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Why Banks with "Customer-First" Mindset Drives Better Revenue
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Why Banks with “Customer-First” Mindset Drives Better Revenue
Why Banks with “Customer-First” Mindset Drives Better Revenue 1300 972 Exist Software Labs

Banks that prioritize customer-first approach and satisfaction have a significant advantage over their competitors. They understand that their success depends on the happiness and loyalty of their customers. This blog post will explore why adopting a customer-centric approach is essential for banks and how it can drive better revenue.

Why is customer experience important in banking?

The financial industry has become increasingly competitive, with customers having more options. With the rise of mobile banking and digital transactions, customers have become more tech-savvy and expect seamless and personalized banking experiences. In this environment, customer experience has become a key differentiator for banks.

Customers want banks to understand their needs and provide personalized solutions that meet their specific requirements. They also expect quick and efficient service, whether they are banking online or in person. By prioritizing customer experience, banks can build strong relationships with their customers, which can translate into better revenue and profitability.

What are the benefits of a customer-centric approach in banking?

There are many benefits of adopting a customer-centric approach in banking. Some of the most significant benefits include

  1. Increased customer satisfaction: By prioritizing customer experience, banks can ensure customers are happy and satisfied with their services. This can lead to increased loyalty and retention, as customers are more likely to stay with a bank that meets their needs.
  2. Improved revenue: A customer-centric approach can lead to increased revenue, as customers are more likely to use additional services and products when they are happy with their overall banking experience. This can translate into higher profitability for the bank.
  3. Competitive advantage: By providing personalized banking solutions, banks can differentiate themselves from their competitors and attract more customers. This can help banks to stand out in a crowded marketplace and win new business.

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How can banks adopt a customer-first approach?

Banks can adopt a customer-centric approach in several ways. Some of the most effective strategies include

  1. Investing in digital banking solutions: Digital banking solutions, such as mobile banking apps and online banking portals, can provide customers with a seamless and convenient banking experience. By investing in these solutions, banks can meet their customer’s evolving needs and expectations.
  2. Prioritizing user experience: Banks should prioritize the user experience in all their interactions with customers. This means ensuring that their website, mobile app, and other digital channels are easy to use and navigate, with clear and concise information.
  3. Personalizing banking solutions: Banks can use data analytics to understand their customers’ needs and preferences. This can help them to provide personalized banking solutions, such as customized investment portfolios and loan products.
  4. Measuring customer satisfaction: Banks should regularly measure customer satisfaction to identify areas for improvement and ensure that they are meeting their customers’ needs.

In today’s competitive banking industry, adopting a customer-centric approach is essential for driving better revenue and building strong customer relationships. By investing in digital banking solutions, prioritizing user experience, personalizing banking solutions, training staff, and measuring customer satisfaction, banks can ensure that they are meeting their customer’s needs and providing a seamless and personalized banking experience.

At Exist Software Labs, Inc., we understand the importance of customer-centricity in banking. We are committed to providing innovative and personalized digital banking solutions that prioritize customer experience and satisfaction. Contact us today to learn more about how we can help your bank drive better revenue and build strong customer relationships.

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PEPIF 2023
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Exist Software Labs, Inc. joins IEMOP’s PEPIF 2023: Shaping the Future of Philippine Energy Industry!
Exist Software Labs, Inc. joins IEMOP’s PEPIF 2023: Shaping the Future of Philippine Energy Industry! 650 486 Exist Software Labs

The Independent Electricity Market Operator of the Philippines Inc. (IEMOP) recently hosted the Philippine Electric Power Industry Forum (PEPIF 2023) on March 20 and 21, 2023 at the Diamond Hotel Manila. Under the theme “Partnering to Achieve a Secure and Reliable Supply of Electricity for the Country”, the two-day event brought together industry leaders, decision-makers, and professionals to discuss challenges, opportunities, and best practices in the Philippine electric power industry.

The PEPIF 2023 was attended by delegates, sponsors, and resource persons who provided invaluable insights and stimulated meaningful discussions among the stakeholders. The forum aimed to strengthen collaboration and forge partnerships among industry participants in support of the objectives of the Electric Power Industry Reform Act (EPIRA) and accelerate programs under the Philippine Development Plan 2023-2028.

One of the key highlights of the forum was the annual Market Participants Update, which apprised the Wholesale Electricity Spot Market (WESM) members of the latest developments in both the wholesale and retail markets. This update provided a comprehensive overview of the current market trends, regulations, and opportunities for the participants.

PEPIF 2023
Chriss Silerio, the VP for Operations of Exist Software Labs, Inc. discussed the Internet of Energy at PEPIF 2023

Chriss Silerio, the Vice President for Operations of Exist Software Labs, Inc., served as one of the esteemed technical resource speakers. His presentation focused on the convergence of informational technology (IT) and operational technology (OT) in the context of the Internet of Things (IoT), and its significance in shaping the future of the energy industry.

