We’re about to spill the beans on everything you need to know about low-code in financial services. Buckle up; it’s gonna be a fun ride!

Rapid App Building

Low-code platforms are like the turbo boost for financial institutions. They come with a user-friendly, drag-and-drop playground and a treasure chest of pre-made components, making app development a walk in the park. Even folks in suits, like financial analysts and operations managers, can roll up their sleeves and get creative. With this speed boost, new solutions hit the market quicker, cutting down on wait time and ramping up how smooth things run behind the scenes.

Bend It Like Beckham – Agility and Flexibility

Finance is a dynamic game, with rules that change as often as the weather. Low-code platforms let you pull off those fancy agile moves and keep up with shifts in the market, those never-ending legal requirements, and the constant chatter from customers. Thanks to low-code’s magic, you can prototype and tinker with your apps at lightning speed, making it a breeze to adjust to whatever curveballs the business world throws your way. Whether it’s adding new features or tying into your existing systems, you won’t need an army of coders or disrupt your core operations.

Teamwork Makes the Dream Work

In the old days, IT teams and business folks used to speak different languages, and that led to some pretty epic misunderstandings and delays. But low-code is like the United Nations for business and tech. It brings them together, lets them hash things out, and builds apps that everyone can agree on. No more lost-in-translation moments, just smooth sailing toward those big goals.

Plug and Play

Financial institutions have a pretty tangled web of IT stuff going on. Low-code platforms are like the master key that fits all the locks. They’re pros at connecting with your existing systems, databases, and even those third-party apps you can’t live without. This seamless integration means data can flow like a river, manual tasks can vanish, and your whole operation can get a fresh boost of energy. Plus, they speak the same language as the hottest new tech, so you’re ready for whatever buzzwords come your way.

Playing By the Rules – Compliance and Security

The finance world has some pretty strict rule-makers, like the data privacy gurus and the financial regulation police. When you bring in low code, you’ve got to make sure it plays by the book. Look for low-code platforms that follow the rules, pack a punch with data encryption, let you set the right permissions, and give you a watchful eye with audit features. This way, you can keep the important stuff safe and stay in the good books with the regulators.

Roadblocks and Things to Think About

Even though low-code development brings a ton of perks, you can’t just jump in without a plan. Here are a few speed bumps to keep in mind:

1. Learning the Ropes: Introducing your team to low-code might require time and training investment.

2. Picking the Right Partner: Not all low-code vendors are made equal. You’ve got to be picky and look for the ones with a track record of awesomeness, top-notch security, and the ability to scale to your needs.

3. Tech Debt Pileup: Building apps faster is great but can lead to messy code and a mountain of technical debt. You’ve got to set some rules and keep things in check to avoid this pitfall.

4. App Life Support: Once you’ve got your shiny new apps, you’ve got to look after them. That means managing different versions, testing, and getting them out there into the world. You need processes and tools to keep everything running smoothly.

Digitalization takes center stage: Almost two decades ago, major financial institutions established separate units to explore e-commerce. Today, 70% of BFSI executives consider digital transformation essential (McKinsey & Company). The sector now focuses on payments, retail and online banking, and wealth management, extending into institutional banking. Despite progress in 2020, the insurance sector lags in digitization. To thrive, insurers must shift to a digital-first approach, offering personalized services to boost customer loyalty through unified views.

Replacing Legacy Systems with Modern Infrastructure: Change is vital as modern platforms offer superior benefits at lower costs. 79% of banking, fintech, and insurance CIOs recognize the influence of real-time, hyper-relevant experiences on customer expectations.

Rethinking Emerging Payments: Emerging payments are consolidating, not slowing down. It’s the right moment for the BFSI industry to develop frictionless, embedded, and native solutions for customer interaction, setting the stage for success.

Low code is like a superhero for financial institutions looking to make big digital changes. It hands the power to the business folks, speeds up app creation, and makes teamwork between business and tech a breeze. But there’s a catch. You’ve got to be ready for these challenges and always keep an eye on the rules and security stuff. If you do it right, low-code can change the game in finance, bring in some cool innovations, and give your customers the best experience they’ve ever had.

