Commercial & Retail Banking

Use Cases

Commercial & Retail Banking

Opensee helps across multiple data sets to manage the bank's resources and produce regulatory reports with consistency, speed and granularity.

Flip the cards and see how we address these common pain points

Manual and painful process

for regulator and top management on demand request (covid, sector…)

Business-user empowerment

Intuitive UI, connector to traditional BIs, low code API, user-defined functions in Python

Manual certification process

inefficient and high operational risk

Smart certification

Automated error detection and raw-level certification

Slow and complex impact analysis

on regulatory metrics (LCR/NSFR, RWA, IFRS, moratorium, …)

Integrated post-processing

Python-based user-defined functions and pre-built templates (Portfolio Analysis, RWA & IFRS Simulations…)

Segmentation of data sets

(between Front Office, Risk & Finance)

Single data environment

No size limits and a flexible data model enabling: a single source of truth, completeness, and cross dataset queries

High infrastructure costs

to keep history and portfolio granularity (loan origination, retail mortgages…)

On-disk technology

Achieving horizontal scalability using commodity hardware with no compromise between history and granularity

Maintaining Data Integrity

during the Quarterly Accounting Period

Direct access by the users

for different usages with versioning and audit trail

Key benefits Opensee delivers


decrease of liquidity buffers


flexible, frequent reporting to top management and regulator


infrastructure cost savings vs. in-memory solutions


Go-to-Markets on key projects (eg loan origination)


savings on the certification process on top of the exhaustivity and quality


Management of RWA and IFRS charges

Open and see our other use cases

Open and see our other use cases

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