment, and compliance. This entails defining acceptable risk criteria, specifying data sources for lending decisions, and establishing governance mechanisms for risk management.

    The Imperative of Transparent Collaboration: Cloud-Native Decisioning Platforms Are One Facilitator of Collaboration

    Achieving transparency and collaboration in risk management requires robust technological solutions. Cloud-native risk decisioning software offers fintechs and sponsor banks the necessary tools for data ingestion, decision and fraud orchestration, and manual review processes. Moreover, these platforms facilitate administrative functions such as user access management, version control, and auditing, thereby streamlining collaboration between a sponsor bank and its compliance team and the fintech, ensuring compliance with regulatory requirements.

    Aligning Market Demands with Regulatory Compliance

    By leveraging an industry-recognized risk decisioning platform, sponsor banks and fintechs can collaboratively define risk policies according to universally-recognized standards that balance market demand for a given fintech product with regulatory obligations. This collaborative approach not only enables fintechs to address a specific market need but also ensures that sponsor banks adhere to regulatory frameworks, such as capital requirements, data privacy, and KYC/BSA/AML requirements, among other banking regulations.

    Navigating Challenges and Seizing Opportunities:

    • Overcoming Regulatory Hurdles

      One of the primary challenges in BaaS partnerships is navigating the complex regulatory landscape governing the financial services industry. By establishing clear governance structures and leveraging cloud-native technology solutions that enable oversight and rule-based administration, sponsor banks can mitigate regulatory risks and foster trust with fintech partners.

    • Seizing Opportunities for Innovation

      BaaS partnerships present opportunities for both sponsor banks and fintechs to innovate and differentiate themselves in the market. By collaborating on product development, leveraging advanced analytics, and embracing emerging technologies such as blockchain and artificial intelligence, partners can deliver cutting-edge financial solutions that meet evolving customer needs.

    As the financial services industry continues to evolve, the collaboration between sponsor banks and fintechs in the realm of BaaS will become increasingly vital. By embracing a franchisor-franchisee dynamic characterized by standardized processes, transparent collaboration, and technological innovation, partners can unlock the full potential of BaaS and drive positive outcomes for customers, regulators, and stakeholders alike.


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    Islamic Banking and Financial Services: Where Tradition Meets Innovation

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    Islamic Banking and Financial Services:
    Where Tradition Meets Innovation

    • Allison Karavos

    Embracing Advanced Risk Decisioning in the Digital Age

    Islamic banking, a rapidly evolving facet of the financial services sector (primarily in the MIddle East), presents a unique blend of traditional Islamic principles and modern financial practices, challenging professionals in finance, lending, credit, and risk decisioning to rethink their strategies. At its core, Islamic banking adheres to Sharia law, which has a number of implications on everyday financial transactions. 

    Some of these principles include:

    • Paying or charging interest (riba) is prohibited (instead of interest, islamic financial institutions essentially profit-share with a model called equity participation)

    • Maisir (gambling) is prohibited

    • Gharar (excessive risk) is also prohibited

    • Financial transactions must be backed by tangible assets

    • Investments in industries deemed ‘unethical’ is not allowed

    These rules and frameworks create a complex landscape of commercial transactions, with stricter parameters and compliance procedures governed by principles such as profit and loss sharing and risk-sharing models, distinguishing it significantly from conventional banking systems. For financial institutions navigating these intricacies, the integration of sophisticated automation becomes not just a competitive advantage but essential. Automation technologies, including risk decisioning software, can play a pivotal role in ensuring compliance with the dynamic regulatory requirements and adapting to evolving consumer demands. They offer the agility needed to align with nuanced, principle-based transactions while maintaining efficiency and competitiveness in the global market. And the Islamic finance sector continues to expand, with more than 560 banks and over 1,900 mutual funds around the world that comply with Islamic principles. Between 2015 and 2021, Islamic financial assets grew to about $4 trillion from $2.17 trillion and are projected to rise to roughly $5.9 trillion by 2026, according to a 2022 report by the Islamic Corporation for the Development of Private Sector (ICD) and Refinitiv. Global Islamic finance assets are said to have reached $4.5 trillion USD in 2022 and are projected to reach $6.7 trillion USD in 2027. The industry has more than doubled since a decade ago, and almost 60 countries now have Islamic finance regulations, with several new markets in Asia and Africa exploring the introduction of Islamic financial services.