According to him — “IoE takes a more holistic approach by connecting people, data, and processes in the interconnected system…by connecting all these energy assets, devices, and systems of the internet, we can create a smart energy network that is capable of self-optimization and self-healing.”

He shed light on how the integration of IT and OT in IoT has the potential to revolutionize the energy sector by enabling more efficient, interconnected, and data-driven systems. He elaborated on how the convergence of IT and OT can optimize operations, enhance grid management, improve asset management, and enable predictive maintenance in the energy sector.

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PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023
PEPIF 2023

The PEPIF 2023 covered a wide range of topics in the electric power industry, including generation, transmission, distribution, retail, and end-use. Industry leaders and experts shared their insights on the latest trends, innovations, and challenges facing the sector. The forum provided a platform for meaningful discussions, knowledge sharing, and networking among the participants, fostering a collaborative approach toward achieving a secure and reliable supply of electricity for the country.

IEMOP expressed its immense pride and honor in successfully hosting the PEPIF 2023 and extended its appreciation to all the participants for their support and contribution to the event. The forum served as a significant milestone in promoting cooperation and partnerships within the Philippine electric power industry, toward a sustainable and vibrant energy future for the country.

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The New Era of Digitalization in the Banking and Finance Industry
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The New Era of Digitalization in the Banking and Finance Industry
The New Era of Digitalization in the Banking and Finance Industry 650 486 Exist Software Labs
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Digitalization in Banking and Finance

If there is something that is only constant in this world, it is CHANGE. As industries evolve and competition becomes more intense, financial institutions are also elevating their offerings.

The banking and finance industry has undergone a significant transformation in recent years with the rise of digitalization. From online banking to mobile payment solutions, digital technologies have revolutionized the way financial institutions operate and interact with their customers. To explore this topic further, join us on our first podcast episode, “The New Era of Digitalization in the Banking and Finance Industry.”

In our first episode, we discuss the latest trends, challenges, and opportunities in the banking and finance industry. Our expert guests share insights on how digitalization has changed the way we manage our finances, and what this means for financial institutions and customers alike. We delve into the benefits of digital banking, such as increased accessibility and convenience, and the risks associated with it, including cybersecurity threats and data privacy concerns.

Contact Us Today to Learn More about Digital Banking!

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Data Ingestion, Data Integration, Data Quality,Driven Organization
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The Importance of Data Ingestion, Data Integration, and Data Quality in becoming a Data-Driven Organization.
The Importance of Data Ingestion, Data Integration, and Data Quality in becoming a Data-Driven Organization. 650 486 Exist Software Labs

Data ingestion, integration, and quality are crucial steps in becoming a data-driven organization:

Ingesting, storing, organizing, and maintaining the data generated and gathered by an organization is known as data management. A key component of implementing IT systems that power business applications use to deliver analytical data to support operational decision-making and strategic planning by corporate executives, business managers, and other end users is effective data management.

Data management is a collection of many tasks that aims to guarantee correct, accessible, and available data in business systems. The majority of the work is done by the IT and data management teams, but business users also contribute.

Want to learn more about Data Solutions and Services? Click here.

These are the key steps in transforming a company into a data-driven organization.

What is Data Ingestion, Data Integration, and Data Quality?

  1. Data Ingestion: It is the process of acquiring data from various sources and bringing it into a centralized data repository for analysis and reporting. Without effective data ingestion, data silos can form, making it difficult to access and integrate data across the organization.

 

It involves acquiring data from different sources, such as databases, cloud storage, or even manual input, and ensuring that the data is transformed and formatted in a way that can be easily integrated and analyzed.

 

  1. Data Integration: This process merges data from different sources into a unified view, making it easier to analyze and make informed decisions. Lack of data integration can lead to inconsistencies, duplications, and errors in data analysis.

 

This step requires removing duplicates, resolving conflicts, and transforming data into a consistent format so that the data can be used effectively for analysis and decision-making.

  1. Data Quality (Cleansing): Cleaning data ensures that it is accurate, consistent, and free of errors. Poor data quality can negatively impact decision-making and hinder the effectiveness of data analysis.

 

The data quality process involves validating the data, correcting errors, and removing inconsistencies, to ensure that the data is trustworthy and fit for its intended use. These three steps are crucial for organizations to effectively leverage their data to make informed decisions, drive business growth, and achieve their goals.

By focusing on data ingestion, integration, and quality, organizations can ensure that they have a solid foundation for their data analysis and decision-making processes. It enables organizations to gain valuable insights, make informed decisions, and ultimately drive business growth and success.

Next is How to Operationalize the Data in a data-driven organization:

 

  • Establish a clear data strategy: The first step is to create a clear data strategy that aligns with the overall business strategy. This strategy should define the business problems that data can help solve, the data sources to be used, the tools and technology required, and the KPIs that will be used to measure success.

