AI your auditors will sign off on.
Fluree unifies core, CRM, and loan systems into one governed knowledge graph — so every answer your teams and your AI produce carries lineage a regulator can follow.
Regulated data, unregulated sprawl.
Financial institutions run on decades of systems that were never designed to answer together. AI raises the stakes — every answer now needs provenance.
Core, CRM, and loan systems don’t agree
Deposits live in the core, relationships in the CRM, exposure in the loan system. Each holds a partial view of the institution — and none of them reconciles with the others.
Regulators expect lineage, not exports
When an examiner asks where a number came from, a spreadsheet assembled the night before isn’t an answer. Every reported figure needs a traceable path back to its source system.
Customer truth is fragmented
The same customer appears under different identities across onboarding, servicing, and compliance systems — so no team ever works from the whole relationship.
Four workloads, one governed graph.
The same unified foundation powers investigations, customer intelligence, reporting, and risk — each with lineage attached to every answer.
AML & investigations
Traverse relationships across accounts, counterparties, and transactions to surface networks that row-by-row screening misses — with every hop recorded for the case file.
Customer 360
Resolve fragmented identities into governed golden records that follow the customer across every line of business — one durable view your bankers and your AI share.
Regulatory reporting
Assemble reports from data that carries its own audit-ready lineage, so every figure traces back to the system it came from — before the examiner asks.
Risk assessment
Connect exposure, collateral, and counterparty data across portfolios to see concentrations while they’re forming — not after quarter-close.
In production across financial services.
Real institutions, real numbers — every metric below comes from a published customer case study.
Go deeper by banking workload.
Three focused solution pages for the teams closest to the work — core modernization, fintech scale, and data products.
Field notes from the people who build this.
Practitioner writing on governed data, master data management, and data-centric security in regulated industries.
From the blog
Introducing Business Intelligence Without the BI Software
What it means to ask questions of governed data directly — no dashboard backlog in between.
From the blog
Improving Master Data Management with Supervised Machine Learning
How ML-assisted matching beats brittle string-rule MDM — and what to look for when you evaluate it.
From the blog
Data-Centric Security
Why policies enforced inside the data itself outlast every application-layer perimeter.
Financial services data questions, answered.
Short answers to what banking, risk, compliance, and data leaders ask us most.
How do banks use a knowledge graph?
Banks use a knowledge graph to connect core, CRM, and loan-system data into one governed view. The same foundation powers customer 360, AML investigations, regulatory reporting, and risk, each with lineage attached to every answer.
How does Fluree create a single customer view across banking systems?
It resolves fragmented identities into governed golden records that follow the customer across every line of business. Until they are resolved, the same customer appears under different identities in onboarding, servicing, and compliance systems. One community bank unified 330,000+ customers into golden records across 113 branches.
Can a knowledge graph help with anti-money-laundering investigations?
Yes. It traverses relationships across accounts, counterparties, and transactions to surface networks that row-by-row screening misses, and every hop is recorded for the case file.
How do you make regulatory reporting traceable for examiners?
Assemble reports from data that carries its own audit-ready lineage, so every figure traces back to the system it came from. That answers the examiner’s question about where a number came from before it is asked.
Do we have to replace our core banking system to use Fluree?
No. Fluree unifies core, loan origination, treasury, and ancillary systems into an AI-ready semantic layer without replacing the core.
How does governed data make AI safe in financial services?
AI raises the stakes because every answer now needs provenance. Fluree enforces policy inside the data itself, so protection outlasts any application-layer perimeter, and each answer traces back to its source.
Can a financial institution package its data as a product?
Yes. Fluree turns governed financial data into products and portals that are packaged, permissioned, and traceable to the source. One financial services data portal indexed 500K documents and grew its knowledge base 10x.
Load the demo graph on a fresh ledger.
Financial Services ships as a working knowledge graph: 19 classes, 171 entities, 5 JSON-LD files, and 18 packaged competency questions. Load it, ask, verify.
- 01
Create a free workspace
Start free on Fluree AI, no credit card, and create an empty database. Developers can use the Fluree CLI instead.
- 02
Import the graph
Load the 5 JSON-LD files, model first. The whole dataset commits in seconds; the kit’s README walks through it click by click.
- 03
Ask the questions
Put the 18 competency questions to the AI agent in plain English and check its answers against the expected results.
Bring governed AI to your institution.
A 30-minute demo tailored to your systems — see how banks and financial services leaders unify their data and put AI to work with lineage on every answer.
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