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Discover how the digital revolution is transforming the agricultural lending landscape Agriculture is reaching new heights with AgriTech leading the charge. The digital shift is being termed as the third green revolution in India. While digital innovation is helping businesses explore untapped markets in agriculture, simplified lending for farmers has helped banks emerge as benefactors in this transformation. For expansion in rural markets, digital lenders need to understand how farmers’ successes are a direct outcome of higher accessibility to the booming digital ecosphere. In rural areas, new technologies have helped agriculturists change their outlook toward markets and adapt profitable practices for maximized produce. Here, multiple startups have connected the dots to make way for new success stories. Majorly, the dots are eco-friendly technology-driven farming processes, data-backed farming choices, and farmer empowerment at every step. Currently, the Indian agriculture market has been valued at INR 55,994 billion in 2020 and is expected to grow to an approximate value of INR 111,916 billion by 2026. In one of the biggest global agriculture markets, one question that’s benefiting banks is – how can we simplify borrowing for farmers? To answer this, a close look at technologies that farmers are adopting could help banks better understand the data that helps lend better. How Is India Changing: Who’s Stepping in with Big Ideas? Firstly, we need to recognize the business outlook towards the sector. It's following a global shift. With environmental and sociological consciousness on the rise, every partaker recognizing business opportunities aims to adhere to ESG investing. ESG investing - Environmental, Social, and Governance investing is used to screen investments based on corporate policies and to encourage companies to act responsibly. For investors, this translates to – maximum productivity from an eco-friendly approach, which also includes the economic well-being of the most crucial contributors – the farmers. Following suit, the biggest grocery deliverers are offering farm-to-home products, and are doing their part in supporting farmers. Moreover, the government of India has pushed for entrepreneurs to step in and take decisive actions for the strategic growth of farmers. One key recommendation is the project called ‘Startup Agri India,’ under which businesses have opportunities to innovate fearlessly for agriculture advancement. The act will be a part of the government’s critical plan to ‘increase farmers’ income by 2022, under which Banks could keep an eye out for the following goals set for farmers' well-being – Growing more crops from the same land Improving the quality of milk, meat, and eggs Using resources more effectively Spending less money on making products Growing crops more often on the same land Growing different, more valuable crops Getting better prices for the products farmers sell Moving from working on farms to other jobs in production What Technologies Simplify Lending in Agriculture? A silent revolution is underway for agriculture, and banks are the biggest benefactors with their offerings of digital loans. But as the market’s competitiveness increases, multiple lenders will soon step in to help 145 million aspirational rural customers whose cross-selling opportunities grow by the day. Insurance-Secured Digital Loan Processes for Crop Majorly, crop insurance is catching on as a preference. Insurance firms and banks could make use of advanced remote-sensing technologies for timely and accurate estimations. In India, data analytics companies like SatSure integrate satellite, weather, and IoT (Internet of Things) analytics to help farmers with financial security and crop insurance. Currently, similar solutions are being used by many banks and insurance firms. Internet of Things (IoT) for Better Predictions Further, as digitization increases, banks, governments, and other stakeholders can now tap into the vast world of data analytics for informed decisions on policies, products, processes, cross-selling opportunities, etc. The increasing sophistication of sensors, internet-enabled connectivity devices, simplified software applications, and cloud data storage, together, facilitate data to be captured, stored, and processed by decision-support tools aiding in planning for agricultural activities that offer the best outcomes. Precision farming is an upcoming application of IoT in Indian farming. Agricultural practices can be planned extremely well by including processes for real-time crop and soil condition monitoring, plant health tracking, weather prediction, and more. An end-to-end IoT solution for the management of fresh foods, Qzense uses IoT for fast and precise quality grading by capturing insights on spoilage, shelf life, and ripeness, ultimately helping farmers achieve higher margins from the same produce. Predictive Analytics for Crop, Farms, Climate, and Markets A majority of agricultural markets are imperfect, as they lack good communication infrastructure, especially information databases. Moreover, the prices of crops are unknown at the time of planting as well as knowing their demand at the time of their sale is difficult. This is changing, as the industry can now use predictive analytics for better calculations like understanding how many other farmers are planting a specific crop as well as how will average yields fare in any given year. Risk-based evaluation software for lending to agri-sectors identifies distress when banks factor in a structured risk assessed at the farmer's level. It also helps in improving targeting, transparency, de-duplication, efficiency, and inclusiveness under farmer welfare programs. Apart from that such software can also account for, major risks like climatic risk in the occurrence of drought, excessive rainfall, temperatures, hailstorms, etc.; risk of pests and diseases; intrinsic risks related to farm management. Explore our digital lending solution, CRisMac Krishak, an agri lending solution, and discover how it empowers banks to simplify lending for farmers and drive growth in untapped agri-markets through digital innovation. Learn more about the crucial role of enhanced accessibility to the digital ecosystem for rural market expansion and farmers' success in India. Contact us to know more about CRisMac Krishak.