 

  • Identify data requirements: Determine what data is required to support the business strategy and goals. This involves identifying the types of data needed, the sources of data, and the frequency of data collection and updates.

 

  • Collect and process data: Collect the relevant data and process it in a way that makes it usable for analysis. This may involve data cleaning, normalization, and transformation.

 

  • Analyze data: Use analytics tools and techniques to analyze the data and derive insights that can inform business decisions. This may involve descriptive analytics, predictive analytics, and prescriptive analytics.

 

  • Communicate insights: Communicate the insights to stakeholders in a way that is clear and actionable. This may involve creating dashboards, reports, or visualizations that highlight the key findings and recommendations.

 

  • Integrate insights into operations: Use the insights to inform business operations and decision-making processes. This may involve integrating insights into existing workflows, processes, and systems.

 

  • Monitor and evaluate: Monitor the impact of the data-driven initiatives and evaluate the success against the KPIs identified in the data strategy. Make adjustments as needed to improve performance.

Overall, operationalizing data in a data-driven organization requires a culture that values data-driven decision-making, a commitment to continuous improvement, and the right technology and tools to support data collection, analysis, and communication.

 

How Personalized Banking Help Users Enjoy Digitalization?
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How Personalized Banking Help Users Enjoy Digitalization?
How Personalized Banking Help Users Enjoy Digitalization? 1300 972 Exist Software Labs

In the age of digitalization, banking has become more than just a transactional relationship between customers and banks. Today, personalized banking is essential for customer satisfaction and retention. Customers expect a seamless banking experience that meets their unique needs, and banks that can provide that experience will be the most successful. In this blog, we will explore how personalized banking help users enjoy digitalization and how digital banking solution providers in the Philippines are leading the way in providing exceptional user experiences.

Personalized Banking – What is it?

Personalized banking is the practice of tailoring banking services to meet the individual needs of each customer. It involves using customer data to deliver personalized products, services, and communication channels that are tailored to their unique preferences, behaviors, and interests. This approach enhances customer engagement and fosters long-term relationship between customers and banks.

Digital Banking Solutions Provider in the Philippines – Leading the Way

The Philippines has emerged as one of the fastest countries to adapt to digital banking in South East Asia. Banks and Financial Institutions have been able to leverage the latest trends and technologies to deliver personalized banking solutions that meet the unique needs of each customer.

User Experience – The Key to Success

In the digital age, user experience is the key to success for banks. Customers expect a seamless omnichannel experience that allows them to access their banking services anytime, anywhere, and on any device. Banks that can deliver this experience will be the most successful in the long run. Personalized banking enables banks to provide a seamless experience that meets the unique needs of each customer, whether they are accessing their banking services via a mobile app, a website, or a branch.

Predictive Analytics and Business Intelligence – A Powerful Combination

Personalized banking is powered by data. Predictive analytics and business intelligence tools enable banks to use customer data to provide personalized products and services. Predictive analytics can help banks anticipate customer needs and behaviors, while business intelligence tools provide insights into customer preferences and behaviors. By combining these two technologies, banks can deliver personalized banking services that meet the unique needs of each customer.

Process Automation – Streamlining Banking Processes

Personalized banking can also help banks streamline their internal processes. Process automation technologies enable banks to automate routine tasks and free up staff time to focus on more important tasks, such as customer engagement and product development. By streamlining their processes, banks can deliver more efficient and effective services to their customers.

The Power of AI – Enhancing the Personalization of Banking Services

Artificial intelligence is also playing a growing role in the banking industry. AI technologies such as chatbots and virtual assistants are increasingly being used to deliver personalized banking services to customers. Chatbots and virtual assistants can provide customers with quick and convenient access to banking services, while also gathering data on their preferences and behaviors. This data can be used to deliver even more personalized banking services in the future.

Seamless Processes – Delivering Exceptional User Experiences

Personalized banking can help banks deliver exceptional user experiences that are seamless and hassle-free. By using customer data to deliver personalized products and services, banks can provide a user experience that is tailored to each customer’s unique needs. This can include everything from personalized marketing messages to customized product recommendations.

Here are some of the most interesting benefits of personalized banking that can improve the customer experience:

  1. Customized Products and Services: Personalized banking enables banks to deliver customized products and services that meet the unique needs of each customer. This can include customized interest rates, loan terms, and credit card rewards programs. By offering personalized products and services, banks can attract and retain customers who are looking for solutions that meet their specific needs.
  2. Faster Service Delivery: Personalized banking can also lead to faster service delivery. By using customer data to anticipate their needs and preferences, banks can deliver faster and more efficient services. This can include faster loan approvals, quicker credit card applications, and more personalized financial advice.
  3. Improved Security: Personalized banking can also improve security by using advanced authentication and fraud detection technologies. Banks can use customer data to build risk profiles that can detect unusual account activity and alert customers of potential fraud. This can help prevent financial losses and increase customer trust.
  4. Greater Convenience: Personalized banking can also increase convenience for customers. By offering a seamless omnichannel experience, customers can access their banking services anytime, anywhere, and on any device. This can include mobile banking apps, online banking portals, and in-person branch visits. By offering a convenient experience, banks can enhance customer engagement and retention.
  5. Enhanced Customer Loyalty: Personalized banking can also enhance customer loyalty by fostering long-term relationships between customers and banks. By offering personalized products and services, banks can create a sense of loyalty among customers who feel valued and understood. This can lead to increased customer retention and referrals.