Exciting News! We’ve Got an Exclusive Ebook Coming Your Way – Stay Tuned and Follow Indium Software on LinkedIn

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Data Storage in Healthcare

The healthcare industry deals with vast amounts of sensitive and confidential patient information. To effectively store and manage this data, healthcare organizations employ various methods, including:

Electronic Health Records (EHR): EHR systems enable the digital storage and management of patient medical records, test results, and treatment histories. These records are stored securely in electronic databases, accessible only to authorized healthcare professionals.

Cloud-Based Storage: Many healthcare providers are adopting cloud-based storage solutions like Google Cloud, and AWS to store and back up their data. Cloud platforms offer scalability, accessibility, and disaster recovery capabilities while adhering to stringent security measures.

Data Warehousing: Healthcare organizations often utilize data warehouses to consolidate and analyze vast amounts of patient data. These warehouses ensure efficient data storage, integration, and retrieval for research, analytics, and decision-making purposes.

Data Security in Healthcare

To safeguard patient information and maintain data integrity, healthcare providers implement robust security measures:

Access Controls: Healthcare organizations employ strict access controls, limiting data access to authorized personnel only. User authentication mechanisms, such as usernames, passwords, and two-factor authentication, are implemented to prevent unauthorized access.

Encryption: Sensitive data is encrypted both during transmission and storage to protect it from unauthorized interception or access. Encryption techniques like Secure Sockets Layer (SSL) or Transport Layer Security (TLS) are commonly used.

Data Assurance Services continue to be a top priority in the healthcare and BFSI sectors, where the stakes are high in terms of privacy breaches and regulatory non-compliance.

Data Loss Prevention (DLP): DLP technologies such as Microsoft Security, help prevent accidental or intentional data breaches by monitoring and controlling the transfer of sensitive data within and outside the organization. These tools can identify and block unauthorized data transfers, ensuring compliance with data protection regulations.

Compliance Measures in Healthcare

Healthcare organizations must adhere to various compliance requirements to ensure data protection and privacy:

Health Insurance Portability and Accountability Act (HIPAA): HIPAA sets standards for protecting sensitive patient information, known as Protected Health Information (PHI). Compliance involves implementing physical, technical, and administrative safeguards to secure PHI and training employees on privacy practices.

General Data Protection Regulation (GDPR): Although primarily applicable in the European Union, GDPR has an extraterritorial impact on healthcare organizations globally. It mandates the protection of personal data and grants individuals’ control over their data, requiring organizations to implement robust security measures and obtain informed consent.

Data Storage in BFSI

Similar to healthcare, the BFSI sector handles vast amounts of sensitive financial and customer data. Data storage methods employed in BFSI include:

Core Banking Systems: BFSI organizations typically have core banking systems that store customer account information, transaction history, and other financial data securely. These systems are designed with redundancy and backup mechanisms to ensure data availability.

Data Centers: Many BFSI organizations maintain their own data centers, equipped with state-of-the-art infrastructure and security measures. These data centers provide a controlled and secure environment for storing and managing critical data.

Data Security in BFSI

The BFSI industry faces constant cybersecurity threats, and securing financial data is crucial. Security measures employed in BFSI include:

Network Security: To safeguard against unauthorized access and data breaches, it is crucial to have strong network security measures in place, including reliable firewalls, intrusion detection and prevention systems, and a secure network infrastructure.

Encryption and Tokenization: Sensitive data, such as customer financial details and authentication credentials, is encrypted to prevent unauthorized access. Tokenization techniques replace sensitive data with non-sensitive equivalents, further enhancing security.

Compliance Measures in BFSI

The BFSI industry is subject to numerous compliance regulations to safeguard customer data and maintain the integrity of financial systems. Several important compliance measures include:

The Payment Card Industry Data Security Standard (PCI DSS) lays out security standards for organisations that deal with credit cardholder data. In order to comply, one must maintain a secure network, put in place strict access rules, frequently check and test security systems, and more.

Anti-Money Laundering (AML) Regulations: BFSI organizations must comply with AML regulations to prevent illicit financial activities. This involves implementing systems and processes to monitor and report suspicious transactions, perform due diligence, and maintain accurate records.

Conclusion 

Data Assurance Services are crucial for maintaining trust, security, and regulatory compliance in healthcare and BFSI industries. Secure storage techniques, stringent security measures, and adherence to regulations like HIPAA, GDPR, PCI DSS, and AML foster trust and resilience. In today’s landscape of increasing data breaches and cyber threats, Data Assurance Services gain prominence as organizations secure sensitive information while meeting evolving compliance standards. Both healthcare and BFSI sectors, holding critical data, require strong strategies for data availability, confidentiality, and integrity.

