Explained: Digital Banking Ecosystem

Recently, IndusInd Bank added a new arsenal to its digital ecosystem. It launched Video Branch, which allows customers to communicate with their branch manager, relationship manager, or centralized video branch executive in real-time. While doing so, customers can even track all of their important financial transactions, such as initiating a fixed deposit or recurring deposit.

This is an excellent example of how building a digital ecosystem helps banks become more relevant to clients, allowing them to form stronger relationships and grab higher wallet shares.

According to Global Market Insights, the Digital Banking Market has crossed USD 8 trillion in 2020 and is expected to grow at a rate of roughly 5% from 2021 to 2027. This industry growth is due to consumers’ increased usage of mobile devices to accomplish day-to-day financial operations. Customers utilize digital banking to check their account balances, deposit checks, transfer funds and shop online. Furthermore, the expanding millennial generation (aged 16 to 34) is pushing banks to offer digital banking services and adopt a digital ecosystem strategy.

What is a Digital Banking Ecosystem?

Digital banking ecosystems are collaborations built on partnerships that use technology to provide new products and services to clients. The idea behind collaborative models like these is simple: although no single bank can cover all of its customers’ needs, a consortium of banks and digital companies can.

Collaborations with Big Tech companies such as Apple Pay and Google Pay have gained significant market share in the mobile wallet sector. Banks, on the other hand, are concerned that closer collaboration with these firms would become a Trojan horse, compromising their position.

There are three types of stakeholders in a digital ecosystem: banks, third-party service providers, and customers. The role of a third party is to act as an intermediary between the customer and the bank. However, customers have to give their consent to third-party providers to carry out financial transactions on their behalf.

Need for a Digital Banking Ecosystem

According to Everfi research, 53% of financial institution customers have moved on from their principal financial provider, with another 9% considering doing so. This explains why banks must evolve if they want to retain existing customers and perhaps attract new ones.

Regulation

Banks must now allow access to customers’ data and online payment capabilities using open API technology, with specific consent. Hundreds of thousands of new clients are introduced to the ecosystem each month as a result of open banking-enabled products being used by both users and enterprises around the world.

Increased Competition

FinTechs are taking advantage of the decreased barrier to enter into the financial services market by using their technical expertise and superior digital client experience. Due to the limited services now offered by these challenger banks, few clients have totally transitioned away from their former pillar banks.

Increasing digital and technological investments

Banks are aggressively investing in their technological systems and data both globally and locally. This lowers operating costs and provides a foundation for new revenue streams.

Changing customer behavior

A paradigm shift from the previous paradigm (provider-based) to the new paradigm (need-based) aided in the creation of one-stop-shop ecosystems to meet the wants and needs of customers. Banks can now embed their products and services at the place of need, such as embedded finance, in this new paradigm.

Over the next five years, customers expect their bank to provide them with more personalization, proactive services, and connected omnichannel experiences. COVID-19 has risen digital adoption levels, with 43 percent of worldwide respondents stating their banking habits have changed during the financial crisis.

The Benefits of the Digital Banking Ecosystem

Banks in digital ecosystems have a number of substantial advantages built-in, including strong customer relationships and well-known brands. Banks, their customers, and other stakeholders can all profit when such strengths are joined with third-party artificial intelligence (AI) and cloud-based solutions.

Increasing the reach and quality of digital products

Working with technology partners can help a bank extend its digital distribution, improve the quality of its products, and reduce client acquisition expenses.

Citibank is one of eight banks that have teamed with Google to offer Google Pay consumers digital checking and savings accounts. Citibank and others can use Google’s platform to deliver branded products and advice to digital-only clients as a result of the partnership.

Competencies in product development are outsourced

When third parties have the technology and capacity to do it better, banks may not need to develop and maintain best-in-class digital solutions and products.

M&T Bank has collaborated with LPL Financial, an investment advisor and independent broker-dealer, to provide access to LPL’s scalable platform, integrated processes, and differentiated product offerings to its brokerage and insurance advisors. M&T advisers can now focus on client connections while the bank tries to improve its efficiency and reinvests in core operations as a result of the agreement.

Providing other ecosystems with access to banking services

When customers transact in other ecosystems, they demand seamless access to bank-held data, as well as banking goods and services. Providing secure access to their systems to partners can help banks bridge ecosystem gaps and stay relevant to their clients.

Intuit’s QuickBooks uses an API technology that enables customers to better manage their financials, enabling them to access their accounts in a variety of banking and cash management functions in one place.

Providing other ecosystems with banking services

FinTechs frequently tout digital procedures and capabilities that can assist banks in providing good, frictionless, and efficient client experiences while avoiding costly updates.

PNC Financial uses OnDeck Capital’s digital onboarding process and external data sources to streamline its small business financing process. As the company claims, the agreement allows PNC to keep control over its risk appetite while reducing loan approval times from days to minutes.

Concentrating on fundamental competencies

By delegating non-core product and capability management to a third party, banks can maintain and strengthen customer connections while focusing resources on vital strategic priorities.

State Farm recently dissolved its banking, mortgage, and credit card divisions in order to focus on its core insurance business. Agents, on the other hand, continue to sell bank products to customers through their partnerships with those buyers, giving State Farm a one-stop-shop for all financial needs.

Product and service marketplaces are expanding

Ecosystems can enable a bank to disaggregate and securely market products and services to other institutions, resulting in increased revenue for the bank and value for the partner.

In the United States, HSBC has partnered with NepFin, an online commercial lending platform, to provide growth finance and international services to FinTech’s midsized business clients. The arrangement allows HSBC to reach out to digital customers it couldn’t previously reach.

Increasing the value of internal resources

Ecosystems are a cost-effective way for banks to promote their in-house developed capabilities to other banks, FinTechs, and even non-bank enterprises.

