At the very heart of the financial world lies a commodity so vast it’s almost immeasurable ... and it’s growing exponentially with potential yet unrealized.
Big data – complex structured and unstructured datasets arriving from innumerable sources – is reshaping the global banking industry. Used effectively, big data can support the delivery of hyper-personalized customer experiences, real-time fraud detection, and robust risk management capabilities. Used ineffectively, big data can drown an organization, bog down efficiency, and result in regulatory fines if not managed appropriately.
Big data is the next big oil. Whether it results in a boom or a bust for banks remains to be seen.
The AI effect
The transition to and digitalization of all aspects of banking over the past few decades substantially increased the amount of data and metadata in banks’ stores. Now, even more data is pouring in from every imaginable source, and AI is the catalyst for another massive acceleration.
While AI algorithms can process and analyze massive datasets at lightning speed, AI also generates massive data volume. The AI market is predicted to grow at a CAGR of 36.6% from 2024 to 2030, and so, too, will data grow as LLMs require increasing amounts of data to learn and improve. Where does this data boom end and how will that end impact AI? Forecasters have called out that data used to train LLMs will run out by 2030. Now there’s a challenge – too much and too little all at the same time.
On the positive side, when AI is integrated effectively, it can streamline, automate, forecast and monitor in real time, leading to profound business transformation. Even more powerful, AI can extract meaningful insights from data that can, in turn, empower strategic decisions, optimize operational efficiency and revolutionize the customer experience.
So how do banks capitalize on all this data to drive a boom while safeguarding against potential spills?
Step 1: Anchor on a solid foundation
Before banks can fully tap into their data, they must first build a rock-solid base. Establishing robust data management capabilities within a strong governance framework will support long-term growth while ensuring there are no costly spills to clean up and manage. This involves:
- Data quality management: Ensure data is accurate, consistent, complete, timely and valid.
- Data security and privacy: Protect sensitive customer information and adhere to data privacy regulations such as GDPR and CCPA.
- Data governance: Implement an effective data governance framework with clear policies and procedures.
- Cultivating a culture of data excellence: Communicate clearly and transparently, establish expectations, reward innovation and ensure compliance.
Further, on the topic of data security and privacy, banks must monitor the developments as different geographies take different approaches and regulators issue requirements.
In the United States, the regulation leans to storing data within US boundaries. But, if doing business in the EU, they must also comply with regulatory requirements like GDPR. The EU is taking a different approach by setting forth multiple regulations that govern data sovereignty.
GDPR is intended to protect the data of EU citizens and allow them to take more personal control of how their data is stored and used. NIS2, the EU’s cybersecurity directive, requires banks to vet their digital supply chains, report breaches and share information. All this is to point out yet another data-related area that banks must adeptly manage and avoid any missteps.
Step 2: Store, structure and share
An overabundance of anything makes storage, organization and accessibility key to survival. While on-premise data storage has been the de facto solution for banks since the 1960s, it’s harder to scale in this heavily digital world. Mass digitalization demands a better, more adaptable, more agile solution that democratizes data and scales alongside the business.
Enter the cloud – data moved to the cloud supports:
- Storage: Cloud storage offers scalability and flexibility, allowing banks to expand storage capacity as needed, reducing the cost of supporting physical infrastructure.
- Organization: Cloud empowers banks to manage their vast data stores more effectively and supports integration with key banking systems and applications.
- Accessibility: Better storage and organization mean better accessibility. Democratizing data means it can be shared more easily, helping teams collaborate to drive innovation.
While the cloud helps banks achieve scale and efficiency, many banks are still opting for a combined approach of on-premise storage solutions and data migration to the cloud. While this approach is necessary at times, it will again require a watchful eye and expert integration if banks hope to deliver data-driven insights and desired outcomes.
Step 3: Unified platforms accelerate insights
Once a solid foundation of data governance and management has been laid, banks must continue to drive internal change to truly capitalize on the many opportunities their data offers. This requires streamlining platforms and defragmenting technology infrastructure to achieve a technology stack that aligns strategic business goals and desired outcomes.
The typical organizational and technology structure at most banks often prevents unified and holistic decisioning. How can you glean insights that inform strategic decisions if data is locked away in silos and fragmented platforms?
It's possible, but it’s also painfully slow and inefficient. A faster, more efficient, and far more effective approach to getting the most out of your data requires accessibility, integration, transformation and analysis to unlock the insights that drive true innovation and business transformation.
To achieve a more optimal state, leading banks are streamlining their infrastructure by reducing their platforms and vendors, and are investing in unified, AI-fueled decisioning platforms. These technology powerhouses help banks break down silos and integrate data from various sources – customer data, market data and operational data.
This critical integration allows banks to best leverage AI for its vast analytical capabilities and gather insights that inform innovation opportunities. This allows them to tap into new markets and revenue streams and deliver differentiated customer experiences in real time.
Step 4: Capitalize on the big data boom
Once banks have laid the foundation of governance, are appropriately managing their data and making it more accessible, and have integrated within a unified decisioning platform, they’re better able to analyze all that data to drive real strategy and transformation. This transformation delivers on the promise of the big data boom and allows banks to:
- Improve risk management: Better manage financial and operational risk, optimize capital and liquidity, more effective asset and liability management, integrated balance sheet management, model for events of significance, and transform risk management capabilities.
- Spot fraud before it happens: Pair data and AI for a more holistic view of fraud risks, uncover new and emerging threats, adapt in real time and better shield customers and the organization from bad actors.
- Optimize the customer experience: Deliver real-time, hyper-personalized customer experiences, identify high-value customer segments and deliver customized journeys that transform and deepen customer relationships.
- Enhance operational efficiency: Automate and streamline operations to direct resources toward high-value tasks that support business outcomes.
- Identify strategic opportunities: As competition increases, innovation and exploration are paramount. Effective data use delivers insights that support strategic decisions and move banks toward appropriate diversification of their business models.
The data driven future of banking
Data is undeniably driving the future of banking. Whether it’s a boom or bust scenario is up to each bank.
Banks that are unable to effectively manage, govern, and extract insights will end up busting. They’ll lose market share, fall further behind the transformation curve and ultimately risk disintermediation. Wait too long to deal with your data debacle and the increased cost will be too exorbitant to handle.
Banks that move forward expediently lay the foundation, and confidently harness the radical power of their data will gain a competitive edge where the sky is the limit, and the ride goes all the way to boomtown.