Conclusion

Personalized banking is essential for customer satisfaction and retention in the age of digitalization. Banks that can deliver personalized banking services that meet the unique needs of each customer will be the most successful in the long run. 

Exist Software Labs, Inc. is the leading digital banking solutions provider in the Philippines and leading the way in providing exceptional user experiences that are powered by the latest trends and technologies. By leveraging technologies such as predictive analytics, process automation, and artificial intelligence, banks can deliver seamless, personalized banking services that enhance customer engagement & satisfaction.

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Unveiling Challenges and Solutions for Renewable Energy Sources
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Unveiling Challenges and Solutions for Renewable Energy Sources
Unveiling Challenges and Solutions for Renewable Energy Sources 650 486 Exist Software Labs

Renewable energy is the future of our planet, but the transition to a fully sustainable energy system is not without its challenges. From technological limitations to policy barriers, there are numerous hurdles that must be overcome.

Yes, renewable energy sources have been around for centuries, and for the past few decades, they have been gaining increased attention and promotion due to the need for more sustainable, environment-friendly, and cost-effective energy sources. However, with the increasing interest, there are a few challenges that have been identified with the use of renewable energy sources.

Challenges for Renewable Energy Sources

  1. Availability of reliable sources – Depending on the type of renewable energy, such as solar, wind, or hydro, these sources are dependent on certain weather or geographical conditions. Solar energy, for instance, can only be tapped during the day, and only if the skies are clear. Similarly, wind energy is highly dependent on wind speed, and hydro energy requires a large reservoir. Having such limited availability of renewable energy sources can be a challenge to its utilization and also leads to power outages due to the lack of a reliable source.
  2. The cost associated with the use of renewable energy sources – Compared to traditional energy sources like coal and gas, setting up renewable energy sources requires higher capital investments. For example, the cost of setting up a solar panel is significantly higher than the cost of purchasing coal or gas. This higher price tag is a challenge for countries and organizations that are looking to adopt renewable energy sources.
  3. Storage of renewable energy – Since renewable energy sources are available intermittently, storing this energy for future use can be a challenge. While newer technologies are being developed to address this problem, the existing technology does not suffice to store this energy in bulk for future use.
  4. lack of infrastructure – The infrastructure needed to support renewable energy sources is often much more expensive than traditional sources of energy. This means that countries and communities that want to switch to renewable energy sources must invest in new infrastructure or upgrade existing infrastructure. This can be a difficult and costly challenge to face.
  5. Information technology – can also present a challenge for renewable energy sources. While information technology has provided a wealth of opportunities for renewable energy sources, it can also present a challenge in the form of cyber-security. For example, if a renewable energy source has been hacked, it could lead to catastrophic consequences. This is why it is essential that information technology is used responsibly and in accordance with strict security protocols.

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Despite the challenges, renewable energy sources are gaining traction due to the numerous advantages it offers. To address the availability challenge, many countries and organizations are investing in building smart grids. This allows the energy from renewable sources to be integrated with that from traditional sources, thus reducing the risk of power outages. To address the cost challenge, organizations are also offering subsidies and incentives to encourage the adoption of renewable energy sources. To tackle the storage challenge, advanced technologies like energy storage systems, such as batteries and flywheels, are being developed to ensure that the energy can be stored for future use.

Ultimately, renewable energy sources are a key component of our future energy needs. However, if we are to ensure that these sources are viable and reliable options for the future, it is important that we understand and address the challenges that they face. By investing in renewable energy sources, upgrading infrastructure, and utilizing information technology in a responsible manner, we can ensure that renewable energy sources are here to stay. With the right solutions and investments, these challenges can be addressed, paving the way for a greener future.

We understand that renewable energy poses unique challenges that require innovative solutions.

At Exist Software Labs, Inc., our team of experts is dedicated to developing cutting-edge software and hardware solutions that help energy businesses and communities make the most of clean energy.

Optimize your renewable energy production and storage, minimize downtime, and reduce energy waste with our advanced analytics and monitoring tools. Our smart energy management systems enable you to manage and control your energy usage in real-time, ensuring that you are always in control of your energy costs and carbon footprint.

By leveraging the latest technologies and working closely with our clients, we help you overcome the obstacles that stand in the way of a more sustainable future. We are committed to providing reliable and effective energy solutions that make renewable energy accessible and affordable for businesses of all sizes.