These sectors embrace advanced technologies like AI and blockchain to enhance data assurance. These technologies offer improved encryption and decentralized storage, bolstering security protocols.

The interplay between data assurance and emerging technologies emphasises the need for ongoing adaptation. Beyond traditional bounds, data assurance encompasses data from IoT devices, wearables, patient monitoring, and mobile banking. Safeguarding data in transit and at network edges is as vital as protecting centralised repositories.

Tackling these challenges necessitates industry collaboration and knowledge sharing. Forums for professionals to exchange insights and strengthen defences against evolving cyber threats Government regulators and industry associations also guide robust data security through standards and enforcement.

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Quick Insights!

1. 1. By 2025, people will create more than 181 ZB of data.
2. 2. 82% of organizations plan to increase their investments in data modernization in 2023, up from  41% in 2022
3. 3. By 2025, large companies will share data for collaboration, data assets will be treated as products, and interconnected devices will collect real-time information.
4. 4. 61% of companies think the fast-growing data volume limits their ability to fully harness their data.
5. 5. A fifth of digital leaders feel they are effectively using data insights to generate more revenue
6. 6. 22% of chief executive officers believe using data effectively to develop new products and services is an important source of their growth in the next five years.

Webinar Unveiled: The Blueprint for Data Monetization

In collaboration with Srinath Venkatesh Nadkarni, Senior Vice President of the Data and Analytics practice, and Sreenivasan Rajasekaran, Senior Data Architect, presents an exclusive webinar poised to be a game-changer – Accelerate Monetization of your Data Assets with Data Modernization!

Cracking the Code: The Data Monetization Maturity Framework!

This webinar isn’t just another online event; it’s a window into transforming your data into a strategic asset. It delves into the vital role data modernization plays in accelerating monetization efforts. Additionally, it lights the path to a successful modernization journey, sprinkled with best practices to ensure smooth data migration to cloud platforms.

Data monetization maturity is determined by the progressive stages of the model. Organizations embarking on this journey can follow these key phases:

Data Nascent Stage: At the initial phase, companies exhibit low data maturity and externalization. They possess limited familiarity with utilizing data and may lack a clear direction for its application. Despite this, they might opt to externalize the small amount of data they’ve generated, modified, or repackaged. This transition marks the move into the Data Services phase. They might offer basic data services such as APIs or shared databases accessible to external partners.

Data Services Phase: These entities may advance their offerings over time by providing more comprehensive datasets for nominal charges. While not offering high-value data, they present a deluge of data, leaving consumers to discern its value. This phase categorizes them as Bulk Data Providers. The responsibility of extracting value rests primarily with the data consumer. This stage showcases substantial data externalization but lacks maturity.

Information Productization Stage: Recognizing the growth potential, some companies opt for higher maturity by transitioning to the Information Productization stage. This move comes with new market prospects (high externalization, moderate maturity). Companies may streamline their data offerings, replacing the data deluge with higher-value data products tailored to specific market needs. As these businesses understand the market demands their data can fulfill, their maturity deepens. This understanding serves as a foundation for subsequent scaling.

Line of Business Phase: As organizations enhance their data product maturity and develop a profound grasp of their underlying data, they progress into the Line of Business phase within the monetization maturity spectrum. They begin selling larger quantities and a diverse array of data products. This transition marks the point where data licensing transforms into a tangible revenue source. Eventually, the proceeds from data licensing and productization become substantial enough to warrant inclusion in the Profit & Loss (P&L) statements, significantly impacting the bottom line.

This evolution towards a data-driven line of business hinges on complete data externalization and the capacity to cater to external customers. Each stage, from nascent data utilization to establishing a profitable data-focused line of business, is characterized by varying data maturity and externalization levels. This model illustrates how businesses can progress and capitalize on their data assets, generating significant value and contributing meaningfully to their organizational success.

Infusing Value with 2023 Data Insights

Our webinar isn’t just a theoretical exploration; it’s anchored in 2023’s data and analytics trends. Expect recent statistics from top-notch research firms to punctuate the discussion, offering you actionable insights for your strategic decisions. Here are our quick tips!

