FINANCIAL SERVICES DATA MANAGEMENT

Every record you keep, in full view.

Financial services data management for banks, asset managers, and insurers: Diskover indexes statements, research, recordings, model files, and backups across every file share, object store, and cloud bucket, so records teams know what they hold and IT stops paying to store what nobody needs.

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34%

of organizations know where all their data is

Thales, 2026

1

catalog across every share, bucket, and archive

Diskover

$63.1M

in SEC penalties to 12 firms for failing to keep electronic communications

SEC, 2025

THE PROBLEM

Auditors see the tip. Storage holds the rest.

Banks and investment firms keep records for years, on purpose. They also keep everything else: copies of every backtest, exports nobody asked for, and files from people who left long ago. When everything is kept, nobody can say what a record is and what is clutter. Only 34% of organizations know where all their data is, according to the Thales 2026 Data Threat Report.

Diagram of financial services storage: current client files above the surface, statements, recordings, chat exports, and backtest copies below.

HOW IT WORKS

From scattered files to clear action.

01

CONNECT

Point Diskover at file shares, object storage, cloud buckets, and archives. Indexing runs in place, read-only, so records never leave the systems your controls already cover.

Global visibility

02

CATALOG

Every file becomes a searchable record with rich metadata, such as name, path, owner, and permissions, enriched with business unit, desk, and record type from your directory and folder structure.

Metadata catalog

03

ORGANIZE

Tag files by record class, retention period, and legal hold. Build saved searches for what records and compliance teams ask every month.

Data intelligence

04

ACTIVATE

Move records to the immutable storage you choose, archive cold data, and run defensible deletion when retention ends, each action with a preview and an audit trail.

Orchestration

BUILT FOR FINANCIAL SERVICES

Diskover speaks records.

Explore the plugin suite

Knows your record types.

File Kind groups statements, recordings, exports, and model files into the record classes your policy uses.

Reads your folder logic.

Desks, funds, clients, and years, recognized from paths and names with path tokens.

Adds business context.

Plugins add business unit and owner from Active Directory or LDAP, so every file has an accountable owner.

Keeps every file closed.

Diskover finds likely sensitive files from metadata, such as names, paths, and owners, without opening them.

WHO FEELS IT

Three teams. Three different pains.

RECORDS • COMPLIANCE

“What must we keep, and for how long?”

  • Retention periods differ by record type.
  • Legal holds must cover every copy.
  • Audit answers start with weeks of searching.

With Diskover: tag every file by record class and retention date, and keep legal holds on every copy.

IT • STORAGE

“Why do we keep every backtest forever?”

  • Copies of the same data on every tier.
  • Old exports and backups nobody owns.
  • Storage bills grow faster than headcount.

With Diskover: find duplicate exports and old backtests, and move or delete them by policy.

DATA • QUANT • AI

“Which data can our models use?”

  • Training data spread across teams and shares.
  • Client data mixed with research data.
  • No record of what a model learned from.

With Diskover: select approved data for models, leave out client data, and keep a record of what was used.

WHY IT MATTERS

Keep what you must. Let go of the rest.

In January 2025, the SEC announced that 12 firms paid a combined $63.1 million for failing to keep and preserve electronic communications. With context on every file, firms keep records for as long as the rules require, put a cost on storage, and stop paying for copies nobody needs.

Explore data intelligence

Cut the copies.

Duplicate exports, old backtests, and orphaned files move or go by policy, with an audit trail.
Defensible deletion

Cost every desk.

See storage cost by desk, fund, or business unit, so each team knows what it keeps.
Chargeback

Answer audits faster.

Find every record by class, owner, and retention date when the regulator asks.
Retention policy

Reduce exposure.

Find likely sensitive files from metadata, so they are known and accounted for.
Sensitive data discovery

AI READINESS

Prepare financial data for AI before it reaches a model.

Explore AI-ready data

01

TAG

Rules tag approved datasets and reference data as they are indexed, and record which files each dataset holds.

02

CURATE

Select research, filings, and documents by any metadata, such as desk, client, date, or record type. Path tokens turn folder names into search fields.

03

GOVERN

Flag likely client and account files from names and paths, so rules leave them out of the training set. Every dataset keeps its lineage.

04

DELIVER

Send curated file lists to Snowflake, your lakehouse, or your AI platform as Parquet, through the REST API.

REAL-WORLD USE CASE

One index feeds compliance and Snowflake.

An Australian financial institution uses Diskover as the inventory behind its data compliance work.

THE CHALLENGE

  • File data spread across many shares and systems.
  • A data compliance program needed a complete inventory.
  • Analytics teams needed the same inventory in Snowflake.

HOW THEY USE DISKOVER

  • Diskover indexes the file estate in place.
  • Automated classification runs on metadata and tags.
  • The Diskover index is a source for Snowflake.

Zero

files opened, everything is cataloged from metadata only

Automated

classification of the file estate

Snowflake

gets file metadata as rows that analysts can query

FAQ

Common questions.

Scattered data points flowing into a single stream that becomes organized data paths across a world map.

See it on your own records.

We will index a sample of your file shares and show you what is recoverable against your current storage spend.

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