Are you ready to dive into the exciting world of renewable energy? As we look to transition to a greener future, there are certainly challenges to overcome. But fear not! With innovation and determination, we can find solutions to even the toughest obstacles. 

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Open Banking Ecosystem: Why do Banks with APIs Captivate More Users
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Open Banking Ecosystem: Why do Banks with APIs Captivate More Users
Open Banking Ecosystem: Why do Banks with APIs Captivate More Users 1300 972 Exist Software Labs

A PLACE WHERE YOU CAN SEE EVERYTHING – This is the first thought that comes to my mind about Mobile Internet Banking. Banks who adapt in digital banking are being advanced in providing quality banking experience by tailoring their offerings to their customers because of open banking.

While top banks are enjoying this kind of flexible and extensive Open-Banking, the majority are still stuck with the traditional way of banking. Taking leverage of this new technology will expedite the growth of Banks and Financial Institutions.

What is Open Banking?

It is a banking technology model that gives access to users to securely allow their data that they can share with the bank’s third parties (of course, with their consent)  to offer a personalized and seamless experience.

This banking model creates a more competitive environment by opening up new opportunities for collaboration between banks, fintech, and other financial institutions. In the Philippines, it is still in its early stages, but it is quickly gaining traction as a new and innovative way of providing financial services to customers.

The implementation of open banking in the Philippines requires collaboration between different stakeholders, such as regulators, banks, fintech, and customers. The Bangko Sentral ng Pilipinas (BSP), the country’s central bank, has created guidelines and regulations that encourage the adoption of open banking in the Philippines. These guidelines include the use of APIs (Application Programming Interfaces) to facilitate the sharing of data between banks and third-party providers.

To encapsulate how it works, Banks and Fintech have privacy policy guidelines when we are installing an app or registering to their website. This means that they designed data safety conditions that comply with regulators and the government to protect every customer’s data. 

Digital Banking in 2023 – What to Expect

Open Banking Ecosystem: Why do Banks with APIs Captivate More Users

Open banking offers several benefits to both banks and customers. Banks can leverage open banking to improve the customer experience by offering new and innovative financial products and services. For example, it enables banks to provide personalized financial advice, digital payment solutions, and other services that meet the needs and expectations of their customers.

Moreover, by partnering with fintech and other third-party providers, banks can access new technologies and expertise that can enhance their offerings.

By working together, regulators, banks, fintech, and customers can create a more competitive and transparent financial services market that benefits everyone. For banks still not adapting to this technology, it is important to stay informed about open banking and embrace this new model to stay ahead of the competition and provide better services to customers.

Executives must understand the importance of open banking and support its implementation and growth. IT experts, on the other hand, must ensure that the necessary technology and infrastructure are in place to help open banking securely and efficiently.

What are the Benefits of Open Banking?

  1. Improving competition: It allows third-party providers to offer financial services, increasing competition in the market and providing customers with more options.
  2. Enhancing innovation: It enables the development of new financial products and services through tailored promotional offerings, loyalty rewards, and other marketing advertisements based on customers’ interests, digital behavior, etc. These kinds of personalized user experiences are always with the consent of users by checking the terms and conditions when they sign up for an account. Additionally, the terms and conditions of the banks are always relying on the government’s Data-Privacy Act.
  3. Improving financial inclusion: It can help reach underserved or unbanked populations by enabling new providers to enter the market and offer financial services.
  4. Enhancing security: It can help improve the security of financial transactions by using modern technologies and standards, such as strong customer authentication.

How Should banks respond to Open Banking? Do they need to adapt?

Banks need to respond to open banking and adapt to this new model. Open banking represents a shift in the traditional banking industry and offers both challenges and opportunities for financial institutions. 

To successfully respond to open banking, banks need to adopt an open and collaborative approach. This means working with fintech, third-party providers, and other stakeholders to develop new financial products and services that meet customer needs and expectations. In order to do this, they need a Digital Banking Solutions Provider that will enable them to apply it accordingly. The effect? Banks can leverage open banking to offer new services, such as personalized financial advice and digital payment solutions, that can improve the overall customer experience.

Additionally, banks must prioritize security and data protection in their initiatives. This includes implementing robust security measures and data management processes to ensure the protection of customer data and financial information.

In short, banks need to respond by embracing it as a valuable opportunity to improve their offerings, better serve their customers, and stay competitive in the market. By adapting to open banking, banks can ensure their continued success in the rapidly evolving financial services industry.

Exist Software Labs, Inc. offers digital banking solutions for banks and financial institutions that want to modernize their systems to better serve their customers and make their banking seamless and personalized. Our solutions include but are not limited to Mobile Internet Banking, Accounts Onboarding/Enrollment, Loans Management System, & Corporate Internet Banking. 

