Analytics Data-Driven Decisions at Every Level
Unlock insights across your lending operation — from collections to GL reconciliation — through purpose-built analytics pipelines.
Request a ConsultationUnlock insights across your lending operation — from collections to GL reconciliation — through purpose-built analytics pipelines.
Request a ConsultationEmpowering Institutions with Scalable, Intelligent, and Domain-Driven Services
Extracted and analysed historical GL variances, achieved full closure and cleaner book for a leading NBFC.
Trusted by the Leaders of Finance
Our analytics solutions are designed with flexible integration capabilities built specifically for banking environments. We offer multiple integration methods including API connectors, SFTP data exchange, batch processing, and real-time data streaming options. We've successfully integrated with all major core banking systems, loan management platforms, and payment processors. Our team has extensive experience working with both modern APIs and legacy banking systems, ensuring we can extract the data needed while maintaining system integrity.
We implement a comprehensive security framework adhering to financial industry standards. This includes end-to-end encryption, role-based access controls, data masking of sensitive information, and detailed audit trails. Our analytics solutions comply with major regulations affecting financial data, including GDPR, CCPA, and banking-specific requirements. We can deploy either on your premises or in secure cloud environments that meet financial regulatory standards, with all security protocols documented for audit purposes.
While results vary by institution, our clients typically see ROI in three key areas: operational efficiency (20-30% reduction in reconciliation time and reporting cycle), risk reduction (15-25% improvement in early risk identification), and revenue enhancement (5-15% increase through cross-selling opportunities identified by our analytics). For example, our bank-to-book reconciliation module saved one mid-size lender approximately 40 person-hours per week, while our early warning analytics helped another client reduce default rates by identifying at-risk borrowers 60 days earlier than their previous system.