Navigate the Complexities of Data Migration and Decommissioning for Legacy Banking Systems Successful data migration is a critical activity for Digital Transformation in Banks. Many times data migration can be challenging due to insufficient time and resources being allocated, resulting in a not-so-ideal Data Migration Plan (DMP), along with insufficient testing and support. Top Data Migration Challenges in the Big Move 1. Lack of well-defined cloud migration strategy: Migrating business applications and data requires careful strategy and planning. The most methods for migrating are — Lift and Shift: Moving applications and infrastructure from on-premises to the cloud with minimal changes. Replatforming: Making some modifications to the existing applications for better compatibility with the cloud environment. Refactoring: Restructuring applications by leveraging cloud-native services and architectures for optimal performance. Repurchasing: Replacing existing applications with cloud-based software-as-a-service (SaaS) alternatives. Retiring: Phasing out outdated applications and systems that are no longer necessary. The challenge lies in ensuring a seamless transition to the cloud while addressing complexities such as data security, application compatibility, and operational disruption. 2. Data security and compliance risks: Companies are still hesitant about handing over their data to third parties. A recent SANS Report shows that 56% of companies are concerned about cloud security. If data is exposed cyber attacks can cause serious disruptions. 3. Financial cost of the cloud migration process: Cloud migration is a costly process, especially if the company fails to analyze its financial potential. The cost of using cloud platforms plus moving to the clouds & momentary risks involved from slow adoption can be a hindrance in the process. As challenging as it can be, it is unavoidable. For Banks and Financial Institutions, to shift to cloud migration, the most important is to build a strategy and use it to the right potential. Decommissioning Legacy Systems in Financial Institutions In data migration processes it may be necessary to Decommission Legacy Systems for multiple reasons. It is essential to implement transferrence stages to maintain functionality without any data loss. Decommissioning processes may be necessary in scenarios where legacy systems are no longer compatible with emerging use cases, commonly, for inclusions of AI/ML-powered solutions. However, it is not always mandatory for every data migration. Here are a few situations when decommissioning processes may be necessary: 1. Obsolete or Outdated Systems: When migrating data from legacy systems that are no longer supported or maintained, it is advisable to decommission those systems. Continuing to operate outdated systems may result in increased security risks, higher maintenance costs, and limited scalability. 2. Consolidation and Rationalization: Organizations undergoing a consolidation effort, such as merging multiple systems or streamlining operations, may need to decommission redundant processes. This helps to eliminate duplicated efforts, simplify workflows, and optimize resource allocation. 3. Transition to Cloud or New Platforms: When migrating data to the cloud or transitioning to new platforms, decommissioning processes can be beneficial. Legacy systems may not integrate seamlessly with cloud environments or lack compatibility with modern platforms, making decommissioning a necessary step for a smooth transition. 4. Compliance and Regulatory Requirements: If certain processes or systems no longer comply with regulatory guidelines or industry standards, decommissioning becomes necessary to mitigate legal risks and ensure adherence to compliance requirements. 5. Cost Reduction and Efficiency: Decommissioning processes can contribute to cost reduction and operational efficiency. By eliminating unnecessary or low-value processes, organizations can free up resources, reduce maintenance and operational costs, and focus on more critical business areas. It is important to carefully evaluate the need for decommissioning processes during data migration projects based on factors such as system relevance, operational efficiency, cost-effectiveness, and compliance considerations. Each migration scenario may have its own unique requirements, and the decision to decommission processes should be made based on a thorough analysis of the specific situation. How Does Decommissioning Commonly Take Place? A Data warehouse is set up and ETL (extract/transfer/load) processes move information from one “soon to be decommissioned” system to the data warehouse environment. The old system is shut down systematically, and the migrated data is sourced from the modern database for future business purposes. A Streamlined Approach to Data Migration 1. Data Analysis – Examine and define the data before migration. This helps to determine the level of source information that can be included. Analyze the source and target systems by referring to end-users so that the process is fully functional. 2. Proper Allocation of Resources – Formulate a well-defined project scope by involving relevant stakeholders at an early stage for easy budget and resource allocation, and successful process implementation within the stipulated timeline. 3. Data Integrity Validation – Design contingency plans that identify and rectify ‘uncleaned’ data before its migration to the target system. This is crucial and could compromise process efficiency if not addressed in time. 4. Creation of the Migration Solution – Define the transformation logic on the data chosen for migration, and code the data migration logic to move the transformed data. 5. Testing and Verification – After the migration is complete, create test data in a test database, and subject it to various test scenarios. This reduces the risk of running into issues later when it will be greatly difficult to rectify them. Discover our comprehensive application migration services that encompass both legacy system decommissioning and seamless data migrations. Our Banking Fintech expert team specializes in streamlining your technology landscape, retiring obsolete systems, and ensuring a smooth transition to modern platforms.