Banks and businesses can offer white-label versions of their products and services through banking-as-a-service (BaaS). BBVA will be able to commercialize its core banking functions, including payments, financing, identity verification, and account opening, as a result of the agreement.

Conclusion

Banks and financial institutions need to continuously upgrade the experience for their customers. However, while doing so they need to factor in the demographics of their customer base. While the millennials and GEN-Zs want services at their fingertips, the older generation still prefers visiting a physical office.

Banks will have to integrate new-age technologies such as AI, ML, and big data analytics into their processes to elevate customers’ experience and improve efficiency in operations. The key to success would be decoding data into actionable insights and acting in real-time. Furthermore, they need to train their workforce and help them get acquainted with news systems.

The next step in the growth of digital banking platforms would be to continuously engage, assist and educate customers accustomed to traditional banking methods. This will fastrack the revenue streams and profit in the near future.

Let’s rewind the clock for a moment. Thousands of years ago, humans had a simple way of keeping tabs on things—literally. They carved marks into clay tablets to track grain harvests or seal trade agreements. These ancient scribes kickstarted what would later become one of humanity’s greatest pursuits: organizing and understanding data. The journey of data began to take shape.

Now, here’s the kicker—we’ve gone from storing the data on clay to storing the data on the cloud, but one age-old problem still nags at us: How healthy is that data? Can we trust it?

Think about it. Records from centuries ago survived and still make sense today because someone cared enough to store them and keep them in good shape. That’s essentially what data observability does for our modern world. It’s like having a health monitor for your data systems, ensuring they’re reliable, accurate, and ready for action. And here are the times when data observability actually had more than a few wins in the real world and this is how it works

How Data Observability Works

Data observability involves monitoring, analyzing, and ensuring the health of your data systems in real-time. Here’s how it functions:

Data Monitoring: Continuously tracks metrics like data volume, freshness, and schema consistency to spot anomalies early.
Automated data Alerts: Notify teams of irregularities, such as unexpected data spikes or pipeline failures, before they escalate.
Root Cause Analysis: Pinpoints the source of issues using lineage tracking, making problem-solving faster and more efficient.
Proactive Maintenance: Predicts potential failures by analyzing historical trends, helping enterprises stay ahead of disruptions.
Collaboration Tools: Bridges gaps between data engineering, analytics, and operations teams with a shared understanding of system health.

Real-World Wins with Data Observability

1. Preventing Retail Chaos

A global retailer was struggling with the complexities of scaling data operations across diverse regions, Faced with a vast and complex system, manual oversight became unsustainable. Rakuten provided data observability solutions by leveraging real-time monitoring and integrating ITSM solutions with a unified data health dashboard, the retailer was able to prevent costly downtime and ensure seamless data operations. The result? Enhanced data lineage tracking and reduced operational overhead.

2. Fixing Silent Pipeline Failures

Monte Carlo’s data observability solutions have saved organizations from silent data pipeline failures. For example, a Salesforce password expiry caused updates to stop in the salesforce_accounts_created table. Monte Carlo flagged the issue, allowing the team to resolve it before it caught the executive attention. Similarly, an authorization issue with Google Ads integrations was detected and fixed, avoiding significant data loss.

3. Forbes Optimizes Performance

To ensure its website performs optimally, Forbes turned to Datadog for data observability. Previously, siloed data and limited access slowed down troubleshooting. With Datadog, Forbes unified observability across teams, reducing homepage load times by 37% and maintaining operational efficiency during high-traffic events like Black Friday.

4. Lenovo Maintains Uptime

Lenovo leveraged observability, provided by Splunk, to monitor its infrastructure during critical periods. Despite a 300% increase in web traffic on Black Friday, Lenovo maintained 100% uptime and reduced mean time to resolution (MTTR) by 83%, ensuring a flawless user experience.

Why Every Enterprise Needs Data Observability Today

1. Prevent Costly Downtime

Data downtime can cost enterprises up to $9,000 per minute. Imagine a retail giant facing data pipeline failures during peak sales—inventory mismatches lead to missed opportunities and unhappy customers. Data observability proactively detects anomalies, like sudden drops in data volume, preventing disruptions before they escalate.

2. Boost Confidence in Data

Poor data quality costs the U.S. economy $3.1 trillion annually. For enterprises, accurate, observable data ensures reliable decision-making and better AI outcomes. For instance, an insurance company can avoid processing errors by identifying schema changes or inconsistencies in real-time.

3. Enhance Collaboration

When data pipelines fail, teams often waste hours diagnosing issues. Data observability simplifies this by providing clear insights into pipeline health, enabling seamless collaboration across data engineering, data analytics, and data operations teams. This reduces finger-pointing and accelerates problem-solving.

4. Stay Agile Amid Complexity

As enterprises scale, data sources multiply, making Data pipeline monitoring and data pipeline management more complex. Data observability acts as a compass, pinpointing where and why issues occur, allowing organizations to adapt quickly without compromising operational efficiency.

The Bigger Picture:

Are you relying on broken roads in your data metropolis, or are you ready to embrace a system that keeps your operations smooth and your outcomes predictable?

Just as humanity evolved from carving records on clay tablets to storing data in the cloud, the way we manage and interpret data must evolve too. Data observability is not just a tool for keeping your data clean; it’s a strategic necessity to future-proof your business in a world where insights are the cornerstone of success.

At Mantra Labs, we understand this deeply. With our partnership with Rakuten, we empower enterprises with advanced data observability solutions tailored to their unique challenges. Let us help you turn your data into an invaluable asset that ensures smooth operations and drives impactful outcomes.

Explained: Digital Banking Ecosystem

What is a Digital Banking Ecosystem?