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12+

Countries where we have happy customers

1050+

Agile enabled employees

06

World wide offices

12+

Years of Experience

05

Agile Coaches

14

Certified Scrum Masters

1000+

Clients projects

1458

Happy customers

Overview

Zenith Bank, a leading financial institution in Southeast Asia, faced increasing challenges in managing credit, operational, and market risks due to evolving regulatory requirements and market volatility. They sought an AI-driven solution to enhance their risk management framework and optimize decision-making processes.

Technical Stack

  • TensorFlow
  • Kafka
  • Spark
  • SAS
  • MongoDB
  • Azure

    • Industry

    Banking & Finance

  • region

    • Region

    Southeast Asia

  • project-size

    • Project Size

    Non- Disclosable

Highlights

Reduced non-performing loans by 20% within six months.

Decreased operational risk identification time by 30%.

Enhanced risk-adjusted returns through real-time market insights.

Strengthened decision-making with AI-driven predictive analytics.

Improved compliance with automated risk management processes.

Challenges & Solutions

Zenith Bank struggled with accurately predicting credit defaults due to limited data integration and outdated scoring models.

  • Solution: Our AI development team implemented a machine learning-based credit scoring system that integrates real-time data from various sources. Using advanced predictive analytics, the model provided more accurate credit risk assessments. The solution reduced non-performing loans by 20% within six months, enabling the bank to make more informed lending decisions.

Manual processes led to delays in identifying operational risks, impacting the bank's efficiency and compliance with regulatory standards.

  • Solution: We deployed a Natural Language Processing (NLP) system to analyze unstructured data from internal reports, customer feedback, and incident logs. The system flagged potential operational risks, enabling the bank to mitigate issues proactively. This automated process decreased risk identification time by 30% and improved compliance adherence.

Zenith Bank faced difficulties in responding to market fluctuations swiftly, affecting its trading desk operations and portfolio management.

  • Solution: Our team developed a real-time market risk analytics platform using deep learning algorithms. This platform continuously monitored global financial markets and provided instant alerts on high-volatility events. The system's predictive capabilities allowed the bank to adjust its strategies promptly, minimizing potential losses and enhancing its risk-adjusted returns.

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12+

Years of Business
Experience

1458+

Happy
Customers

12+

Countries with
Happy Customers

1050+

Agile enabled
employees

Core Features

  • Real-time Data Integration
  • Advanced Predictive Analytics
  • Automated Risk Identification
  • Dynamic Market Monitoring
  • Regulatory Compliance
  • no.-of-resources

    • No. of Developers

    06

  • time-frame

    • Time Frame

    February 2023 - November 2024

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