DevOps brings accelerated insights, enhanced collaboration, and scalability to data solutions It’s not a new thing that fintech companies, startups, and multinationals use 'Developer Operations' – DevOps – in the ever-growing field of analytics for their BFSI partners. Pick any company offering business analytics solutions to Banks and NBFCs and you will see that they have well-structured DevOps practices. Let’s see why? DevOps practices are growing at a faster pace today. The team helps multiple financial fronts to reach strategic goals faster and profit in highly competitive markets. Majorly, elimination of delays in software development is possible because of DevOps. With these teams in place, developers can respond to business needs faster. As DevOps is a must for BFSI data analytics solution partners, every analytics provider can need a few essentials in place. The benefits that follow are essential for better deployment of advanced analytics solutions, and further, maintenance of these systems in complex data environments like customer relationship management, lead generation, recovery/collections, and data-driven investing. Business Benefits for BFSI Companies • Faster time to market for new functions or products • More stable and resilient operating workspace • Improving inter-agency cooperation and communication • New innovations and new features for customers Technical Advantages for Data Analytics Partners • Real-time problem solving • Less human intervention and errors • Less complex project management process • Streamlined product life cycle with continuous delivery Data Culture Development • Better, productive, and synchronized teams • Skilled employees for specific tasks • Better knowledge sharing between departments What Do You Get from Analytics Partners Who Use DevOps Strategies? When your BFSI analytics partners incorporate DevOps strategies into their operations, it can bring several benefits and advantages. Here are some things you can expect from analytics partners who utilize DevOps: Higher Customer Satisfaction DevOps has brought a lot of change in how the Development, Operations, and Testing teams work with each other to ensure faster, reliable, and secure delivery of software. It has enabled enterprises to respond faster to changing customer needs and market requirements in the digital age. Customer Experience is a guiding torch for DevOps. Improved Collaboration The main point of opting for DevOps is to remove silos that hinder workflows and improve the relationship between development, operations, and quality assurance teams. Once DevOps processes and principles are put into place, the drive toward automation becomes easier as teams work iteratively toward the standardization of collaboration. Agile and SCRUM Methodologies The flexible design of small, intuitive development steps aligns well with the DevOps approach which eventually leads to even faster deployments. Combining DevOps with an Agile approach helps easily incorporate feedback and customer reviews. Instead of wasting time developing a complete function that could be redundant. CI/CD Practices Continuous Integration (CI) is a core practice that integrates code changes from different sources into a central repository. It collates code changes as needed and uses automated tools to validate code correctness which is achieved through a source code version control system. The reason to incorporate CI is that it makes it easier to highlight bugs and quality issues in less code. Continuous delivery (CD) begins when continuous integration is complete. Continuous delivery allows getting code from constant integration into a production environment. It makes software and deployment smooth, low-risk, and can be done quickly. 'Continuous Deployment' is the next step that combines continuous integration and continuous delivery to make software updates automatically available to users without human intervention. Hence, continuous deployment requires complete automation and also refers to the process of automatically releasing developers’ changes from the repository to production, without the need for developer approval for each release. Are you ready to harness the power of DevOps-driven solutions with modern cloud platforms? Look no further! Our team of expert banking fintech professionals specializes in connecting businesses with the right cloud solutions. Experience the advantages of DevOps in data analytics by partnering with us today. Visit our application migration page to learn more and take the first step toward unlocking the true potential of your data-driven strategies.

Discover the top banking analytics trends unlocking quicker processes and better insights For Banks data and analytics (D&A) trends demand large-scale culture shifts. As technological rollouts are taking other major industries by storm, the urgency for real-time data is intensifying. Banks are expecting more from data, leaving just one requirement open-ended – Innovation! New-age data collection and delivery use enterprise-wide data lakes and accelerate analytics processes with AI/ML-powered solutions. Because aggressive scaling up of architecture is the only way forward, a few trends that deal innovatively with this demand, have emerged. Where data is second to none, staying up-to-date with trends helps envision the maximum benefits of system transformation. Since data teams play a major role in driving this, we have made a list of trends most Banks and Financial Entities should keep track of today. Increased ROI from Machine Learning Artificial intelligence (AI) and machine learning (ML) is showing no signs of slowing down. Frequently bringing new business use cases, the planned return on investment (ROI) still needs to be clearly explained as we progress into the new era of digital banking. Research shows that by 2022, 90% of banks had explicitly mentioned AI as a core analytical competency, and investments have grown consequentially. Return on Investment (ROI) in Banks will be majorly expected from these areas — Fraud Detection and Prevention Risk Management Data Analytics Customer Segmentation and Personalisation Enhanced Customer Service and Support Automated Compliance and Regulatory Reporting Operational Efficiency and Data Collaboration Cloud Computing Cloud access lets financial entities proactively store, access, and innovate with data, enabling easy scalability for future operations. Internal and third-party applications via the cloud provide them with potential cost savings and performance enhancements while enabling teams to generate insights and analytics in a more cost-effective manner. Evolving Access to Real-time Data Many key insights and correlations across finance can now be automated using machine learning (ML) and its counterpart artificial intelligence (AI). This enables credit monitoring teams to analyze much larger data sets (from hundreds of columns to millions of columns) and new sources of alternative data (e.g. social media, credit card spending data, and financials of top executives). Environmental, Social, and Governance Data The increasing availability of Environmental, Social, and Governance (ESG) data is enabling financial entities to develop comprehensive strategies for lending, credit monitoring, and collections. On a larger scale, the ability to build thematic strategies can be enhanced by the addition of ML and AI models, which help investors analyze data in real-time. Keeping up with these trends will allow you to anticipate change and manage uncertainty. It also helps proactively monitor, experiment with, or then decide to aggressively invest in key trends based on their urgency and alignment with your strategic business priorities. Stay ahead of the curve and ensure your teams are up to date with the latest trends in fintech solutions. Connect with our team of experienced banking fintech professionals today and gain valuable insights into the evolving landscape of financial technology. Contact us now to explore the possibilities of banking fintech solutions tailored to your specific needs.

