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Banking’s Data Democratization: Insights and Lessons for Future`

Banking’s Data Democratization: Insights and Lessons for Future`

The banking industry has changed profoundly in recent years, with data playing a pivotal role. Data in banking is no longer confined to silos but has become a democratized resource that drives innovation and change. This blog explores the concept of Banking’s Data Democratization, its impact on the industry, and the lessons it offers for the future. We will delve into banking transformation services, data in digital transformation, and big data in banking. Additionally, we will highlight recent examples of financial institutions leading the way in this data revolution.

The Rise of Data in Banking

Historically, banks were data-rich but often struggled to extract the needed help from their data. With the advent of technology and increased connectivity, the banking data concept has shifted dramatically. Here are the crucial aspects of this transformation:

Data Democratization 

Data democratization is about making data accessible to all stakeholders within a bank. It empowers employees to access and utilize data for informed decision-making. This shift has been fundamental in modern banking.

Banking Transformation Services 

Banks have embraced banking transformation services to democratize data, including data analytics, machine learning, cloud computing, and artificial intelligence. These services help banks efficiently manage and analyze data to extract valuable insights.

Data in Digital Transformation

Digital transformation in banking has been closely intertwined with data digital transformation. Banks leverage data to streamline processes, enhance customer experiences, and remain competitive digitally.

Big Data in Banking

The sheer volume of data generated in banking is staggering, and big data in banking has become a driving force. Banks use big data analytics to understand customer behavior better, detect fraud, and develop personalized services.

banking data democratization

Remarkable Advances in Data Democratization

Several financial institutions have made significant strides in banking’s data democratization. Let’s explore some examples:

1)JPMorgan Chase:

JPMorgan Chase has established the “Data Analytics and AI Solutions” division, which harnesses the power of big data and AI to enhance decision-making. They have created advanced algorithms for credit risk assessment and portfolio optimization, improving the bank’s operational efficiency and customer service.

2) HSBC:

HSBC has implemented a data democratization strategy, ensuring that data is accessible to employees across the organization. They’ve also invested in data analytics tools to enhance their anti-money laundering efforts, protecting the bank and its customers.

3) Wells Fargo:

Wells Fargo uses data-driven insights to personalize customer experiences. They analyze transaction data to offer tailored product recommendations, improving customer satisfaction and loyalty.

Challenges and Approaches to Success

While banking’s data democratization holds enormous potential, it also presents challenges:

1) ata Security: 

With increased data accessibility comes the need for robust data security. Banks must invest in state-of-the-art cybersecurity measures to protect sensitive customer information.

2) Regulatory Compliance:

Data privacy regulations are stringent. Banks must navigate complex compliance requirements while utilizing customer data.

3) Data Quality:

Ensuring data accuracy and quality is crucial. Banks need to invest in data governance and management processes.

4) Cultural Shift:

Democratizing data requires a cultural shift within banks. Employees must embrace data-driven decision-making.

Conclusion.

Banking’s data democratization is a transformative force in the industry. Notable institutions like JPMorgan Chase, HSBC, and Wells Fargo have harnessed the power of data to enhance their operations and customer experiences. However, challenges like data security and regulatory compliance persist. Success lies in investing in cybersecurity, adhering to regulations, ensuring data quality, and fostering a data-driven culture. The lessons learned from these innovations will shape the future of banking, where data is king and its democratization is the key to competitive advantage.

About Maveric Systems

Starting in 2000, Maveric Systems is a niche, domain-led Banking Tech specialist partnering with global banks to solve business challenges through emerging technology. 3000+ tech experts use proven frameworks to empower our customers to navigate a rapidly changing environment, enabling sharper definitions of their goals and measures to achieve them.

Across retail, corporate, and wealth management, Maveric accelerates digital transformation through native banking domain expertise, a customer-intimacy-led delivery model, and a vibrant leadership supported by a culture of ownership.

With centers of excellence for Data, Digital, Core Banking, and Quality Engineering, Maveric teams work in 15 countries with regional delivery capabilities in Bangalore, Chennai, Dubai, London, Poland, Riyadh, and Singapore.