    Leveraging technology to harmonize these rich traditions with the demands of modern finance has become increasingly crucial for institutions aiming to thrive in this distinctive financial landscape.

    Islamic Banking: Complex Needs Means Complex Challenges

    Looking deeper at the complexities of Islamic banking reveals numerous challenges faced by financial institutions. One significant hurdle is the inherent variability in Islamic finance principles, which can differ across regions and jurisdictions. This diversity, influenced in part by differing interpretations of Sharia law, leads to variations in products and services offered, complicating compliance and operational strategies. Additionally, the Islamic finance sector, like all of finance, is subject to continuously evolving regulations, adding layers of complexity for institutions striving to remain compliant. On top of that, there are often regional differences in regulations and legislation, adding additional legal complexity on top of the cultural challenges, affecting the overall structure, delivery, and compliance requirements of Islamic financial services. And let’s not forget operational costs, which can be prohibitive when considering the requirements to align financial products and services with Islamic banking principles/guidelines – often needing specialized expertise and processes to ensure all nuances are covered. 

    This is where the use of outdated or legacy risk decisioning software can pose a significant threat – not only to the overall adherence to Islamic banking principles, but also to the overall customer experience, which, as we all know, is key to customer retention and loyalty. Traditional risk management and assessment tools, typically designed for more conventional financial services systems, can fall short in decisioning accuracy when faced with the unique considerations of Islamic banking. This can lead to overall operational inefficiencies, increased risk exposure (including credit losses and fraud), and an inability to adequately meet the demands of your customers, especially when it comes to tailored product offerings and frictionless experiences across the entire journey. And introducing unnecessary (and unwelcome!) friction in the customer experience is a surefire way to negatively impact customer satisfaction and overall retention.

    Embracing Advanced Risk Decisioning Technology

    But the good news is, investing in advanced, automated, adaptable risk decisioning technologies can enhance the customer experience and help you maintain a competitive edge, while still effectively managing your risk in an increasingly complex financial landscape. Upgraded risk decisioning tech, especially when it includes embedded intelligence like AI/ML, can transform your risk management strategy, while still ensuring compliance with Islamic banking principles. AI can analyze vast amounts of data, identifying patterns and risks that may be overlooked by traditional evaluation methods, enabling a more holistic, accurate assessment of risk and your customers – and more compliant decision making. The integration of advanced technologies also streamlines your risk processes, reducing the time and effort required to accurately evaluate your customers. Gaining this efficiency means lower operational costs, but it also helps to accelerate the delivery of financial products and services to your customers, greatly enhancing the overall experience and helping ensure customer satisfaction and loyalty. Islamic banking customers, like customers of just about any industry these days, expect fast, personalized offers – which isn’t easy to do with more legacy tech. 

    Besides these obvious benefits, updating your legacy risk decisioning technology also helps to support further innovation within the Islamic banking sector. Like everything else in finance, change and evolution is the name of the game – but it’s very difficult to remain agile and adaptable with outdated, siloed systems and processes. Leveraging more flexible tech, especially with embedded intelligence, enables the rapid development of new, compliant financial products and services that meet the evolving needs of both customers and the market as a whole. Consider advanced risk decisioning a dual-force, empowering Islamic financial institutions to navigate complex compliance requirements with ease, while also fostering an environment of innovation (and bonus, don’t forget that whole customer satisfaction piece). Mitigating risk and driving the industry forward in a way that aligns with both traditional Islamic principles and modern customer expectations means you can strike that necessary balance in this unique environment.