Efficiently build cross-platform apps with a native-like experience using React Native Since its initial release, React Native app development has been a hot topic. After many trials and errors, Facebook adopted React Native in 2015, and it has since successfully contributed to the top mobile app development companies. According to the most recent statistics, 1.6k active developers are working hard to improve the framework, as the future of cross-platform development lies in React Native. Developers would eventually have to learn their way around the development process. Why React Native Apps? These apps offer cross-platform compatibility, allowing developers to build apps for both iOS and Android with a single codebase. Its component-based architecture promotes code reusability, speeding up development and reducing effort. With native-like performance, React Native delivers a seamless user experience, closely resembling that of native apps. By "native-like," it means that apps built with React Native have the ability to closely mimic the user interface and functionality of native apps developed specifically for a particular platform (e.g., iOS or Android). React Native achieves this by utilizing native components and APIs provided by the underlying platform, resulting in a similar look, feel, and performance as that of apps developed using platform-specific technologies. This allows React Native apps to seamlessly integrate with the native features and capabilities of the targeted operating system, providing users with a familiar and consistent experience. So, What Should be Avoided in Development? Specifically, understanding and avoiding React native app development mistakes can help maintain the users' experience satisfaction, a game-changing factor today. The mistakes made by the developers while developing React native apps are: Incorrect Estimation The app's main interface differs between iOS and Android. Forms: At this point, an evaluation of the verification layout should be established. You will need to write more code when developing an app with the React Native framework than when developing a hybrid project. Web Apps: Different backend APIs should be investigated. The program's logic, including the database structure and how things are related, should be made clear. Incorrect Redux Storage As a developer, you must pay close attention to data processing and app design. When properly organized, redux can help with data management and app troubleshooting. It's a fantastic tool for managing apps and data. Mutation of State Inside the Render Function All of the information about the element that will be displayed on the interface is contained in the data. It retrieves data from the database and displays it on the panel. In React, the set value () function accepts a new object state and compares it to the previous one. After that, merge the new and old states and distribute the data. Misapplication of Redux If the application is large, Redux simplifies debugging and maintaining app states. However, Redux should be avoided because it is time-consuming. Left "console.log" The simple console log commands make debugging the app easier. Allowing log statements within the application itself, on the other hand, will be a huge challenge. If you continue to use unsynchronized rendering logic, the JavaScript thread may become congested. All of these will eventually cause the appliance to slow down. Usage of Stateless Components Stateless components are those that do not extend any type of class. As a result, rather than using them, developers should use pure components for React Native development. Because in pure components, the process of re-rendering occurs only when a change in the states is detected. Otherwise, re-rendering occurs in proportion to the parent component in a stateless component. The appliance may occasionally malfunction or crash. When this happens, you'll lose track of all variables and may end up writing custom code instead of React. It has become increasingly important for developers to use pure features as time has passed. React Native Images Are Not Optimised You should not overlook optimizing images in React Native applications as a coder. Enhancing assists in resizing images locally before uploading them to a cloud storage service, such as an s3 server, and obtaining the CDN link via API. The picture-loading procedure is significantly faster when using this method. Ignoring the Structure of the Project A developer should never overlook or ignore the project structure. They should spend more time learning about the project in general. If they do not do this, it may have negative consequences in the long run. Developers can aspire to have a well-organized project framework by integrating good project structures with React Native development. Failure to Follow Protocol React Native provides the best react native practices that developers must adhere to. If developers deviate from standard protocols, the overall development process suffers. As a result, developers and designers must always adhere to and adhere to the standard protocols. Not Reading the Codes of External Modules External modules are frequently used by us developers to save time. They make things easier and faster because documentation is included. It helps us understand what is wrong with the module and also tells us how to fix it. Why Create Flawless React Native Apps? React Native development has all of the components to be the best framework available. The only catch here is that the developers must avoid these common mistakes when developing React native apps. React Native can make you the best in the business if you can eliminate all of the unhealthy practices and control the mistakes. Build flawless experiences for your banking customers by connecting with our expert app development team. Transform your banking services with cutting-edge solutions. Contact us now!

Software Architecture prepares banks for the future while ensuring privacy, security, and regulatory compliance In today’s era, Digital Financial markets are plagued with volatility. For Banks and NBFCs, upgraded software helps pool and process data in real-time which helps deal with unwarranted situations. In other major industries, data analytics solutions are upgraded using plug-and-play add-ons, but upgrading Financial data systems is a bit more complicated. For Financial Institutions (FIs), Privacy and security are major concerns. Even though Banks are advised to digitalize for emerging markets, a few areas require preventive measures to fend off data breaches, possibilities of fraud, and issues in regulatory reporting. Today, subscription-based software helps FIs adopt a data-first culture easily, but planning and blueprints for Solution Architecture are crucial for successful digital transformation. What is Solution Architecture? Solution Architecture is a service offering a reassessment of existing systems and developing future-proof data systems for evolving business needs. It is a process that explores the relationship between business problems and the software used to tackle these to help build blueprints for the practical adoption of new solutions. It establishes ground rules and instructions for the successful implementation and delivery of integrated system architecture. What are the Main Goals Associated with Solution Architecture? Some important questions while planning business-centric software infrastructure is, what specifics can Banks explore? Here’s a list of important goals for Solution Architecture. Standardize Customization in Coding In minimizing the amount of custom code in digital banking architecture, Financial Institutions minimize the number of legacy systems in the future. Instead, this puts light on standardized systems with minimal customized development and makes data analytics systems much more flexible. Increase Data Democratization for Teams If data analytics systems are more standardized, self-servicing in data processes will become a common practice. At the same time, data analytics systems can be integrated, streamlined, and simplified, and the removal or addition of features no longer requires the support of external vendors. Improve Cloud Integration for Storage and Applications Cloud systems are the most modern approach in terms of data-first banking solutions. It provides a faster, safer, and more flexible form of digital architecture and its applications help Banks decrease spending on problems related to upgrades for software and data security. Is there any process to build blueprints for Solution Architecture? In the world of finance, Solution Architecture plays a crucial role in creating customized software solutions that meet the unique business needs of banks and other financial institutions. As non-functional requirements such as security, performance, and reliability are analyzed, Solution Architecture ensures that the new solution delivers on its promise. In this article, we'll explore the importance of Solution Architecture in creating solutions that meet the highest standards. Customizing Solutions for Banks, NBFCs, PPIs, and more Generally, Banks and Financial Institutions already have operating systems in place, an information context, and integration requirements. Solution architecture makes sure that a new solution will be able to fit in perfectly in the existing enterprise environment. For this to be possible, data solutions and analytics vendors have to take into consideration elements of the business model. These include business processes, operating systems, and application architecture. On Understanding these aspects, it would be possible to design a specific solution that fits the environment best, and further craft implementation strategies to address business goals. Data Management – Speed, Security, and Reliability All software has to meet a number of non-functional requirements i.e., speed, security, reliability, etc. that describe the characteristics of the system or its quality attributes. While non-functional requirements depend on the complexity of each software, the most common requirement among them are security, performance, maintainability, scalability, usability, and reliability of a product. The main role of Solution Architecture here is to analyze all non-functional requirements and to ensure that the development and deployment phase delivers on its promise. Our team of banking domain experts at D2K Technologies is ready to partner with you to achieve optimal performance and efficiency through the power of solution architecture. With our deep industry knowledge and technical proficiency, we help you design and implement customized solution architecture tailored to meet your business needs and objectives. Our services help you enhance your operational agility, elevate customer experience, improve risk management, and ultimately drive profitability. You can connect with us to learn more about how our solution architecture services help to thrive in today's dynamic marketplace.