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Data Analytics Importance in the Finance and Banking Industry

Data Analytics Importance in the Finance and Banking Industry

Three things are coming together to start the next spotlight – Data Analytics in BFSI. First, think about how technology has changed. Information is becoming more and more accessible. In the past few years, the amount of valuable data—actual signal, not just noise—has grown exponentially while processors have gotten smaller and cheaper. Businesses have opened their minds and are willing to use new ways of analyzing data that might have been thought too academic and unrealistic for the real world. The exponential growth of computing power, which makes it possible to do in seconds an analysis that used to take weeks, and new tools for storing data, such as Hadoop, have made it much easier for any company to do these kinds of analytics.

Second, the economy is putting much pressure on banks in many places. According to McKinsey’s latest study, 54 percent of the top 500 institutions in the world are priced below their book value. In 2014, as the report posits, only 18% of banks got the industry’s value. Realizing this, banks have tried various ways to improve things, including going digital and cutting costs. But these moves can only get them so far. They need something new.

The third thing that is pushing analytics is these attempts to digitize. A standard bank has digitalized much of its work and puts data by terabytes. Advanced analytics would be hard to use in a bank that does most of its work by hand, but digital banks already have the roads built.

When you put everything together, you get advanced analytics, which are large-scale ways to use data to get real business insights and make much better decisions. The tools are there; now, banks need to use them to take steps that can lead to real change.

Partnering with domain experts in Data Technology and Big Data Analytics like Maveric Systems brings a decisive edge for FIs to embrace next-generation technologies and create industry benchmarks.

data analytics in banking - maveric systems

Importance of Data Analytics in the Banking and the Financial Sector

  1. Advanced analytics can help banks make small changes to almost everything they do daily, boosting the standard P&L levers. Here are some things that could be done:
  2. Together with transactional and trading analytics, deeper and more detailed profiles of customers can help get and keep customers, as well as cross-sell and up-sell. For example, one bank used information about credit card transactions (from its terminals and those of other banks) to make deals that encouraged customers to buy from one of the bank’s merchants frequently.
  3. Increasing work output. Every step of the banking process can be made faster and better. Banks can use advanced analytics to respond to governmental requests quicker and more accurately and help teams make decisions with the help of analytics.
  4. Improving risk control. Compliance and control costs have increased significantly in the past few years, and banks can use analytics to get a return on their significant investments. With the help of analytics, banks can use tools like digital credit assessment, advanced early-warning systems, next-generation stress testing, and credit-collection analytics to lower their risk costs.
  5. Customer Experience: Another way analytics can have an effect is by helping digital banks live up to their promises and give customers a much better experience for a fraction of what it costs now. In some places, up to 65% of people now talk to their banks in multiple ways. Their paths through them are very complicated. They often start in one channel, do steps in others, and end in another, with many stops and turns to gather information. Successful digital banks offer a smooth multichannel experience by collecting real-time data and using analytics to understand the customer and build the right (and always consistent) journey view.
  6. Lastly, analytics can help banks find new ways to grow their businesses and even new ways to do business. Banks can profit from their data by letting new ecosystem partners, like telecom companies or stores, use their customer analytics tools. As a data company, the bank can be at the center of a customer environment where banking and many other B2C and B2B businesses bring in money. Taken to an extreme that is reasonable but not impossible, banks can use data and analytics to create a new business model and beat fintech companies at their own game.

Conclusion

Data analytics has become essential to how small and big businesses make decisions. The vast amounts of structured and unstructured data made by many gadgets on different platforms have given us unique insights. With the help of data analytics and data management, the Banking and Financial Services Industry (BFSI) has used Big Data to improve organizational success and ensure risk management, financial growth, and performance. The main goals of the banking and economic areas are to improve performance, make money, and cut down on risk. In this data-driven world, success depends on Big Data technologies that can store and handle semi-structured and unstructured data in real-time.

About Maveric Systems

Starting in 2000, Maveric Systems is a niche, domain-led Banking Tech specialist partnering with global banks to solve business challenges through emerging technology. 3000+ tech experts use proven frameworks to empower our customers to navigate a rapidly changing environment, enabling sharper definitions of their goals and measures to achieve them.

Across retail, corporate & wealth management, Maveric Systems accelerates digital transformation through native banking domain expertise, a customer-intimacy-led delivery model, and a vibrant leadership supported by a culture of ownership.

