Banking on Data: Transforming Banks with Data Intelligence

As financial institutions continue to invest heavily in technology to augment, digitize, and even disrupt traditional operations and service offerings, the concept of what constitutes a ‘bank’ continues to change dramatically. Thanks to digital tools, such as Artificial Intelligence (AI) and Machine Learning (ML), we now have a glimpse of what banks of the future may look like: intelligent and able to provide a more convenient and impeccable banking experience for all. 

While banks continue to embrace these technologies, the past year emphasized the need for financial institutions to transform digitally. Limited mobility due to the much-needed lockdowns to stop the spread of COVID-19 made it apparent that customer-centricity and financial inclusion remain a challenge in the banking sector.

In the Philippines alone, the number of unbanked adults remains one of the highest in Southeast Asia (SEA). In 2019, unbanked Filipinos were estimated at 51.2 million, out of a total adult population of 71 million, as revealed by the BSP’s Financial Inclusion Survey released in 2020. 

As a response, BSP released Circular No. 1105 last year to decrease the country’s unbanked population. This circular considers digital banks a distinct classification of banks and provides the framework for its operation and establishment. Initially, only five financial institutions were given licenses to operate as digital-only services. It was later expanded to seven last August 2021. The goal is to bring 70 percent of Filipino adults into the banked population and 50 percent to online payments by 2030.

The past year has also seen significant changes as businesses and consumers alike went increasingly digital, driving the rise of online transactions and digital payments. BSP’s latest data revealed that 20.1 percent of monthly payments volume was done digitally by the end of 2020, indicating an improvement from the 17-percent digital transactions in the first six months of the same year.

As consumers increasingly go digital, particularly amid the never normal, it is now a crucial period for financial institutions to recalibrate their banking services and help improve financial inclusion and provide better customer experiences through customer-centric service offerings. But what does it take to achieve all these? 

Unlocking Possibilities through Data Intelligence

Banking involves sifting through tremendous amounts of data gathered from various clients and transactions recorded in the bank’s systems. External sources also add up to these data, including mobile operators, social networks, and credit bureaus, among others. 

For banks to truly explore the full potential of their data, they need to ensure that the entire data lifecycle is adequately managed and governed—from data collection, recording, monitoring to visualization, analysis, and interpretation. When done correctly, data assets can add significant value to the bank’s profitability and sustainability.

With AI-enabled tools, financial institutions can effectively use and transform them into data intelligence, which is necessary for making intelligent business decisions and staying competitive and profitable. Banks need a clear data strategy to utilize the full benefits from data, which constitutes three crucial aspects. 

First is data management that involves data ownership and governance, including data collection, storage, structuring, review, cleaning, and monitoring. 

Next is reporting and visualization, which involves the creation of an intelligent view of the bank’s performance, quality of the portfolio, staff productivity, and other categories necessary to drive the business.

And lastly, data analytics, which is deemed the most challenging yet valuable part of data strategy. Through analytical models developed by banks, they can predict customer behavior, understand better their needs and preferences, and proactively manage the overall business.

As financial services become more available due to digital banking, AI-powered analytics can help banks differentiate themselves, particularly with the help of data intelligence. Nowadays, data intelligent banks utilize AI and ML to analyze and transform massive data sets into intelligent insights. With these insights, banks can understand better their collected information and provide better services and experiences to their customers while ensuring robust regulatory compliance and risk management.

Becoming an ‘Intelligent Bank’

Among the country’s banks that utilize data intelligence is the UnionBank of the Philippines (UnionBank). As part of its data strategy, the UnionBank accelerated its digital initiatives further by collaborating with SAP to create a new banking model to support customer-centric services.

With the help of SAP Data Intelligence, UnionBank integrated into their systems the first-known “Data Science Factory” model in SEA’s financial sector. This model can help the bank realize an enhanced business management, improve internal processes, and have a better end-to-end perspective of all its operations.

UnionBank’s adoption of SAP Data Intelligence for its new digital model provides several advantages. This comprehensive data management solution helps the bank transform its distributed data sprawls into critical data insights, delivering innovation at scale. 

Intelligent banks using this solution can easily find the most relevant data through enriched metadata tags, user-generated ratings and comments, and unified business glossaries. It can also build an enterprise data fabric that connects data silos and increases visibility into several data assets. 

For UnionBank, SAP Data Intelligence serves as a critical pillar in the governance and management of internal processes. It aids the bank to streamline operations and stay ahead in regulatory compliance and risk management while supporting its new digital model. It also helps equip the bank’s administrators and other internal staff with the necessary insights and tools to provide high-quality customer service.

For instance, using its Data Science Factory model, all the data and insights gathered by UnionBank can help them enable hyper-personalized accounts, allowing the customers to understand their financial capabilities better. By personalizing these accounts, the bank can support whatever specific goals their customers want to achieve. It also makes it easier to fulfill its responsibilities like providing loans, managing savings, and offering other services with ease while protecting its customers’ privacy.  

Making Transactions Easier

As UnionBank embraced this new model, the company also saw the need to improve its efficiency and communications internally, particularly since the bank handles numerous documents every day. To tackle this challenge, the bank now employs SAP Signature Management by DocuSign.

As a global reseller of DocuSign, SAP knows first-hand the great benefits that customers like UnionBank gain from the solution. It allows users to automate workflows from simple agreements to the most complex transactions like loan applications to service agreements.

DocuSign provides users the ability to send, review, and sign documents from anywhere at any time for their convenience, with network support for iOS, Android, and Windows Mobile. It also helps employees increase productivity by integrating with common document authoring applications, document management, and identity management systems. 

Embracing Intelligent Banking 

Amid the ‘never normal’ world, organizations across all industries are taking initiatives to retain their customers—banks and financial institutions are no exception to this reality. As intelligent banking becomes one of today’s most significant trends in the industry, it’s high time for banks and financial institutions in the country to embrace AI-enabled technologies for their digital transformation journeys. 

Becoming an intelligent bank does not only ensure customer retention. It also enables banks to develop innovations that make for better banking experiences while helping achieve increased financial inclusion and defining what lies ahead for the future of banking.

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