Explore what you unlock on remodeling banking application architecture for digital-first banking As Finance embraces the ‘Digital First’ environment, traditional data systems powering finance are in dire need of remodeling. The BFSI industry is on its toes for digital acceleration. And, rightly so. Keeping up with changing times allows lenders to retain customers who are now accustomed to data-backed, intuitive digital services. Banking application architecture forms the backbone of banking in the digital age. Consisting of cloud-based databases, internal data systems, and digital integrations with external lending partners, it enables advanced data analytics, inclusions of Artificial Intelligence (AI) and Machine Learning (ML), and transforms banking on multiple fronts. What Constitutes Banking Application Architecture? Banking application architecture is made up of various components and layers that work together to create a robust and scalable system. Some of the key components of banking application architecture include the front-end user interface, the middleware that connects the front-end to the back-end systems, the databases that store the data, and the analytics and reporting tools that provide insights and business intelligence. Banking Application architecture also includes security and compliance features to protect sensitive data and ensure regulatory compliance. Many major banks are already investing in and implementing modern software architecture to improve their digital capabilities and stay competitive in the industry. According to Deloitte, By 2025, 80% of heritage banking services will be delivered through modern banking platforms, enabling banks to reduce the cost of delivery by 30%. Here's what banks' goals are with banking application architecture today - Design and develop micro-service platforms and containerized components using a domain-driven approach. Implement an API gateway and an enterprise event bus for communication between systems and components. Incorporate business process automation to streamline and optimize banking operations. Leverage big data analytics and AI/ML capabilities to collect, standardize, and analyze data for better decision-making. Implement a comprehensive data management and governance framework to ensure the accuracy, security, and privacy of sensitive financial data. What is Banking Application Architecture Enabling Today? Why is Remodelling Important? Banking Application Architecture supports banking services that are highly interconnected with Digital Banking. In modern use cases, it supports new-age banking functions such as Banking as a Service (BaaS) models using Application Programming Interfaces (APIs) for payments, credit, and investments. In all, it supports - Digital Agility Services Business Process Automation Integration and Interoperability Customer Experience Security and Privacy Core Banking Functions Mobile Banking Payment and Transaction Processing Regulatory Compliance Comprehensive Analytical Insights Today, remodeling is important as cloud-based Banking Application Architecture helps increase the integration of banking solutions with partners, service providers, and regulatory institutions. In addition, modern banking application architecture also enables FIs to enhance customer experience, reduce operational costs, streamline business processes, and stay competitive in a rapidly changing industry. With the use of advanced technologies such as big data analytics, artificial intelligence, machine learning, and robotic process automation, FIs can gain valuable insights from their data, automate repetitive tasks, and make data-driven decisions. Here are three major improvements Banking Application Architecture brings to digital banking – Molds Digital Customer Experience Offers convenience, user satisfaction, and ease in interactions with Banks Updates the applications to meet and exceed customer expectations Delivers integrated services of the bank for partners to add value Cutting Costs and Operating Expenses Streamlines and enables auto-updates for portfolio management Enables high efficiency and operability for interconnected systems Increases Return on Investment, resulting in higher productivity Increase Security and Compliance-readiness Rapidly builds on requirements for new-age cybersecurity efforts Reduces costs, mitigates risk, and increases compliance with operations Helps quickly provision for bad loans, financial crimes, fraud, and more How Does Digital Banking Benefit from the Remodeling? In the rapidly changing landscape of banking, data-driven automation and insights are critical for success. But how can financial institutions achieve these goals while ensuring maintaining privacy and security? Your technology service partners should offer system integration and solution architecture services to help firstly remodel banking application architecture, including digital agility services, business process automation, and comprehensive analytical insights. These are three major areas that are driving success in digital lending. See how these three layers help financial institutions thrive in today's digital age. Digital Agility Services This service layer provides micro-service platforms such as financial work fronts, which are used to create a container and containerized components. These are mainly cloud-based. New application structures are designed and developed using the ‘Domain-driven Design’ for both – Banking Frameworks and Information Frameworks. These are loosely coupled components connected with one another or external systems through APIs and messaging by using an API gateway and an enterprise event bus – a communication system between mutually interacting software applications in a service-oriented architecture. Some examples of where this works are data management, customer onboarding, and loan management. Business Process Automation The automation layer provides a proven set of methods and tools that deliver a defined value proposition. It supports business process reengineering. Big Data Analytics and AI/ML capabilities are used to collect, standardize, and analyze data and to reuse it for business processes. A few examples are automated task management, process mining and modeling, robotic process and intelligent automation, document processing, decision management, and workflow orchestration. Comprehensive Analytical Insights The insight layer helps financial institutions get the most value from data in a cost-effective way, irrespective of its origin and data storage. This domain provides capabilities that include an AI and machine learning platform, operational and main data stores, data warehouse and data lake, hybrid cloud data access, data integration and virtualization, intelligent automation, and data governance and lineage. To learn more about how these services can help your financial institution remodel its banking application architecture, and drive digital innovation, connect with our banking domain experts today. Contact us to schedule a consultation and discover the benefits of adopting digital agility services, business process automation, and comprehensive analytical insights for your organization. Let us help you stay ahead of the curve in the fast-paced world of finance.

