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How Digital Banks can Leverage AI-Driven Business Intelligence with Kea

By May 30, 2024Business Intelligence7 mins read
AI-Driven Business Intelligence in Digital banks


Digital banks, characterized by their online-only presence and customer-centric approach, are at the forefront of the digital revolution in the banking sector. However, with the proliferation of digital channels and the exponential growth of data, digital banks are faced with the daunting task of effectively harnessing this wealth of information to drive business growth and enhance customer experiences. 

Kea will be the go-to Business Intelligence (BI) tool for digital banks seeking to unlock the full potential of their data. Powered by advanced artificial intelligence and conversational BI capabilities, Kea offers a transformative solution that enables digital banks to navigate the complexities of data management and analysis with ease. In this article, we’ll delve into the intricacies of implementing Kea for digital banks, providing a roadmap for success in the digital age. 

The Evolution of Banking: From Brick and Mortar to Digital Banks

The Crusades played an important role in shaping the concept of banking. The trip to the holy land from Europe was wrought with many risks from diseases to bandits. The Templar knights devised a system where you could deposit money with their monastical order anywhere in Europe and they would give a receipt. The pilgrims can produce this receipt at their destination, and they get their deposit back for a small fee. Banking is not a novel concept in the new world. Everyone depends on a bank for their basic transactions. Let us view how the banking sector evolved with technological advancements.

  • Traditional Banking Landscape: Banking began as a localized affair, with physical branches serving as the primary point of interaction between customers and financial institutions. Transactions were conducted manually, relying on paper-based records and face-to-face interactions with bank tellers. Branches were central hubs for banking activities, providing services such as deposits, withdrawals, and loan applications to customers within their local communities.
  • Transition to Electronic Banking: Automated Teller Machines (ATMs) revolutionized customer access to cash by providing convenient alternatives to traditional branch visits. Additionally, the introduction of credit and debit cards facilitated cashless transactions, offering customers greater convenience and flexibility in managing their finances.
  • Advent of Online Banking: Banks began to establish their online presence through web portals, allowing customers to access banking services remotely. Online banking platforms enabled users to perform various transactions, including account inquiries, fund transfers, and bill payments, from the comfort of their homes or offices.
  • Mobile First Banking: Mobile banking apps emerged as powerful tools that empowered customers with anytime, anywhere access to their accounts. With mobile apps, users could perform a wide range of banking activities, such as checking balances, transferring funds, and depositing checks, directly from their smartphones
  • Emergence of Digital Banks: Digital banks which operate primarily without a physical branch, leverage cutting-edge technology to offer streamlined and cost-effective banking services to customers. These banks prioritize digital channels for customer interactions offering greater accessibility, lower fees, and enhanced convenience to customers, signaling the evolution from brick-and-mortar banking to fully digital banking experiences.

Top 3 Data Analytics Challenges in the Digital Banking Landscape

The lack of physical infrastructure and minimal human teller interactions for daily banking operations means digital banks require an exceptional user experience supported by robust infrastructure. These can be crafted only with improvements supported by data-driven decisions captured from customer behavior. Thus, an excellent system that can collect, store, and analyze the data churned at each customer touchpoint becomes table stakes for a digital bank. Let us explore three key data challenges faced by digital banks in data analytics and management.

Data Silos and Fragmentation

Digital banks often face the challenge of disparate data systems, resulting in fragmented data across various platforms and departments. This fragmentation impedes the ability to obtain a comprehensive view of customer data, hindering efforts to derive meaningful insights and provide personalized services. To address this challenge, digital banks must prioritize efforts to break down silos and create a unified data ecosystem.

Regulatory Compliance and Data Security

In the highly regulated banking industry, digital banks must navigate a complex landscape of regulatory requirements and compliance standards such as the General Data Protection Regulation (GDPR), Payment Card Industry Data Security Standard (PCI DSS), and Know Your Customer (KYC). Compliance with these regulations is essential to safeguard customer information, establish data accountability, maintain trust, and avoid costly penalties. By implementing comprehensive data security policies such as access controls, and obfuscating sensitive information, digital banks can uphold regulatory standards and protect sensitive customer data.

