advanexus

Modular Data Platform for the Banking Ecosystem

The Platform for Data Integration, Visualization, Processing, and Control

Engineered with precision.
Designed around the real needs of institutional systems.
Adapted for highly regulated operational environments.

Founder: Milovan Tomašević, PhD

Concept: advanexus operates as a technical layer above existing operational systems, automating data integration, migration, standardization, and control — across the entire financial ecosystem.

Shared Challenges Across the Banking Ecosystem

Banks	Central Bank
multiple database systems (DB2, Oracle, MSSQL, PostgreSQL…) CSV / XML / JSON + internal proprietary formats manual procedures and Excel dependencies large daily and monthly batch processes inconsistent technical interpretation of rules difficult implementation of new regulatory changes incidents without a clear audit trail	no unified technical model across banks inconsistent technical implementations of the same regulation complex data consolidation and comparison limited visibility into banks’ data preparation need for a centralized sandbox environment need for stronger DQ rules and validations technically complex changes for new regulations
Shared reality: Data comes from different systems, in different formats, and with varying quality — and must be unified, stabilized, and standardized.

The platform that accelerates, standardizes, and simplifies data operations

advanexus removes key technical barriers: slow data transfer, inconsistent formats, complex workflows, real-time limitations, and lack of standardization.
Designed for the entire data ecosystem: non-technical users, data engineers, and data scientists.
Delivers zero-downtime operations, high speed and efficiency, and simplified workflows.
A single platform that accelerates operations, improves data quality, and streamlines the development and management of critical processes.

Data Integration & Standardization

Area	For Banks	For the Central Bank
Source Integration	Connects to DB2, Oracle, PostgreSQL, MSSQL, CSV/XML/JSON, APIs, MQ, and internal formats — without modifying core systems	Unified, stable, and controlled technical data flow from all banks
Data Standardization	Maps existing structures to standardized models (transactions, liquidity, DWH feeds, new regulations)	Identical format from all banks → easier comparison, consolidation, and supervisory insight
Flexibility	Banks retain their internal models and architectures	The central bank gains a unified, technically consistent data model
Implementation	Introduced gradually — from a single domain to full workflows	A unified technical implementation for all participants in the ecosystem

C++ High-Performance Modules

Banks	Central Bank
Processes massive batch workloads in minutes instead of hours	Stable and deterministic execution times
Fast migrations and large-scale transformations with no downtime	Reliable alignment with regulatory deadlines and daily cut-offs
Minimal resource usage during critical overnight windows	Predictable, consistent sector-wide processing

Audit, Versioning & Incident Forensics

Banks	Central Bank
Clear audit trail of who did what	Transparent insight into all critical processing flows
Detailed forensics and incident analysis	Ability to reconstruct reports retrospectively (replay)
Versioned rules and processes for each change	Compliance oversight across all participating institutions

Key Use Cases

Use Case	What Banks Gain	What the Central Bank Gains	Unique Advantage
1. Data import & preparation	Less manual ETL work	Standardized input	Ingest + automatic SQL generation
2. Source integration	Single point for DB/API/files	Consistent formats from all banks	Broadest connector ecosystem
3. Data standardization	Clear, unified structures	True comparability across institutions	Internal business model
4. Analytics & visualization	Local dashboards	Faster controls	SQL + visualizations in one place
5. Backup & restore	Operational stability	Forensic reconstruction	Unified backup/restore engine
6. Automated SQL execution	Fewer manual operations	Full transparency	Centralized job control
7. Cross-DB schema transfer	Lower migration risks	Validation of large transformations	Algorithmic dependency detection
8. Dependency management	Optimal execution order	More predictable deadlines	Parallelism scheduler
9. Data Quality	Fewer errors	Standardized controls	DQ built directly into pipelines
10. Scheduler	Predictable execution	Better coordination	Central orchestrator
11. Python Sandbox	Analytics + ML	Validation of statistical models	SQL + Python together
12. Fast file analysis	Instant preview	Faster intake & checks	Every file → queryable table
13. API integrations	External data exchange	Consolidated access	Zero additional coding
14. Knowledge Base	Faster onboarding	Clear documentation	First platform with integrated knowledge

Complete Shared Flow

Step	Banks	Central Bank	Shared Value
1. Data acquisition and loading	Data from core systems, databases, and files	Receiving unified, pre-prepared datasets	Controlled and consistent input across the ecosystem
2. Model mapping	Converting local formats into a shared model	One technical model for all participants	Easier consolidation and comparability
3. Validation & Data Quality	Local DQ rules and technical checks	Central DQ rules and oversight	Stable data quality across the entire flow
4. Process automation	Jobs executed without manual work	Predictable timelines and coordinated schedules	Reduced operational risk
5. Visualization & reporting	Dashboards and quick insights	Harmonized view for all participants	Transparency and clearer information
6. Audit & forensics	Local logs and history	Centralized view of all processes	Easier incident identification and reconstruction
7. Sandbox testing	Testing new rules and processes	Validating banks before production rollout	Safe implementation of changes

Technical Architecture

Banks	Central Bank
Isolated instances	Aggregation (central) layer
Ability to maintain bank-specific models	Standardized reference model
High integration flexibility	Transparent validation and supervisory insight

Note: advanexus is fully multi-tenant — operating independently per bank while also supporting a unified central node.

What makes advanexus unique

On-premises / cloud / hybrid deployment – operates within existing infrastructure or in the cloud.
No changes to existing systems – works as a technical layer above core platforms.
End-to-end workflow in a single platform – from data acquisition and standardization to quality checks and audit.
Modular architecture – institutions use only the components they need.
Designed for the entire banking ecosystem – one unified process with different oversight views (banks / central bank).
Enables a unified technical standard across the banking ecosystem.
AI-ready – AI assists the workflow but does not govern critical processes.