Banks miss out on next-gen automation and real-time analytics with non-integrated systems System Integration helps manage the complexity inherent in technology — the lack of interdependence on other systems, mainly for holistic automation and the uselessness of standalone data. It is pivotal to upgrade technology stacks to upgrade to seamlessness in data processes and to tackle new business challenges depending on increased data collaboration from multiple data systems. In the financial sector, Core Banking Systems (CBS) may usually have a sound base but seem to perform inadequately compared to the results from newer technologies. System Integration – as a standalone or a value-added service – upgrades existing systems by improving interconnectedness. This helps manage the upgradation of business processes in the shortest amount of time. How? Some benefits include improved dataflow pipelines, increased data automation, and comprehensive data visibility. What Does System Integration Improve in Banking and Finance? A well-planned roadmap to deal with unintegrated systems is based on a lender’s preparedness for the inclusion of new technologies. As we know, new digital players like Neobanks and Fintech lenders aren’t the only threat in financial segments. Blockchain, DeFi, Web 3.0, and other disruptive evolutions will soon test traditional financiers’ digital readiness. On that note, let’s take a look at what progress System Integration drives. Application Modernization Application Modernization improves traditional core systems to match evolving business requirements, mainly to help innovate fast. Building DevOps – Development Operations DevOps act as a catalyst of delivery using continuous/automated design, development, security, testing, and operations practices. Better Program Delivery Management Innovation-driven programs across all phases estimating to delivery, risk management, quality management, and project closure. Current Banking Industry Status and Requirements for Innovation Current banking systems have outdated applications that directly impact the outcomes of banking functions.  One example is astronomical amounts of data generated by banks but is managed in silos which obstructs data innovation. For Banks, System Integration helps Banks make the best use of new-age data solutions such as Intelligent Automation, the Internet of Things, Cloud-based Applications, and Advanced Analytics. D2K Technologies' Banking Fintech Experts are ready to help you unlock the benefits of system integration in your bank. By leveraging our deep industry knowledge and technical expertise, you can achieve seamless integration of your disparate systems and optimize your bank's operations. Our system integration services enhance your operational efficiency, boost productivity, elevate customer experience, and ultimately drive profitability. Don't miss this opportunity to revolutionize your bank's systems - connect with us today.

Discover the emerging trends shaping enterprise BFSI software development in 2023 and stay ahead in the industry In 2023, the enterprise BFSI (Banking, Financial Services, and Insurance) software development landscape is experiencing dynamic shifts and exciting trends that are reshaping the industry. With the rapid advancements in technology, the BFSI sector is embracing innovative solutions to enhance operational efficiency, improve customer experiences, and stay ahead of the competition. From the adoption of AI and machine learning to the rise of open banking and blockchain integration, this article explores the key trends that are driving the evolution of enterprise BFSI software development in 2023. Let us look at the trends in Enterprise BFSI Software Development in 2023. Gaining the Popularity of DevSecOps DevSecOps is a framework that positions security as a shared concern in the software development life cycle (SDLC). The name is an abbreviation for development, security, and operations. The goal is to foster a symbiotic relationship between these three disciplines by emphasizing the implementation of transparent security practices as early as possible in SDLCs. The need for security must be balanced against the need for developers to have access to quick, efficient tools. DevSecOps is both a cultural shift and a driving force to seek out new tools and automated processes within enterprise SDLCs. DevSecOps is growing at a 31% compound annual rate. Methodologies for Rapid Agile Development Rapid Agile Development is a method that entails customer collaboration, iterative and incremental development, and frequent software delivery. These methods will be used by developers to create better software in less time. It makes use of customer collaboration to create better products faster. Customers are involved throughout the development process. Customers are also involved in the software development lifecycle. Cloud Services Cloud services are becoming increasingly important in the software development industry. Cloud services are less expensive, more flexible, and provide greater security than most traditional on-premise software solutions. Companies will increasingly rely on cloud computing for their projects, and cloud services will be in high demand. This trend is expected to continue, with more and more businesses utilizing cloud services for their needs. With unlimited space, any company can store as much data as they want. Not only does this protect against hackers because no files are stored locally, but it also keeps servers operational 24 hours a day, seven days a week. The Growing Use of Blockchain Although the majority of the attention has been focused on cryptocurrency, blockchain technology has potential applications in the software development industry. More than 80% of businesses believe blockchain and other digital assets will generate new revenue streams. Meanwhile, more than 73% of respondents said they would lose competitive advantages if they do not adopt this new trend. Systems based on blockchain-oriented software (BOS) are extremely stable and secure. Its data is replicated and stored decentralized, ensuring its security. There are several layers of security to help prevent unauthorized access. Microservices Architecture A microservices architecture is a type of framework that allows developers to create applications that are independent of other services. These modules can be managed and modified independently of the other components. The cloud microservices market is rapidly expanding, according to Technavio. They forecast a CAGR of more than 25% by 2026, adding $1.59 billion to the market value. The microservices architecture is an innovative method of developing software. This new structure eliminates the need for developers to devote time to the development and maintenance of applications. They can also reuse their applications in other projects. Why Is It Important to Keep Up with The Latest Trends in Software Development? It allows you to stay ahead of your competitors. Reduce the risk of data breaches. Improve business productivity and efficiency. Reduce labor costs. Bring the latest technologies to the business and create more opportunities for ROI. The Imperative of Staying Competitive in the Tech-Driven BFSI Sector Staying competitive in this tech-driven world is always a major challenge for businesses, particularly in the BFSI sector. Technological advancements, changing customer expectations, evolving cyber security, and regulatory requirements continually shape the industry. Every year, new trends and technologies emerge in the field of enterprise software development, specifically tailored to meet the unique requirements of Finance. By embracing the latest trends in enterprise software development, you can enhance operational efficiency, improve customer experiences, and position your business for sustained success in Finance. Stay ahead of the curve in enterprise BFSI software development. Connect with D2K Banking Fintech experts to leverage the latest trends and drive success.