With centers of excellence for Data, Digital, Core Banking, and Quality Engineering, Maveric Systems teams work in 15 countries with regional delivery capabilities in Bangalore, Chennai, Dubai, London, Poland, Riyadh, and Singapore.

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How Are Data Analytics Used In The Banking And Finance Industries?

How Are Data Analytics Used In The Banking And Finance Industries?

Financial institutions use data and predictive analytics to improve customer experience and amplify business success. Today, banks want more than incremental gains. They want data-driven revenue breakthroughs. Banks increasingly rely on data. It’s the future of communication and might address banks’ most significant issues.

Data drives today’s financial market. The information helps financial services businesses personalize, streamline, and profit. This change affects operating costs, staffing, customer experience, and more.

Engaging banking domain experts like Maveric Systems for next-generation data technology solutions enable leading banks to make bold bets and maximize their innovation potential.

The Growing Use Cases for Big Data Analytics for BFSI

  1. Fraud Detection: Banks and financial organizations aim to reduce fraud, but analytics may also control risk. Banks can prioritize fraud detection by assessing account risk. Analytics can detect and rate fraud-prone consumers and apply different levels of monitoring and verification to those accounts.
  2. Operational/liquidity risk: Operational risk is the risk of company losses. Operational risk includes financial institution-specific hazards. Liquidity risk includes macro, comprising interest rate swings, foreign exchange rate changes, and bond value changes. Operational hazards include fraud, theft, computer security breaches, and management incompetence. Banks utilize data analysis to identify high-risk loan defaulters and act before things get out of hand.
  3. Investment bank risk modeling: Risk modeling simulates how a portfolio of assets (stocks, bonds, futures, options, etc.) or a single asset (such as an interest rate) reacts to different scenarios. Risk modeling across all assets reduces portfolio risk and improves performance.

Data-Driven Banking

Technology and analytics enhance strategic planning and decision-making. Data-driven banking rethinks banking data. Instead of displaying account information, currency fluctuations, or analyzing your data, banks use it to add product and service information to their products. This gives banks more insight into their customers’ lives and helps them increase earnings by delivering more accurate data about their clients’ demands.

This helps customers make more competent judgments and allows third-party companies to promote a bank’s products, which benefits society.

Three Key Components for creating a holistic Data Analytics Strategy

  1. Data Volume: We realize “Data Analytics” demands “excellent data,” but volume comes first. Many corporations tend to ignore volume. They think it’s available. Building a data bank is an enterprise problem today; only a few businesses take it seriously. Data collection, curation, and storage systems require the correct personnel and time at project start-up. Not establishing a data warehouse and putting everything there is the data team’s primary business goal.
  2. Data Accuracy: Data quality follows volume. More data is needed to ensure relevant insights/models. It reduces data team productivity. Data workers spend much of their time reassembling data to improve quality. Data scientists spend over 82% of their time cleaning and preparing AI/ML data. Organizations need good data pipelines and reliable data flow infrastructure for accurate insights.
  3. Data Security and Compliance: Organizations should prioritize data governance, security, and compliance when establishing a data strategy rather than technology-focused data volume and quality. A data analytics roadmap needs the correct mix of people, data, products, technology, process, and governance to be productive. An analytics roadmap should also begin with thoroughly analyzing the company’s business goals and key indicators.

Big Data Analytics for BFSI

Conclusion

Finance is increasingly using data analytics. Data analytics is helping more companies enhance internal processes worldwide. Data analytics helps them understand customers better. This allows CEOs to make smarter business decisions. Finance professionals use data analytics to gain insights that improve decision-making. Finance teams use data analytics to understand KPIs (KPIs). Revenue, net income, payroll, etc. Data analytics helps finance teams analyze fundamental KPIs and spot revenue turnover fraud.

About Maveric Systems

Starting in 2000, Maveric Systems is a niche, domain-led Banking Tech specialist partnering with global banks to solve business challenges through emerging technology. 3000+ tech experts use proven frameworks to empower our customers to navigate a rapidly changing environment, enabling sharper definitions of their goals and measures to achieve them.

Across retail, corporate & wealth management, Maveric Systems accelerates digital transformation through native banking domain expertise, a customer-intimacy-led delivery model, and a vibrant leadership supported by a culture of ownership.