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WESM Mindanao
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Are you prepared for WESM Mindanao’s commercial operation?
Are you prepared for WESM Mindanao’s commercial operation? 650 486 Exist Software Labs

The Independent Electricity Market Operator of the Philippines (IEMOP), operator of the Wholesale Electricity Spot Market (WESM), announced that it is preparing market participants for the official launch of the WESM Mindanao  on January 26, 2023.

Energy Secretary Raphael Lotilla signed the Department of Energy Circular 2022-12-0039 in December 2022, requiring Mindanao electric power industry participants and entities to register as WESM members.

As part of the preparations for the commercial launch of WESM Mindanao, IEMOP hosted a Focus Group Discussion(FGD) in collaboration with various energy industry agencies. IEMOP discusses the provisions of DOE Circular 2022-12-0039 and the activities leading up to WESM’s commercial operations in the region.

WESM Mindanao
WESM Mindanao

Source: WESM | Readiness checklist

“The commercial operation of WESM Mindanao and the MVIP [Mindanao Visayas Interconnection Project] is expected to improve the reliability of electric power supply not only in the Mindanao grid but also in the Luzon and Visayas grids,” according to the circular. It also stated that the commercial operation of the MVIP would require the commercial operations of WESM Mindanao to allow for the efficient transfer of electricity exchanges.

The circular also requires the market operator to facilitate WESM registration and authorize the disconnection of WESM participants and entities that are required to register but are unable to do so.

The critical roles of different agencies such as IEMOP, National Electrification Administration (NEA), Power Sector Assets and Liabilities Management Corp. (PSALM), Philippine Electricity Market Corp. (PEMC), and National Grid Corp. of the Philippines (NGCP) were also discussed in the circular.

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Among the roles played by various agencies were:

The IEMOP should also ensure that WESM Mindanao participants comply with the registration requirements and take appropriate action to address noncompliance. They should also ensure that the WESM Mindanao transitions and operates smoothly.

The PEMC will monitor and evaluate the WESM Mindanao implementation and make recommendations to address any policy issues that may arise. It will also impose sanctions and penalties following the circular’s provisions.

The NEA will assist electric cooperatives (ECs) in completing their WESM registration and coordinate with relevant agencies to ensure that the ECs meet the financial and technical requirements for WESM registration.


So the real question is, Are you ready to transition with the WESM Mindanao commercial operations?

We understand that you are committed to ensuring that your company remains compliant with the WESM rules and market manuals, but we also know that it can be difficult to keep track of all of your obligations.

That’s why we at Exist Software Labs Inc. provide Energy System Solutions, a solution that helps you:

– Automate the collection of 5-minute WESM data,
– Comply with the NEW BIR Ruling,
– Streamline submission to CRSS and NMMS,
– Seamless monitoring of MMS data such as RTD, HAP, DAP, LMP, and others,
– Generation of BCQ for CRSs upload,
– Smooth processing of CRSS Metering and Settlement data, and more! 

We will help you avoid sanctions and penalties by assisting you to ensure full compliance with all of your obligations under WESM Rules and Market Manuals.

Check out these links to help you get prepared for WESM Mindanao commercial operation

– WESM Mindanao
– WESM Operations
– WESM-Mindanao-FGD-Grid-Scheduled-Gens_QA-_clean.pdf (iemop.ph)

Avoid WESM Penalties and Sanctions Today!

Automate your processes and create a more competitive, transparent, and efficient system with our Energy Systems Solutions!

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Big Data, Data Solutions, Healthcare, Retail
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Trends and Industries: How Data Solutions upend existing sectors to new heights in 2023?
Trends and Industries: How Data Solutions upend existing sectors to new heights in 2023? 650 486 Exist Software Labs

The defining era of data is currently upon us. Business model threats and economic shocks are common. Power is changing wherever you look, including in the market, our technological infrastructure, and the interactions between companies and customers. Change and disruption have become the norm. Data Solutions have been useful in innovating the industry.

Data-savvy businesses are well-positioned to triumph in a winner-take-all market. In the past two years, the distance between analytics leaders and laggards has increased. Higher revenues and profitability can be found in companies that have undergone digital transformation, embraced innovation and agility, and developed a data-fluent culture. Those who were late to the game and who still adhere to antiquated tech stacks are struggling, if they are even still in operation.

So, when you create your data and analytics goals for 2023, these are the key trends to help you stay one step ahead of your competitors.

Healthcare

Data Analytics and Data Solutions can be used to improve patient outcomes, streamline clinical trial processes, and reduce healthcare costs. 

Some specific examples of how Analytics is being used in healthcare include:

  1. Improving patient outcomes: Analytics can be used to identify patterns and trends in patient data that can help healthcare providers make more informed decisions about treatment plans. For example, data from electronic health records (EHRs) can be analyzed to identify risk factors for certain conditions, such as heart disease or diabetes, and to determine the most effective treatments for those conditions.
  2. Streamlining clinical trial processes: Data Analytics can be used to improve the efficiency of clinical trials by allowing researchers to identify suitable candidates more quickly and by helping them to track the progress of trials more closely.
  3. Reducing healthcare costs: Analytics can be used to identify inefficiencies in healthcare systems and to help providers implement cost-saving measures. For example, data analysis can be used to identify patterns of overutilization or unnecessary testing, and to develop strategies for reducing these costs.