Data Access, Scalability, and Performance

As digital banks grow their customer base and expand their operations, they must contend with data access, scalability, and performance challenges. Delays in data access, slow processing times, and degraded performance impact customer satisfaction and operational efficiency. Embracing scalable solutions such as conversational business intelligence platforms is essential for digital banks to meet increasing demands and scale their operations effectively. They empower banks to derive actionable insights from large datasets, optimize business processes, and enhance decision-making capabilities, ultimately improving scalability and performance.

Overcome Data Analytics Challenges in Digital Banking with Kea

Kea is a cloud-based business intelligence platform purpose built for digital banks to interact with their data without writing a single-line of code. Powered by advanced artificial intelligence (AI), Kea offers a conversational business intelligence (BI) platform that allows users to derive actionable insights through natural language queries. With Kea, you can simply Talk to Your Data™ – ask questions in plain English or other languages and receive instant, real-time responses.

The challenges mentioned in the previous section can be easily addressed with Kea’s advanced features.

  • Data from Anywhere: The entire Kea ecosystem also encompasses our revolutionary data management product Nutcracker. Nutcracker automates data pipelines and helps Kea access data from a unified source to answer your data questions and produce actionable insights breaking data silos.
  • Access Controls: Kea has inbuilt capabilities to limit data access. With role-based access controls, Kea can ensure that data is revealed on a ‘need-to-know’ basis. Additionally, Kea can mask sensitive information such as Personally Identifiable Information (PII) like social security numbers, mobile numbers, etc. ensuring regulatory compliance.
  • Democratized Access: With Kea access data using simple English constructs from small data tables with as low as 1000 rows to huge data lakes containing terabytes of data and a multitude of measures and dimensions. This ensures data access and scalability.

The features of Kea goes beyond addressing these challenges. Check out additional reasons for implementing Kea in your digital bank.

  • No-Code Platform: You can access information from Kea without writing a single line of code with the simplest of interfaces – Natural language. This means that Kea doesn’t require any prior technical knowledge ensuring anyone can access insights.
  • Answer across formats: All of Kea’s answers can be accessed across formats – text or voice and includes an engaging visualization ensuring additional context is provided to the information.
  • Automate Reports: Most of your BI requirements are repetitive in nature like “How many loans were processed yesterday” or “Credit card growth in the last week”. Save these questions with hashtags and automate the report delivery to your desired interval – daily, weekly, monthly, etc.
  • No more stale metrics: Most of the decision-making is reactive in nature specifically because the data received through reports are outdated. Build Livestories with Kea that will ensure the insights you receive are just-in-time. No more looking at last week’s data on new account access.
  • Anytime access: You don’t have to depend on any external teams to scrap data and give you the insights. Rather get instantaneous access to your information with Kea on-the-go anytime from any time-zone.
  • Collaborate in Real-time: You don’t have to take a screenshot of the report and share it over email to get an answer from your peers. Rather invite them to the dataset and collaborate in the same platform.

The list of Kea features that can revolutionize business intelligence for your digital bank is a longer list. These are but a few impactful ones that can help you become truly self-service.

Parting Notes: Future-Proof Your Digital Bank with Kea

Looking ahead, digital banks must remain vigilant and proactive in future-proofing their operations to stay ahead of the curve. Kea offers a range of future enhancements and integrations that enable digital banks to adapt to emerging technologies and evolving market trends seamlessly. By staying updated with Kea’s latest features and innovations, digital banks can ensure that they remain competitive in the ever-changing landscape of digital banking and continue to deliver value to their customers.

Intrigued to transform your digital bank’s business intelligence practice with a futuristic solution like Kea?

Contact Us Today!

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