With centers of excellence for Data, Digital, Core Banking, and Quality Engineering, Maveric Systems teams work in 15 countries with regional delivery capabilities in Bangalore, Chennai, Dubai, London, Poland, Riyadh, and Singapore.

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How DevOps will help FIs to advance the use of Automation

How DevOps will help FIs to advance the use of Automation

Ninety-nine percent of respondents to a recent Atlassian Survey – DevOps Trends state that DevOps has positively influenced their firm. There is a reason why post-COVID, DevOps has an increased preference for leading banks and FIs.

Amidst the epidemic, some financial institutions were compelled to augment their digital service to accommodate consumers’ evolving desires. Transformations of the front end, such as digital account opening, Know Your Customer, mobile banking, online customer assistance, and self-service, must be completed quickly.

This significant effort to improve the digital customer experience (CX) has had a ripple effect on backend systems and supporting IT operations. A rising digital footprint spanning on-premises software and the cloud necessitates improved cadence for managing new deployments, target infrastructure, and legacy cores with new digital add-ons. Working with deep domain experts – like Maveric – creates market-defining value propositions.

Automation in DevOps

How is DevOps offering game-changing rhythms in the BFSI sector?

Robotic Process Automation

DevOps significantly accelerates internal procedures within the financial services business. Automating tasks across the process chain or software delivery cycle effectively achieves efficient resource utilization, improved product quality, and increased developer productivity while balancing responsibilities across cross-project requirements, frequent updates, and enterprise-level process management.

Security

Security is the fundamental reason financial service organizations embrace DevOps as part of their digital transformation efforts. Even though the rapid delivery method of DevOps was previously perceived as a security risk, numerous financial institutions have claimed improved security and faster recovery due to DevOps principles.

Creating a performance culture

DevOps is a combination of Development (Dev) and Operations (Ops) that is valued more for the organizational culture it fosters than for the technology itself (Ops). DevOps culture facilitates the concurrent functioning of development, operations, and Quality Assurance (QA), promoting effective collaboration and knowledge-sharing, thereby easing internal processes. DevOps approaches unite several teams on a single platform while connecting them to a project pipeline.

Effective Management Outcomes

Large firms frequently need help with their widely dispersed internal teams, which may result in misunderstandings that disrupt the process flow when necessary. DevOps handles all steps of the software delivery pipeline (release, deploy, test, and build) to ensure shared visibility and process control between teams. This includes preventing differences between groups and eliminating functional silos by properly addressing every component of the software delivery chain.

Creating Tomorrow’s Modernization Dynamics

Digital banking is nothing new. DevOps enables you to modernize systems continuously without putting your business at risk by bringing it offline. Alternately, if companies start from scratch, DevOps enables modernization at the construct stage, responding to the current trends without the outcome that the newly-released solution is already obsolete.

Boosting Transparency

Previously, financial software was developed independently using a very hierarchical procedure. Participants worked effectively in silos, focusing on their part of the assignment and nothing else, which was beneficial for information security but hampered efficiency. All of this has changed. DevOps in finance necessitates the participation and collaboration of multiple teams, including QA, engineering, content, compliance, legal, etc., to guarantee that the software solution is up to par. The an

Conclusion

The rapid delivery of services has become crucial for businesses across all industry verticals to compete in the current market environment. Financial services are essential businesses characterized by high customer reliance and the consequent necessity for rapid delivery of solutions to fulfill the ever-increasing end-user requirements. As a sector that engages in high-level financial operations, such as banking, financial services necessitate uninterruptible client service and a solid internal infrastructure for streamlined processes.

About Maveric Systems

Starting in 2000, Maveric Systems is a niche, domain-led Banking Tech specialist partnering with global banks to solve business challenges through emerging technology. 3000+ tech experts use proven frameworks to empower our customers to navigate a rapidly changing environment, enabling sharper definitions of their goals and measures to achieve them.

Across retail, corporate & wealth management, Maveric accelerates digital transformation through native banking domain expertise, a customer-intimacy-led delivery model, and a vibrant leadership supported by a culture of ownership.

With centers of excellence for Data, Digital, Core Banking, and Quality Engineering, Maveric teams work in 15 countries with regional delivery capabilities in Bangalore, Chennai, Dubai, London, Poland, Riyadh, and Singapore.