    Future-Proofing Your Decisioning Technology

    So if you’re convinced of the importance of upgraded technology to support risk mitigation, customer experience, and adherence to Islamic banking guidelines… what can you do to ensure you are implementing the best risk decisioning technology that not only meets your needs now, but also supports your needs in the future?

    Some key things to keep in mind are:

    • Data: Ensure you have access to a rich variety of global data sources, including both traditional and alternative data, and that your data can be easily accessed and integrated into your risk decisioning workflows.

    • Ease-of-Use: Do you need to rely on vendors or your IT team to implement any new changes in your decisioning processes, or can you make changes yourself? Look for credit risk management software that is business-user friendly, with an intuitive, low-code UI, drag-and-drop processes, and easy visualization so you can make changes in minutes. 

    • Embedded Intelligence: Make sure you have access to your decisioning data and the ability to use advanced analytics and embedded intelligence to understand your decisioning performance and optimize accordingly.

    • End-to-End: Can you make decisions across the entire customer journey, all in one platform? Eliminate siloed processes and disparate systems with end-to-end decisioning that allows you to onboard customers seamlessly, detects and prevents fraud, optimizes collections treatment strategies, and enables personalized, relevant product offerings (including upsell/cross-sell opportunities) across the lifecycle.

    • Case Management: Not every decision can be automated – but with case management integrated into your decisioning, you can streamline referral handling for frictionless investigations.

    Just like Islamic banking beautifully blends tradition and innovation, so too can your risk decisioning technology. Incorporating advanced technology in your risk assessments, including AI/ML, allows you to respect the traditional values of Islamic banking while embracing technological innovation to meet the dynamic needs of today’s customers. And if you can’t replace all existing technology with upgraded solutions, start small and integrate new processes and solutions alongside existing systems to start reaping the benefits of automation as quickly as possible. 

    By integrating these advanced technologies, you can foster an environment of innovation, driving the industry towards a more inclusive, efficient, and forward-thinking future.


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    Lending to Live: Navigating the Cost of Living Crisis for Lenders in the UK

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    Lending to Live:
    Navigating the Cost of Living Crisis for Lenders in the UK

    • Allison Karavos

    In the wake of the ever-growing concern surrounding cost of living in the UK, consumers are finding themselves at the heart of financial turbulence, grappling to maintain stability and meet basic needs. As prices for essential goods and services continue to rise, consumers are finding it increasingly difficult to make ends meet, presenting not only a challenge but also an opportunity for lenders and credit providers to play a pivotal role in supporting these consumers, especially the underserved segments of society. 

    In this transformative landscape, AI-powered, data-driven decisioning platforms can play a pivotal role in reshaping lending practices to be more responsive, inclusive, and empathetic.

    Understanding the Cost of Living Crisis

    Recent statistics paint a sobering picture: as of early 2024, inflation rates have soared, significantly impacting the prices of food, energy, and housing. This has resulted in a notable increase in the cost of living, outpacing wage growth and putting immense financial pressure on many households. For instance, the Consumer Prices Index (CPI) rose by 4% in the 12 months to January 2024. The cost-of-living crisis in the UK is not just a financial challenge; it is a daily struggle for individuals and families trying to navigate rising expenses, stagnant incomes, and economic uncertainties. From housing to healthcare, education to groceries, every aspect of life is impacted, putting immense pressure on consumers to make ends meet.

    The Consumer-Centric Approach

    In challenging times, the consumer must be at the forefront of any meaningful solution. Lenders need to reevaluate their approach and recognize the importance of a consumer-centric strategy. This involves understanding the unique financial situations of borrowers, acknowledging their challenges, and tailoring lending solutions that genuinely support their needs. And it’s not just about short-term solutions, but about offering support and solutions that go beyond traditional lending models, focusing on long-term financial well-being and stability.

    Adapting to Evolving Consumer Needs: Leveraging AI and Data-Driven Decisioning

    The ability to adapt quickly to changing circumstances is crucial in addressing the cost-of-living crisis. One of the most powerful tools at the disposal of lenders in addressing the cost-of-living crisis is technology, specifically AI and data-driven decisioning. 

