Taxonomy Vs Ontology in Banking

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A taxonomy and ontology are similar but very different methods to organize data and show relationships. While both offer distinct frameworks to classify and relate information, each suited to different organizational needs. Both serve as foundational elements in managing and leveraging data but differ fundamentally in structure, purpose, and application. In this article we focus on the banking application domain, without further ado, let’s take a look at how they differ and why it matters.

Taxonomy

A taxonomy is a hierarchical classification system that organizes information into categories and subcategories.
Banking Taxonomy Example:
Banking Products
  • Accounts
    • Checking Accounts
      • Personal Checking Account
      • Business Checking Account
    • Savings Accounts
      • Personal Savings Account
      • Business Savings Account
      • High-Yield Savings Account
    • Certificate of Deposit (CD)
      • Short-term CD
      • Long-term CD
  • Loans
    • Personal Loans
      • Secured Personal Loan
      • Unsecured Personal Loan
    • Business Loans
      • Small Business Loan
      • Equipment Loan
    • Mortgage Loans
      • Fixed-rate Mortgage
      • Adjustable-rate Mortgage (ARM)
  • Customer Segments
    • Personal Banking
      • Individual Accounts
      • Joint Accounts
    • Business Banking
      • Small Business Accounts
      • Corporate Accounts
    • Private Banking
      • High-Net-Worth Individuals (HNWIs)
      • Ultra-High-Net-Worth Individuals (UHNWIs)

Ontology

An ontology organizes information and defines the relationships between different categories and concepts. Beyond the simple hierarchy seen in taxonomies, an ontology allows for multiple types of relationships, showing how things connect and interact.
Banking Ontology Example:
  • Customer
    • Has: Accounts (e.g., Savings Account, Checking Account)
    • Performs: Transactions (e.g., Deposits, Withdrawals)
  • Accounts
    • Type: Savings Account, Checking Account, Loan Account
    • Has: Interest Rate
    • Is Linked to: Bank Branch (where the account is managed)
  • Transactions
    • Involves: Money Transfer
    • Relates to: Currency (e.g., USD, EUR)
    • Has: Transaction Date, Amount
  • Loan
    • Is Taken by: Customer
    • Is Secured by: Collateral (e.g., Property)
    • Has: Interest Rate, Repayment Schedule
  • Property
    • Has: Value, Location
    • Is Related to: Mortgage (Loan type)

Why It Matters

Connections and interactions among categories and concepts simulate thought processes and considerations used by humans when making decisions.

Ontology frameworks, and the knowledge graphs built upon them, supercharge GenAI applications with rich, contextual insights—enabling decision-making at a speed and scale far beyond human capability.

Supercharge Your Data with DataKite.ai

GenAI is poised to transform the banking industry by enhancing customer service, reducing risk, improving compliance, and streamlining operations.
Now is the time for banks to adopt ontologies, knowledge graphs, and GenAI to stay ahead in an increasingly data-centric world and secure their position in the financial landscape of the future.

DataKite.ai supports banks by streamlining data management and implementing AI-powered technologies. Contact us to see how Datakite.ai can help make GenAI work for your bank.