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Methods Of DevOps Methodology In The Banking Industry

Methods Of DevOps Methodology In The Banking Industry

Financial services, together with companies in the computer industry, may be ranked among the leaders in DevOps practice maturity. When it comes to accelerating innovation and implementing cutting-edge software delivery techniques like agile, continuous delivery (CD), and DevOps, FIs are at the forefront of change. Several requirements for the financial sector are

  • Increased data volumes
  • A cross-channel presence that is growing
  • Secure, quick data transfers
  • Customer centricity.

These form the design principles for consulting engagements for banking technology domain specialists like Maveric Systems

What is DevOps

DevOps is a set of methods and technologies for streamlining operational workflows, procedures, and pipelines for delivering software.

What are the top three benefits of DevOps?

  1. Cost Savings. Every industry is trying to reduce costs, and the banking industry is no exception. Here are several ways that DevOps can help save money. Infrastructure as a code allows for implementing template-based solutions instead of wasting valuable development time manually setting up IT infrastructure. Software engineers are more concerned with creating new features than how they are distributed and used. Moreover, reducing infrastructure utilization where it is possible helps bring down costs. Customers pay for what is required at a given time, allowing resource consumption and cost efficiency.
  2. Process Automation. Process Automation through continuous software delivery pipelines is another DevOps component that improves resource productivity, developer quality, and product management and visibility while enabling velocity and scalability. Companies may monitor the status of all DevOps processes and releases and ensure that they can optimize, direct, and control them by controlling all release processes from a single, central platform and automating end-to-end pipelines.
  3. Security. This is the main issue that hindered or worried financial services companies in their efforts to undergo digital transformation. Although DevOps’ rapid delivery method was once thought to be a way to undermine security, several financial firms on the move reported security improvement and quicker recovery thanks to DevOps practices. DevSecOps was introduced as an added benefit to ensure complete security integration throughout the pipeline. As a result, several businesses in the sector began to consider DevOps as a resource to handle security.

devops in banking

Agile Methodologies Promote Digital Transformation

To stay ahead of the competition, most banks now use agile processes. The primary reason for doing this is to meet the regular business demands that result from attempts to enhance the banking experiences of clients. The DevOps teams will primarily be fine-tuning the project planning and execution procedures that support this improvement goal. Applications would be developed using the agile methodology for banking in small, manageable chunks called sprints. Before being deemed executable or finished, each stage is painstakingly tested. The appropriate channels are followed for real-time feedback and course correction before adding more layers of development on top of the supplied component. The ultimate result must be that the customer receives a valuable product in less time than is feasible through any other development procedure.

Reducing errors in service delivery

The team can offer continuous build and integration functionalities using workflow management technologies. On dedicated cloud or on-premise systems, they can provide automated integration builds, minimizing service delivery failures. The final audit trail generates a bill of materials for every build, enabling developers to fix mistakes inadvertently. In broad strokes, it is possible to see what additional tasks, lines of code, and software assets were added to the build. The banking application is continuously delivered across test and production environments thanks to DevOps implementation. Errors are less likely to occur during the product life cycles of each financial service or product. As a result, it takes much less time to get from development to production.

Conclusion

In banking and financial firms, DevOps aids in meeting and exceeding new needs. This method enables one to provide value to the market in a secure, effective, and economical manner. As a result, numerous banking, financial services, and fintech organizations have already recognized the necessity to modernize historical banking infrastructure. The philosophy, equipment, and practices of DevOps have become the means of guiding digital transformation. DevOps techniques address governance, security, risk, and compliance issues and improve the quality of application releases.

About Maveric Systems

Starting in 2000, Maveric Systems is a niche, domain-led Banking Tech specialist partnering with global banks to solve business challenges through emerging technology. 3000+ tech experts use proven frameworks to empower our customers to navigate a rapidly changing environment, enabling sharper definitions of their goals and measures to achieve them.

Across retail, corporate & wealth management, Maveric accelerates digital transformation through native banking domain expertise, a customer-intimacy-led delivery model, and a vibrant leadership supported by a culture of ownership.

With centers of excellence for Data, Digital, Core Banking, and Quality Engineering, Maveric teams work in 15 countries with regional delivery capabilities in Bangalore, Chennai, Dubai, London, Poland, Riyadh, and Singapore.

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