01/09/2025
Here’s a comprehensive list of terms associated with AI adoption in the Nigerian banking industry 👇
🔹 Core AI Technologies
Machine Learning (ML): Algorithms that learn from data to improve decision-making.
Natural Language Processing (NLP): Powers chatbots, voice banking, and text analytics.
Robotic Process Automation (RPA): Automates repetitive back-office banking tasks.
Predictive Analytics: Forecasts customer behavior, credit risk, and fraud.
Computer Vision: Used in biometric verification like facial recognition for KYC.
🔹 Customer Experience & Engagement
Chatbots & Virtual Assistants: AI-driven support for 24/7 customer service.
Voice Banking: Transactions and inquiries using voice recognition.
Personalized Banking: AI tailors financial advice and product offerings.
Sentiment Analysis: Understanding customer feedback from social media and complaints.
🔹 Risk & Compliance
AI-Powered Credit Scoring: Alternative data-driven loan assessment.
Fraud Detection Systems: Real-time monitoring of unusual transactions.
Anti-Money Laundering (AML) AI: Identifying suspicious activities.
RegTech (Regulatory Technology): AI tools for compliance with CBN/NDIC rules.
🔹 Operations & Efficiency
Process Automation: Reduces manual tasks in account opening and reconciliations.
AI in Treasury & Trade Finance: Enhances forecasting and liquidity management.
Smart Document Processing: AI extracts and processes customer data.
ATM & Cash Forecasting: AI predicts demand to reduce shortages/downtime.
🔹 Innovation & Future Trends
Open Banking & APIs: AI enhances interoperability and data-driven services.
AI-Powered Cybersecurity: Protects against phishing and hacking attempts.
AI in Wealth Management (Robo-Advisors): Automated investment advice.
Blockchain + AI: Improves transparency in payments and settlement.
Explainable AI (XAI): Ensures transparency in AI-driven decisions.