Financial services

Data Analytics can be used to detect fraud, assess risk, and personalized financial products and services. 

Some specific examples of how Data Analytics is being used in the financial industry include:

  1. Fraud Detection: Data Analytics can be used to identify patterns and anomalies in financial transactions that may indicate fraudulent activity. This can help financial institutions to prevent losses due to fraud and to protect their customers.
  2. Risk Assessment: Analytics can be used to assess the risk associated with various financial products and services. For example, data analysis can be used to assess the creditworthiness of borrowers or to identify potential risks in investment portfolios.
  3. Personalizing financial products and services: Analytics can be used to gain a deeper understanding of individual customers and to personalize financial products and services accordingly. For example, data analysis can be used to identify the financial needs and preferences of individual customers, and to offer customized financial products and services that are tailored to those needs.

Retail

Retail companies can use Data Analytics to optimize pricing, understand customer behavior, and personalize marketing efforts. 

Some specific examples of how Data Analytics is being used in the retail industry include:

  1. Prizing Optimization: Retail companies can use Data Analytics to identify patterns in customer behavior and to optimize their pricing strategies accordingly. For example, data analysis can determine the most effective price points for different products and identify opportunities for dynamic pricing (i.e., adjusting prices in real time based on demand).
  2. Understanding customer behavior: Analytics can be used to gain a deeper understanding of customer behavior and preferences. This can help retailers to make more informed decisions about the products and services they offer, and to identify opportunities for cross-selling and upselling.
  3. Personalizing marketing efforts: Analytics can be used to deliver more personalized and targeted marketing efforts to customers. For example, data analysis can be used to identify customer segments with similar characteristics and to develop customized marketing campaigns for each segment.
  4. Cost Reduction: Being able to have a JIT (Just in Time) procurement and storage of items which in turn increases/optimizes warehouse capacity and reduces spoilage, and improves logistics.

Manufacturing

Data Analytics can be used to optimize supply chain management, improve production efficiency, and reduce costs. 

Some specific examples of how Data Analytics is being used in the manufacturing industry include:

  1. Optimizing supply chain management: Analytics can be used to improve the efficiency of the supply chain by identifying bottlenecks and inefficiencies, and by developing strategies to address these issues.
  2. Reducing fuel consumption: Analytics can be used to identify patterns in fuel consumption and to identify opportunities for fuel savings. For example, data analysis can be used to identify the most fuel-efficient routes or to identify vehicles that are consuming more fuel than expected.
  3. Improving fleet management: Analytics can be used to improve the efficiency of fleet management by identifying patterns in vehicle maintenance and repair data, and by helping fleet managers to develop strategies to optimize vehicle utilization and reduce downtime.
  4. Forecast roadworthiness of vehicles: This can help set trends on when a vehicle would break down or need repairs based on utilization, road conditions, climate, and driving patterns.

Energy

Data Analytics can be used to optimize the production and distribution of energy, as well as to improve the efficiency of energy-consuming devices.

Some specific examples of how Analytics is being used in the energy industry include:

  1. Optimizing the production and distribution of energy: Analytics can be used to optimize the production and distribution of energy by identifying patterns in energy demand and by developing strategies to match supply with demand. For example, data analysis can be used to predict when energy demand is likely to be highest and to adjust energy production accordingly.
  2. Improving the efficiency of energy-consuming devices: Analytics can be used to identify patterns in energy consumption and to identify opportunities for energy savings. For example, data analysis can be used to identify devices that are consuming more energy than expected and to develop strategies to optimize their energy use.
  3. Monitoring and optimizing energy systems: Analytics can be used to monitor and optimize the performance of energy systems, such as power plants and transmission grids. Data analysis can be used to identify potential problems or inefficiencies and to develop strategies to address them.

Agriculture

Analytics can be used to optimize crop yields, improve the efficiency of agricultural processes, and reduce waste.

Some specific examples of how Data Analytics is being used in agriculture include:

  1. Optimizing crop yields: Analytics can be used to identify patterns in crop growth and to develop strategies to optimize crop yields. For example, data analysis can be used to identify the most suitable locations for growing different crops and to develop customized fertilization and irrigation plans.
  2. Improving the efficiency of agricultural processes: Data Analytics can be used to identify patterns in agricultural data and to develop strategies to optimize processes such as planting, fertilizing, and harvesting.
  3. Waste Reduction: Analytics can be used to identify patterns in food waste and to develop strategies to reduce waste. For example, data analysis can be used to identify the most common causes of food waste on farms and to develop strategies to address those issues.