    A data-driven, decision intelligence platform enables lenders to assess and respond to evolving consumer needs in real-time, ensuring lending institutions can remain agile and responsive. 

    More specifically, these technologies help lenders:

    • Better Understand Consumer Needs: By analyzing data patterns and consumer behavior, lenders can gain insights into the financial challenges that different segments of the population are facing.

    • Personalise Financial Solutions: AI can help tailor financial products and services to meet the specific needs of individual consumers, providing more relevant and effective support.

    • Improve Risk Assessment: Enhanced data analytics can lead to more accurate risk assessments, allowing lenders to offer credit to a broader range of consumers, including those who might be underserved by traditional credit scoring models.

    • Offer Proactive Financial Guidance: AI-driven tools can provide consumers with proactive and personalized financial advice, helping them manage their finances more effectively in tough economic times.

    Supporting the Underserved

    One of the key challenges in the lending industry is reaching and supporting underserved communities. A data-driven approach helps bridge this gap by enabling lenders to evaluate risk more accurately, extending financial support to those who might be overlooked by traditional lending methods. This inclusivity is not just a strategic advantage but a social responsibility that aligns with the urgent need for financial equity.

    With the right data at the right time, lenders can support underserved groups by:

    • Developing products and services tailored to their specific needs

    • Using alternative data in credit decisioning to include those with thin credit files

    • Providing financial education and guidance to help them manage their finances

    Looking Ahead: A Compassionate Future of Lending in the UK

    Looking ahead, the lending industry in the UK is expected to undergo significant changes. We can anticipate a greater emphasis on responsible lending, with a focus on sustainability and long-term financial health. Technology, particularly AI and machine learning, will continue to play a critical role in shaping the future of lending. These advancements will enable lenders to offer more personalised and flexible financial solutions, making finance more accessible and inclusive.

    In conclusion, the cost-of-living crisis in the UK presents both a challenge and an opportunity for lenders and credit providers. By adopting a consumer-centric approach and leveraging technology, they can not only support consumers through these difficult times but also pave the way for a more inclusive and sustainable future in lending. Lenders must evolve to meet the pressing needs of consumers. As we navigate these challenging times, the integration of technology and empathy will undoubtedly shape a future where lending serves not just the financial well-being of individuals but the resilience of the region as a whole.

    Looking for more info on how a holistic, AI-powered decisioning platform can help evolve your lending strategy?

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    Bridging the SME Funding Gap

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    Bridging the SME Funding Gap

    • Allison Karavos

    Ten Companies Embracing Lending Innovation

    SMEs remain the powerhouses of most economies, both global and regional. But it’s often still difficult for them to get the funding they need to thrive. How can we bridge the $5.2 trillion global funding gap for these deserving yet underserved businesses? And how can lenders expand into this high-demand market segment?

    By embracing digital transformation and implementing intelligent risk decisioning, loan providers can ensure greater accuracy and agility when making lending decisions for SMEs. While there is still much untapped potential in the industry, more and more lenders are willing to embrace innovation, better serving the needs of SMEs without increasing their risk. Check out our list for some of the SME lenders leading the way. 

    Faster, More Agile Loan Approvals

    SME lenders across the globe are trailblazing new, future-proof ways to serve SMEs and transform formerly clunky, complex application processes into streamlined, optimized ones. Utilizing innovative tech can enable you to automate credit decisioning to provide accurate, real-time approvals, allowing SMEs to gain access to funds quicker than ever before. By automating data collection, risk decisioning and pricing, lenders can enable faster approvals and ensure funding is in hand within a matter of only minutes.

    Balance risk with opportunity across the customer lifecycle.

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    Guest Post: How generative AI is transforming due diligence

    GUEST POST

    How Generative AI
    is Transforming Due Diligence

    • Chris Green, CEO, Xapien

    The Importance of Knowing Third Parties

    The role of compliance is to prevent actions that could break regulations or lead to any financial, reputational, or other risks that sit outside an organisation’s risk threshold. This entails having a comprehensive understanding of an organisation’s counterparts — clients, suppliers, and investors — to spot inconsistencies and potential red flags that point to regulatory or reputational risks. Only then can organisations make strategic decisions.