Gather, Centralize, Analyze: Create a single hub for all your data, making analysis easier. Imagine you’re a retail chain aiming to boost sales. Centralizing data from all your outlets allows you to analyze buying patterns, identify popular products, and enhance inventory management.

Opt for Your Model: Choose between monetizing data internally or externally. Picture a fitness app that tracks user activity. You can use this data to enhance your app’s features (internal monetization) or partner with health insurers (external monetization) to offer personalized plans.

Comply and Secure: Adhere to data regulations like GDPR and ensure data accuracy. Suppose you’re a healthcare provider offering telemedicine. By safeguarding patient data, you gain trust, enabling fruitful collaborations with other healthcare players.

Elevate Your Strategy: What Awaits You

Embrace the future of data monetization by reserving your spot in this exclusive webinar. Armed with the right knowledge, you can propel your organization toward success, leveraging the power of data like never before. The question isn’t whether you should – it’s whether you can afford to miss out. Are you ready to seize the future?

The post Data + Innovate = Value! Mastering Data Monetization for Business Success appeared first on Indium.

Here are some IT systems that have had a significant impact on HealthCare:

• Electronic Medical Record (EMR): EMRs and EHRs are collections of patient records stored in a digital format. It contains a patient’s demographics, medical history, and radiology images.
• Health Information Security (HIS): With the digitalization of patient data, the need for robust information security measures has become most important.
• Artificial Intelligence in Health Care: It has the ability to analyse large amounts of medical documentation quickly, and it assists in diagnosing diseases faster, suggesting more treatment options, and providing personalised treatments. It also improves medical practises
• Health Care Administration and Medical Billing: This system has streamlined administrative tasks such as patient billing, scheduling appointments, and insurance claims.

Digital Assurance in HealthCare Applications:

The majority of healthcare applications process sensitive patient data that can be shared throughout different information systems. It includes information on the demographics, billing, and health of the patient. Digital assurance is essential in the healthcare sector because to the very sensitive data in the applications.

Digital assurance in healthcare is crucial for managing risks and ensuring patient safety. The actions and a set of steps that are planned to guarantee ongoing development in the standard of medical care are surrounded by digital assurance in healthcare. Some healthcare apps need to be examined in order to produce high-quality medical products.

The following list includes the key categories of healthcare software testing:

• Security & Compliance Testing: To ensure the protection of sensitive patient data and compliance with industry regulations like HIPAA and GDPR.
• Performance Testing: To check the stability of HealthCare applications under normal load and stress conditions.
• Functional Testing: To ensure the functionality of the HealthCare feature works as per the requirements planned.
• Compatibility Testing: To ensure the HealthCare applications are able to run on different devices and that the feature is fully compatible with the required range of Browsers and operating systems.
• Integration Testing: To check whether the Healthcare applications work together smoothly if any of the healthcare software modules are combined. (e.g., EMR, Laboratory Information System, Medical Devices, etc.)
• Interoperability Testing: To check if a healthcare solution can exchange medical data accurately with major data transfer standards such as HL7, NCDPD, IHTSDO, CDISC, DICOM, and more.

Continuous Testing in Healthcare:

Continuous testing is a development process in which Healthcare applications are tested continuously throughout the entire software development life cycle (SDLC). The aim of Continuous testing is to determine whether the software quality across the SDLC will meet the quality standards, ensuring the applications are free from defects and enabling higher-quality and faster deliveries.

Here are some key points regarding continuous testing in healthcare:

• Automation: Continuous testing relies heavily on test automation. Automated test scripts are designed to validate various phases of healthcare applications, such as UI, data integration, interoperability, security, standards, and compliance.
• Test Coverage: Continuous testing aims to provide complete test coverage across different modules of healthcare systems, including electronic medical records (EMRs), laboratory decision support systems, online medicine platforms, and mobile health applications. It helps to identify issues early on, reducing the risk of patient safety concerns.
• Speed and Efficiency: Continuous testing enables rapid feedback on the quality of healthcare software. By automating tests and integrating them into the development pipeline, healthcare organisations can find and resolve issues promptly, accelerating the delivery of high-quality software.
• Regression Testing: Continuous testing includes regression testing, which ensures that new changes or updates to the software do not affect the unchanged areas or break existing functionality. This is crucial in healthcare, where software changes can have significant implications for patient care.
• Security and Compliance: Continuous testing incorporates security and compliance testing to identify vulnerabilities and ensure adherence to industry regulations and standards such as HIPAA (Health Insurance Portability and Accountability Act) in the United States. This helps protect patient data and maintain the privacy and confidentiality of health information.
• Integration and Interoperability: Healthcare systems often involve multiple interconnected healthcare modules and interfaces. Continuous testing verifies the smooth integration and interoperability of these systems, ensuring consistent data exchange and communication between different healthcare applications.