These are just a few examples of the many industries that are likely to adopt Data Analytics technologies as part of their digital transformation efforts in the coming years. 

Other industries that are also likely to adopt Analytics Technologies include Government, Education, and Media, among others. In general, Data Analytics Technologies are being adopted across a wide range of industries because they can help organizations to gain insights from their data, make more informed decisions, and improve their operations. 

As more and more organizations recognize the value of Analytics, it’s likely that we’ll see even greater adoption of these technologies in the coming years.

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Data Science, Science and Technology
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Data Science 101: What are concepts you need to know before entering the Data Science world?
Data Science 101: What are concepts you need to know before entering the Data Science world? 650 486 Exist Software Labs

I was playing around with data and then I found the Science — Yes, my introduction to the world of Data Science has been a part of my research work.

If you’re like me, starting out with Data Science looking for resources that can give you a jump start or at least a better understanding of it or you have just heard/read the term being coined and want to know what it is, of course, you can find a gazillion materials about it, this is, however, how I started and got familiar with the basic concepts.

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What is ‘Data Science’?

Data Science provides meaningful information based on larger amounts of complex data or big data. Data-Driven Science combines different fields of work in statistics and computation to interpret data for decision-making purposes.

Understanding Data Science

How do we collect data? — Data is drawn from different sectors, channels, and various platforms including cell phones, social media, e-commerce sites, various healthcare surveys, internet searches, and many more. The surge in the amount of data available and collected over a period of time has opened the doors to a new field of study based on big data — the huge and massive data sets that contribute towards the creation of better operational tools in all sectors.

The continuous and never-ending access to data has been made possible due to advancements in technology and various collection techniques. Numerous data patterns and behavior can be monitored and it can make predictions based on the information gathered.

In technical terms, the above-stated process is defined as Machine Learning; in layman’s terms, it may be termed Data Astrology — predictions based on data.

Nevertheless, the ever-increasing data is unstructured in nature and is in constant need of parsing in order to make effective decisions. This process is really complex and very time-consuming for organizations — and hence, the emergence of Data Science.

A Brief History / Background of Data Science

The term ‘Data Science’ has been in existence for about three decades now and was originally used as a substitute for ‘Computer Science’ in the 1960s. Approximately 15–20 years later, the term was used to define the survey of data processing methods used in different applications. 2001 was the year when Data Science was introduced to the world as an independent discipline.

Disciplinary Areas of Data Science

It incorporates tools from multiple disciplines to gather a data set, process and derive insights from the data set and interpret it appropriately for decision-making purposes.

Some of the disciplinary or noteworthy areas that make up the Data Science field include Data Mining, Statistics, Machine Learning, Analytics Programming, and the list goes on. But, we would be doing a brief discussion mainly on the aforesaid topics as the concept of Data Science mainly revolves around these basic concepts, just to keep it simple.

Data Mining applies algorithms to complex data sets to reveal patterns that are then used to extract useful and relevant data from the set.

Statistics or Predictive Analysis uses this extracted data to gauge events that are likely to happen in the future based on what the data shows happened in the past.

Machine Learning can be best described as an Artificial Intelligence tool that processes massive quantities of data that a human is incapable of doing in a lifetime — it perfects the decision model presented under predictive analytics by matching the likelihood of an event happening to what actually happened at a predicted time in the past.

The process of Analytics involves the collection and processing of structured data from the Machine Learning stage using various algorithms. The data analyst interprets, converts, and summarizes the data into a cohesive language that the decision-making team can understand.

Data Scientist

Literally speaking, the job of a Data Scientist is multi-tasking: We collect, analyze and interpret massive amounts of structured and unstructured data, and in a maximum number of cases, to improve an organization’s operations. Data Science professionals develop statistical models that analyze data and detect patterns, trends, and various relationships in data sets.

This vital information can be used to predict consumer behavior or to identify business and operational risks. Hence, the job of a Data Scientist can be described as a story-teller that uses data insights in telling a story to the decision-makers in a way that is understandable. The role of a Data Scientist is becoming increasingly important as businesses rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies.

Present & Future of Data Science

Data Science has become the real thing now and there are potentially hundreds and thousands of people running around with that job title. And, we too have started seeing these Data Scientists making large contributions to their organizations. There are certainly challenges to overcome, but the value of data science from a business point of view is pretty clear at this point.

Now, thinking about the future, certain questions definitely arise — “How will the practice of data science be changing over the next five years? What will be the new research areas of data science?”

“Will the fundamental skills remain the same?”

These are certainly debatable questions, but one thing is for sure — inventions have happened and will continue to happen when there arises any demand for the betterment of the future. And, the world would keep benefiting from data science through its upcoming innovations.

The possibilities of how to utilize Data Science in real-world scenarios are endless! Our Data Solutions team would be happy to help you capitalize on this technology for your enterprise.

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