    The work of compliance professionals hinges on the information accessible to them. Initially, this was confined to official state registries and government records like passports and incorporation documents. Over time, Politically Exposed Persons, sanctioned entities, and other risks surfaced, so databases were created to check against these risks.

    However, in today’s digital landscape, the surge in publicly available information demands that compliance professionals extend their search to billions of internet pages for a comprehensive understanding of their counterparts. 

    This explosion of data has made the role hugely challenging and time consuming, with many compliance teams simply unable to afford deep due diligence across the entire indexed internet. Instead, they rely on traditional databases which limits what an organisation can know, and a few cursory internet searches. This exposes organisations to massive risk

    Whether harnessing internet data, or sticking to databases, the compliance process is time-consuming. Teams must review lengthy PDF reports, sift through numerous false positives, and read multiple pages to determine the relevance of data to the subject. The result? A slow compliance process that often takes place at the end of sales conversations, causing tension in relationships with business teams awaiting a decision.

    Now, imagine if compliance professionals had the tools to reveal comprehensive insights about potential clients. What possibilities could this unlock for the entire business? These insights could be seamlessly shared across the organisation, enhancing sales conversations and transforming compliance from a business prevention department into a business enabler. 

    Due diligence could become the initial step rather than the final one in a sales process. Sales teams would depend on compliance to provide essential insights about potential clients before committing substantial time and effort to prospect conversations.

    Automating Due Diligence with Generative AI

    AI makes this possible. By connecting traditional data sources with the vast online information about third parties, compliance professionals who use Xapien’s AI tool can gain deep understanding of their counterparts in minutes, not days.

    Our AI tool efficiently searches trillions of web pages, blending compliance data with open-source information for a nuanced understanding of third parties that goes beyond databases and watchlists. Using machine learning techniques, Xapien reads and extracts key insights from web pages. It does the grunt work that slows compliance teams, such as reading and reviewing to ensure the information gathered is directly related to the subject. 

    The next job of the compliance team is usually to write the report. Again, Xapien already does this. It writes concise summaries that are fully-sourced down to sentence level based on the information it finds. Huge time savings mean that Xapien reports can be run as the first, and not the last step in any sales or client onboarding process. 

    Running third parties through Xapien at the beginning of the compliance process helps identify early red flags. This proactive approach allows compliance teams to catch risks early in the process, preventing teams from investing resources in a deal that might not go ahead, but also unlocking useful insights about clients that the sales team can use in their conversations.

    Eliminating multi-page PDFs and false positives enables compliance teams to focus on strategic thinking based on the information already analysed by Xapien. Having these sharable reports facilitates quicker decision-making with the business team on how to proceed. 

    One Xapien customer, a compliance team in a private equity firm, used a tool that added two hours for each new screening. Now, it takes an additional 10 minutes. This streamlined process ensures no delays in deals, enabling the business team to proceed more efficiently.

    Find Xapien on the Provenir Data Marketplace

    Partnering with Provenir has strengthened Xapien’s foothold in the AML-regulated sector and helped more businesses access fully-automated enhanced due diligence (EDD) reports on individuals and organisations. By automating manual research, it helps compliance teams scale their operations and, most importantly, catalyse revenue growth. If you’d like to learn more about how Xapien could help your organisation, get in touch with our team of experts here.

