Transforming banking operations with data portals

To succeed in increasingly challenging and competitive markets, banks need to harness data and use it to boost efficiency, become more customer-centric, innovate, make better-informed decisions and meet a growing range of regulations. They need to understand their data landscape and free their information from departmental silos in order to share it securely across the organization and beyond, all while preserving customer privacy and meeting compliance standards. 

Data portals provide a focal point for data sharing, centralizing internal and external data, enriching it and then making it available seamlessly across the business in formats, such as dashboards, visualizations and APIs, that employees can use in their working lives. 

Banks have always been significant users of technology, building up comprehensive technology stacks to run operations, communicate with customers and interact with the wider banking ecosystem. However, their sheer size can make it difficult to understand and share data assets across the business – often data remains stuck in silos within specific departments, despite its potential value to other employees. Freeing this data helps overcome four key challenges that banks face today:

Competition within banking has never been greater, with new, digital-first, fintechs offering innovative services to customers based on a combination of personalized customer service and a deep understanding of their data. To retain customers, traditional banks need to meet their changing needs, and this starts with combining, enriching and analyzing data and becoming more data-driven. 

Banks operate on a large-scale, with tens of thousands of customers, a huge range of products and multiple offices. Running operations is consequently expensive, leading to a constant requirement to reduce costs, save time within processes, and increase efficiency. Digitizing and automating workflows provides a key chance to achieve these efficiency gains, and data is crucial to powering more effective, less-costly processes. Maximizing and scaling data use also helps increase operational efficiency within the IT infrastructure, removing manual processes and generating greater ROI from technology investments.

Given their role at the heart of the global economy and in supporting their customers’ financial well-being, banks have to comply with a wide range of regulations, from protecting customer details to preventing money laundering and ensuring they have sufficient reserves in case of crisis. Data is essential to compliance, and is also vital to understanding business performance and effectively managing risk when it comes to both strategy and operations.

To retain customers and engage with government and wider society banks need to increase trust with all stakeholders. That means becoming more transparent around their operations, demonstrating ethical practices, and most importantly demonstrating their commitment towards corporate social responsibility (CSR) and environmental, social and governance (ESG) targets. Sharing data increases openness and shows their progress towards these commitments, strengthening relationships and deepening trust.

Managing data at a technical level is just the first step in increasing value from it. Banks therefore need to invest in data portals that provide a single, centralized access point to information, whether it is created internally, by partners or is third-party data that is either purchased or accessed as open data.

By providing a seamless user interface, data portals make it as easy to find, understand and use data as when buying a product on an e-commerce marketplace. This intuitive experience democratizes data, ensuring that non-technical users benefit from data, alongside data professionals such as analysts and data scientists. Everyone can use it in their working lives, helping drive better, more informed decision-making, greater efficiency and increased collaboration.

Data portals also provide greater control, with rigorous access management policies meaning that only authorized users are able to view and download specific data assets, enforcing data security, confidentiality and compliance policies. 

Overall, data portals connect data assets with users, breaking down silos and helping build a data-centric culture. All of this increases the return on investment from the wider data and technology stack, as senior management can see the tangible benefits that greater data use delivers.

Based on our experience, there are multiple ways that a data portal can be used to deliver value for banks. Here we have identified four key example use cases, where managing data and enriching it with external information benefits banks during their day-to-day operations.

Banks rely on a range of external data services to ensure that their operations run smoothly and comply with regulations. Data could be collected from sales partners, subsidiaries, be bought from commercial providers (such as credit check information), be openly available demographic or geographic information (such as addresses), or public reference data, such as company details.

By centralizing all of these different data sources and making them available internally through a data portal, banks are able to:

• Ensure that everyone is accessing the same single source of truth, removing concerns that external data is out-of-date or incorrect
• Integrate and cross-reference different data sources, including customer, public reference and demographic data to deliver a complete picture of customers and markets
• Run analysis based on external data and identify innovative new service offers based on combining customer and external data
• Remove duplication, avoiding different parts of the bank buying or downloading the same data, saving money and reducing administrative complexity
• Feed relevant data into every system within the bank, using APIs to automate the process and create robust, transparent data flows
• Encourage the greater use of external data by users by making it available in a single location where it is clearly described and can be quickly discovered
• Run more efficient Know Your Customer (KYC) checks by cross-referencing internal records against external socio-demographic data
• Reduce fraud and highlight potential money laundering attempts by carrying out both hot checks against external databases during the onboarding process and cold checks on existing customers. 
• Better manage risk by centralizing data sources and ensuring that processes are followed correctly.

AI models offer the potential to transform how banks analyze and act on their enormous volumes of data. However, most existing Large Language Models (LLMs) are trained on generic data, rather than information that is specific to banking or the bank itself. This means any responses they provide will lack sector or organizational context, limiting their usefulness and potentially leading to inaccurate decisions being made.

Instead, comprehensive data collected and stored on data portals can be used to better train LLMs. They bring together sector-specific data, often available through open licenses, with the bank’s own data, stored in structured, machine-readable formats. These multiple data assets can then be integrated with AI models through APIs and custom metadata, fine-tuning outputs to improve accuracy, create greater trust, and generate deeper business value through contextualized outputs. Models can be continually fed with new data to maintain relevance, increasing value over time.

Banks make an enormous number of decisions every day, particularly around the services and terms they offer to customers. For example, if someone applies for a loan to buy a specific car, the bank needs to check their credit worthiness, analyze the vehicle itself and deliver a personalized quote in terms of interest rates and length of the loan period, based on understanding all risks. And they need to do this at scale, processing potentially thousands of loan applications every day. The more data banks can access when making such decisions, the more informed they will be, enabling them to offer compelling quotes more quickly to customers, while managing risk. 

Taking the example of making a car loan, banks can use their data portals to import publicly available data on the individual car being purchased, including its age, driving history, emissions and value, and then combine it with credit score and internal information to create a single dataset that is made available to decision-makers, both through dashboards and by feeding into company CRM systems. This enables more data-driven decisions that maximize revenues while minimizing risk.

Customers now demand a more personalized experience from their bank, based on their individual needs. At the same time errors in customer records (such as incorrect spellings of names or addresses), disrupt business processes through poor quality data.

Banks can deliver this personalized, efficient service by enriching their own datasets with external geographical and socio-demographic data. By making this information available via their portal, bank employees can automatically geocode postal addresses, spot and correct errors and apply context (such as around the customer’s location or demographic background), to deliver a tailored experience that matches their needs and increases loyalty over time.

Banks have to maximize the value of their data by sharing it across the organization. As these use cases demonstrate, centralizing information in a single data portal makes it easy for all authorized users to access data on a self-service basis through APIs, breaking down data silos and duplication. This increases control, security and governance, while increasing operational efficiency and boosting ROI from data and technology investments. Banks can manage risk more effectively while meeting changing customer needs, benefiting everyone and increasing loyalty and revenues moving forward.