Exploring Advancements for Teams in Data Collection and Data Utilization Approaches for Financial Ecosystems Data communities are networks of engaged data users within an organization—represent a way for businesses to create conditions where people can immerse themselves in the language of data, encouraging data literacy and fueling excitement around data and analytics. What’s New with Data Collection-Utilization Approaches Seeping into Financial Ecosystems? ‘Web 3.0’ was originally coined as the Semantic Web by Tim Berners-Lee, the Web’s original inventor. It is an extension of the World Wide Web through standards set by the World Wide Web Consortium, being called semantic because of its all-linking web-like nature. The most fundamental goal of the Semantic Web is to make internet data machine-readable and easily interpretable by the vast number of computation devices out there. What’s New? Blockchains have become the foundation for the storage of all validated information that web 3.0 needs to become what it wishes to be. In a blockchain, information is validated by multiple contributors, making it impractical, and almost impossible to hack or manipulate information. Termed the most secure data storage method to date, Blockchain is versatile and vast ecosystems can be created to suit specifications. Redefined Digital Connectivity: Evolution of the Internet into a Safe Space New world internet is based on updated digital safety norms for sensitive data, where the concept of web 3.0 will now let the internet benefit from being – Open as its underlying infrastructures will now be built from open-source software by an open and accessible community of developers and executed in full view of the world. Trustless as the network in itself allows everyone to interact publicly or privately without a trusted third party. Permissionless as both users and suppliers are participating without authorization from a governing body. Couple this with banking, and we see a revolutionary partnership brewing. For new-age finance, Application Programming Interfaces (APIs) connect different applications built with different programming software. To reimagine banking, APIs promote a connected ecosystem with shared data sources built with blockchain for the trusted processing of customer and transaction data. A merger of APIs and Web 3.0 is what has come to be known as open banking and is being built on blockchain ecosystems to enhance digital banking with A-grade security. Naturally, for traditional banks, the competition with internet-based banking services is intensifying. More Data, Increased Data Diversity Drive Advances in Processing and the Rise of Edge Computing It may come as a little surprise that the pace of data generation continues to accelerate. In the financial services industry alone, the amount of data generated each second grew by over 700% in 2021. Upwards of 90% of an organization's unstructured data goes unprocessed, according to analyst firm IDC. Non-database sources will continue to be the dominant generators of data, in turn forcing organizations to re-examine their needs for data processing. Voice assistants and IoT devices, in particular, are driving a rapid ramp-up in big data management need across industries, including finance. The use of devices for distributed processing is embodied in the concept of edge computing, which shifts the processing load to the devices themselves before the data is sent to the servers. Edge computing optimizes performance and storage by reducing the need for data to flow through networks, reducing computing and processing costs, especially cloud storage, bandwidth, and processing expenses. Edge computing helps to speed up data analysis and provides faster responses to the user. The emergence of DataOps and Data Stewardship for fluid data-sharing practices, and challenges in managing data over its lifecycle One area of advancement is the emergence of DataOps, a methodology, and practice that focuses on agile, iterative approaches for dealing with the full lifecycle of data as it flows through the organization. Rather than thinking about data in a piecemeal fashion with separate people dealing with data generation, storage, transportation, processing, and management, DataOps processes and frameworks address organizational needs across the data lifecycle from generation to archiving. Due to widespread security breaches, eroding customer trust in enterprise data-sharing practices, and challenges in managing data over its lifecycle, organizations are becoming much more involved in data stewardship and working harder to properly secure and manage data, especially as it crosses international boundaries. New tools are emerging to make sure that data stays where it needs to stay, is secured at rest and in motion, and is appropriately tracked over its lifecycle. If you're interested in learning more about the latest data collection and utilization approaches in the financial ecosystem, then connect with D2K's banking fintech experts who can guide you through the complexities of this exciting and rapidly evolving landscape.