A Roadmap to Test Automation Success in the Healthcare Industry: 

Implementing test automation successfully in the healthcare industry needs careful planning and consideration of regulatory requirements.

Below is the roadmap to help you achieve test automation success in the healthcare industry:

fig. Roadmap to Test Automation Success

Define clear objectives: Identify the goals and objectives for test automation in the healthcare industry. Determine what can be achieved through automation, such as improved testing efficiency, increased test coverage.

Understand regulatory requirements: Understand the regulatory requirements specific to the healthcare industry, such as HIPAA (Health Insurance Portability and Accountability Act) and PSQIA (Patient Safety and Quality Improvement Act) compliance.

Conduct a thorough assessment: Perform a comprehensive assessment of testing processes, including manual testing practises, test coverage, and high-risk areas. Identify the most suitable areas for automation and prioritise based on their impact on patient safety, business processes, and return on investment.

 Choose the right test automation framework: Select a test automation framework that best suits the healthcare industry. Open-source frameworks like Selenium and BDD tools like Cucumber and JBehave are popular choices in this domain. Popular choices in this domain.

Build a robust test environment: Create a dedicated test environment that closely mimics the production environment to ensure accurate testing. Set up test data management processes that include anonymization and data protection techniques to comply with privacy regulations.

Develop a test automation strategy: Define the test automation strategy that includes the types of tests to be automated (e.g., Functional, Performance, Security, Integration), the selection of appropriate test tools, and the establishment of testing standards and guidelines. Consider utilizing behavior-driven development (BDD) or similar techniques to align the automation efforts with business requirements.

Implement test automation gradually: Begin with a pilot project or a small set of test cases to validate your automation strategy and identify any challenges or bottlenecks.

Collaborate with stakeholders: Involve key stakeholders, such as clinicians, business analysts, and regulatory compliance experts, throughout the test automation process. Get their input to ensure that the automation efforts align with their needs and address their concerns.

Establish continuous integration and delivery: Integrate test automation efforts into your development and deployment pipelines. This helps identify issues early and reduces the risk of deploying faulty software.

Monitor and maintain the test automation suite: Regularly monitor the performance and effectiveness of your test automation suite. Maintain and update your test scripts to accommodate changes in the healthcare system, software updates, and evolving regulatory requirements.

Invest in training and skill development: Provide training and support to the testing team to ensure they have the necessary skills and expertise to leverage test automation effectively.

By following this roadmap, we can increase patient safety, reduce risks, and provide enhanced software quality.

Case Study: According to the CISQ report (Consortium for IT Software Quality), software failures have affected a variety of industries, and most businesses spend more to detect and remedy flaws.

A few recent examples of how software affected brands are as follows:

• Because of an error in their accounting software, Wells Fargo Bank had to foreclose on loans for consumers.

• Application failures brought on by crew scheduling issues damage the airline industry more.

• Due to a problem with its management software, Tesla incurred significant costs, and the stock price fell by almost 3% the next day.

Numerous incidents that occurred in banks, health care facilities, and other institutions may have been discovered and fixed with the use of automation testing and continuous testing.

Conclusion:

Following COVID-19, the healthcare industry underwent significant change, and governmental laws and regulations were loosened. Without appropriate healthcare applications, the healthcare sector today cannot function. When processing massive amounts of data, it’s critical for those apps to be effective, secure, and compliant with all applicable standards and laws. Therefore, it is necessary for healthcare goods to undergo ongoing testing to guarantee that the software complies with all requirements, norms, and regulations. We will produce high-quality software, improve the effectiveness and efficiency of QA test efforts in the healthcare industry, and avert the inevitable errors of manual testing by adhering to the automation roadmap in healthcare.

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