Smart contract execution for loans and investments.

Instantaneous account setup using AI-based document verification.

Robo-advisors offering investment insights within DBUs.

AI-powered analytics enhance AVRM, DBU, ATM security by detecting suspicious behaviors.

Predictive maintenance minimizes downtime for machines.

 Biometric and behavioral AI ensures secure user authentication for transactions and access.

Multi-factor authentication (MFA) is enhanced with AI-driven risk analysis.

AI-based middleware ensures efficient communication between systems and payment switches.

Real-time monitoring and AI diagnostics ensure swift error resolution.

AI-powered chatbots to handle queries in multiple languages.

Conversational AI for self-service teller machines such as AVRM, ATM, DBU and Bank on wheels.

Real-time monitoring using ML anomaly detection algorithms.

Predictive analytics to identify suspicious patterns in transactions.

AI optimizes large transactions by analyzing market trends and providing cost-effective execution strategies.

Automated systems ensure compliance with bulk transaction rules.

 AI identifies patterns and trends during specific seasons or events, optimizing resource allocation.

Demand forecasting models enhance decision-making for staffing, inventory, and liquidity management.

 AI models use time-series forecasting and macroeconomic indicators to predict currency exchange rate fluctuations.

Sentiment analysis of global news can provide real-time insights.

 AI-driven anomaly detection models analyze transaction patterns to flag unusual activities, helping in compliance with Anti-Money Laundering (AML) regulations.

Machine learning algorithms adapt to new fraud patterns dynamically.

 AI automates screening against PEP databases and sanctions lists, reducing false positives and enhancing efficiency.

Natural Language Processing (NLP) can analyze unstructured data sources to identify PEP connections.

 AI-powered OCR and image recognition streamline document verification.

Machine learning validates identities by cross-referencing with databases and detecting forgery.

Predictive analytics identifies customer behaviors, such as churn or upselling opportunities.

AI personalizes recommendations based on historical and behavioral data.

Continuous monitoring through AI flags changes in customer profiles, risk levels, or transactions.

Risk-scoring models ensure compliance with regulatory standards.

AI-driven data management systems ensure accurate and timely updates while adhering to data retention policies.

Natural Language Processing (NLP) aids in identifying and securely deleting sensitive customer information.