Building Seamless Data Access and Automation with Data Fabric in Banking: A Solution Architecture Approach Going by the definition, data fabric refers to the ‘physical topology of servers and other hardware components that aids in storage and processing of data’. It refers to the digital architecture that supports the movement of data across servers and virtual platforms and additionally aids in building resources for simplified data access to developers and analysts. Even though the term is new, the idea was conceptualized way back to define interconnectedness for data-intensive systems. Today, the term includes functions that integrate public and private architecture, cloud and on-premise systems, and external vendors’ systems to internal data storages for two goals – Simplified data access for the increasing number of data-centered teams and seamless automation for large-scale data-intensive ecosystems. Importance of Solution Architecture for Data Fabric in the Banking Ecosystem Data fabric, because of being connected to different data access points across a Bank’s system architecture, is primarily used to easily build innovative, new solutions for extensive automation of data cleansing and report generation. Modern-day solutions of application integration and data governance ensure its sustenance. Data governance and application integration, despite being independent functions play their part in data functions when – It going to connect and provide virtualized access, It’s going to automate data discovery, It’s going to build a data catalog, It’s going to create an automated data pipeline. Solution architecture can help banks build toward the creation of a data fabric in a banking ecosystem. Better collaboration Quicker fraud detection 360° Portfolio Monitoring Avoidance of Reporting Siloes Easier System Development All-rounded Information Management What’s next for Data-first Banking? The traditional banking industry is on the verge of undertaking transformations based on technologies like smart contracts and blockchain. Here, the banking industry has ushered into a new digital age, but the workforces of many banks have no way forward when it comes to innovating with data. D2K Technologies has been instrumental in propelling growth of such financial ecosystems by focusing on three important takeaways – Building interconnected ecosystems for seamless digital financial services, improving data literacy to assist in building on premise data management teams, and readying financial ecosystems for the arrival of new technologies. In conclusion, implementing an enterprise-wide data fabric architecture can enable banks to streamline their data management processes, improve collaboration, and develop innovative solutions. As the banking industry continues to evolve, it's crucial for banks to stay ahead of the curve by leveraging fintech expertise to create and implement robust data solutions. Connect with banking fintech experts today to learn more about how data fabric architecture can benefit your organization.

Learn about the benefits of Extract, Transform, and Load (ETL) for Data Analytics in Banks In today's data-driven world, the importance of ETL (Extract, Transform, Load) processes in Banking is on the rise. As Banks handle vast volumes of data from various sources, such as customer transactions, market feeds, and regulatory reporting, efficient data management becomes paramount. ETL plays a pivotal role in this domain by extracting the data from the primary source i.e., unstructured data whether it is from another database or application, and transforming the data by cleaning, structuring, deduplicating, and finally combining it. After this, Loading is the final step where the structured data is loaded into the target database. With accurate and timely data integration, banks can gain insights into customer behavior, identify trends, assess risks, and make informed business decisions. Moreover, ETL processes help ensure data quality, integrity, and compliance, which are critical factors in the highly regulated banking industry. As data complexity grows, the effective implementation of ETL becomes a strategic advantage for business intelligence in banks, enabling them to harness the power of data and stay ahead in a competitive landscape. As per The Business Research Company's report, the BI software market grew from $32.73 billion in 2021 to $39.42 billion in 2022 at a compound annual growth rate (CAGR) of 20.4%. Why is ETL Important for Banks’ Business Intelligence? Businesses rely on ETL for consolidated data to develop a holistic point of view to make better decisions and increase productivity. Here’s how. High-Level Data Mapping Leveraging data and transforming it to generate valuable insights is a major challenge when it comes to huge amounts of data. Data mapping simplifies database functions like integration, migration, data lakes, and warehousing. The function of ETL here is that it allows mapping for specific locations and helps establish a correlation between different sources. Data Quality and Big Data Analytics Huge amounts of data in their unstructured form are not that insightful and are even slightly ambiguous, even after applying algorithms. It needs to be structured, analyzed, and interpreted to build potential and ETL ensures the quality of this data in warehouses through standardization and deduplication. The tools combine data integration and processing and deal with huge amounts of data. In its data integration module, ETL assembles data from distant sources. Post integration, it applies business rules to give the analytics command of the data. Automatic & Faster Batch Data Processing Nowadays, ETL tools run on scripts, which are apace than traditional programming. Scripts are a featherlight set of instructions that administer peculiar tasks in the background. Also, ETL ‘batch processes’ data like moving huge volumes of data between two systems in a set schedule. Occasionally the volume of incoming data increases to millions of events per second. To handle similar situations, batch processing can help with timely functions. For illustration, Banks batch process the data generally during night hours to resolve the entire day’s deals. Benefits of ETL for Data in Business Applications ETL (Extract, Transform, Load) processes have a wide range of business applications, enabling organizations to efficiently integrate, clean, and analyze data from various sources. From enhancing business intelligence and reporting to facilitating data migration and consolidation, ETL plays a crucial role in enabling data-driven decision-making and optimizing operational processes. Context - Helps businesses gain deep traditional context of huge amounts of data Consolidation - Provides a 360-degree view of data for easier analysis and reporting Productivity - Provides productivity with repeatable processes without heavy coding Accuracy - Provides high accuracy in data and audits needed in regulatory compliance Every financial organization generates huge amounts of information, and we tend to perceive however necessary to keep track of almost all data. D2k Technologies expedites credit analysis processes and reduces the chance of fraud. Our ETL Services help extract and transform your data with a one-of-a-kind solution tailored to your strategies. Get in touch with D2K Banking Fintech Experts to discuss your ETL requirements and more!