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    Enhancing Financial Services Through Case Management

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    Enhancing Financial Services
    through Case Management

    Enabling Frictionless, End-to-End Onboarding

    In the ever-changing world of financial services, case management can be a critical component to success when it comes to mitigating risk of loss, maximizing the value of your customers and ensuring frictionless onboarding experiences. By seamlessly integrating case management solutions into your decisioning processes, you can streamline operations, reduce fraud losses, and enhance customer experience in a variety of ways. The case management market on its own is expected to grow to $9.44 billion by 2026 at a compound annual growth rate (CAGR) of 9.54%. And the idea of case management has a profound impact on a variety of roles within your lending/onboarding functions, including application agents, fraud investigators, and credit risk underwriters. So we’re looking at the ways case management can enhance your business growth and help enable frictionless, end-to-end onboarding that get you to market faster and improve the customer experience along the way.

    Case management in financial services refers to the process of handling manual review of client cases effectively and efficiently, from initiation through to resolution (whether that’s an approval or a rejection of a particular application). But it’s made infinitely more powerful when it’s integrated with an intelligent decisioning solution that can easily expedite cases when needed and review everything all in one place.

    Integrate Seamlessly with Decisioning

    Your risk decisioning solutions, in whatever form they take, are critical for making numerous decisions in the life of your customers – including lending, fraud screening, onboarding, customer/portfolio management, and collections. But despite the advances in intelligent decisioning, not every situation can be automated. Integrating case management for the situations that need human intervention makes both solutions exponentially more powerful – you can easily expedite case handling and re-trigger automated decisioning when it’s ready, and by having most applications automated you can shift and focus resources on the cases that need it most. And when you integrate case management into real-time decisioning, you eliminate the siloed views that can be common in the financial services world (particularly when dealing with complex legacy technology). Seamlessly integrating manual intervention into your automated decisioning flows enables one truly holistic, end-to-end decisioning solution and frictionless onboarding experiences. 

    Streamline Onboarding, Reduce Fraud Losses, and Treat Customers Fairly

    Sounds like a tall order for one simple case management solution? It’s not. Over half of fraud and risk executives at financial services firms are not entirely satisfied with their current case management systems. 

    Think about the different roles that necessitate manual intervention and case handling, and there are very specific advantages to both them and your customers. 

    Application Agents: Application agents face the challenge of processing applications quickly while still maintaining accuracy. With case management seamlessly integrated with your existing processes, your application agents can create and amend applications, manually enter and update application information, re-trigger decisioning processes when needed, view everything in a summary dashboard, and ultimately streamline the onboarding process – impressing your customers in the process.

    Fraud Investigators: Fraud threats continually evolve, and the stakes (and risk of losses) are high. According to TransUnion, from 2019-2022 there was an increase of 39% in cases of fraud attempts in financial services. Your fraud investigators can more accurately investigate fraud rings with the ability to manually intervene, and better prevent losses. They can perform a deep-dive into decisioning data, execute roles-based controls and fraud checks, and benefit from queue management to ensure the most efficient processes – and reduce overall fraud losses as a result. 

    Credit Risk Underwriters: Credit risk underwriters are responsible for fair and balanced risk assessment of each and every applicant. Ensure that your underwriters can manually action referrals when necessary, review and understand risk policy rules, attach documentation and notes for visibility, and drive further downstream actions after review – enabling the ability to treat customers and their unique situations fairly and compassionately. 

    Implementing Case Management Solutions

    Implementing case management in financial services involves careful planning and execution. It’s essential to choose the right system that aligns with your needs. The challenges, such as data integration and staff adaptation, can be mitigated through a phased implementation approach – or by ensuring that you have selected a solution that integrates seamlessly with your decisioning and data solutions, eliminating siloed environments and inefficient processes. Technology that includes AI, machine learning, and advanced analytics will also help further streamline processes and enhance decision-making accuracy, enabling more efficiency and bias-free decisions across the entire organization and the complete customer lifecycle. 

    Ensuring you have a comprehensive case management solution enables improved efficiency, reduced risk, better compliance and fraud decisioning, and enhanced customer satisfaction. The ability to optimize actions and interventions at every step of the onboarding process allows you to more effectively balance risk with opportunity across the entire lifecycle of your customers. Prevent losses, maximize value, and remove friction in all aspects of your onboarding – and watch your business grow as a result.

    Balance risk with opportunity across the customer lifecycle.

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