A queue that grows faster than the team
Applications, onboarding requests and alerts arrive in volume, and each one needs reading, checking and an opinion. Hiring at the same pace does not add up.
AI flows for financial institutions
Credit, onboarding and AML with AI, without data leaving the building.
Ready-made Aptabit Platform templates for credit analysis, onboarding, document forensics, PEP screening and anti-money laundering. Adapt them to your policy, connect them to your credit pipeline and run everything on the institution's infrastructure.
- Runs on your infrastructure
- Local or cloud models
- Fixed license, no per-analysis fees
Same requirements, smaller team.
Credit analysis, customer onboarding and anti-money laundering demand the same care at any institution. What changes is how many people are available to do it every day.
Data that cannot leave
Income, debt, documents and account activity are protected by banking secrecy and data protection law. Sending them to an AI hosted by a third party creates a bigger problem than it solves.
Decisions that must explain themselves
Internal audit, external audit and the customer can all ask why an opinion came out the way it did. An answer with no recorded reasoning is not enough.
Ready-made flows for the daily work of a financial institution.
Each template becomes a draft in your workspace, already linked to the configured AI model. From there the flow is yours: change the instructions, fields, rules and destinations.
Credit and collections
Consumer credit analysis
Assesses an individual's risk from income, debt and requested amount, and returns a recommendation, risk band, suggested limit and reasoning.
Business credit analysis
Credit opinion for companies based on revenue, debt and industry.
Proof of income analysis
Extracts and validates declared income, flagging discrepancies.
Smart collections
Builds the collection schedule and message suited to the customer profile and the stage of the debt.
Onboarding and prevention
KYC onboarding
Extracts and validates customer data to open the relationship.
Document forensics
Looks for signs of tampering in data extracted from ID cards, driver's licenses and proofs of address.
PEP and sanctions screening
Assesses whether a name or profile shows signs of being a politically exposed person or on a restricted list, and the associated risk.
AML screening
Analyzes a transaction or alert and rates the money laundering risk, with the reasoning for the analyst.
Compliance and controls
Compliance review
Checks a text or process against a regulatory checklist and points out gaps.
Data anonymization
Identifies and redacts sensitive personal data in a text.
Audit report
Generates an audit report from events and findings.
Vendor due diligence
Assesses a vendor's risk from the data provided and the knowledge base.
Back office and customer service
Bank reconciliation
Extracts entries from a statement and flags discrepancies against the expected entry.
Contract extraction
Extracts parties, amounts, terms and obligations from a contract.
Risk clause analysis
Points out risky clauses in a contract and suggests changes.
Knowledge base support
Answers customers using the knowledge base, with a polite fallback when it cannot find the answer.
From template to production in four steps.
The template saves you the blank page. The fine tuning stays with the people who know the institution's policy.
- 1
Pick a template
One click creates the flow as a draft in the workspace, with the AI model already linked.
- 2
Adapt it to your policy
In the visual editor you change instructions, input fields and decision rules, and add lookups into internal manuals and policies.
- 3
Publish and connect
Every published flow gets its own API endpoint and token. Your core system, credit pipeline or CRM calls the flow and receives a structured result.
- 4
Keep the analyst in control
Decision blocks separate what runs automatically from what goes to human review, with tracing and audit.
AI that runs where the data already lives.
Aptabit Platform is installed in the institution's environment. A credit application does not need to pass through another company's cloud to be analyzed.
On your infrastructure
Docker, Kubernetes or on-premise. Database, files and vectors stay in your environment.
Local models
Run models with Ollama, vLLM or LM Studio, or bring your own key from a cloud provider.
Cost that does not grow with volume
Fixed license, no fees per analysis, token or user. More applications do not mean a bigger bill.
Access under control
Isolated workspaces, roles, RBAC, ABAC and an audit trail.
Built for
Questions from teams evaluating it
Does customer data leave the institution?
No. Aptabit Platform runs on your infrastructure and, with a local model, inference happens there too. If the institution prefers a cloud model with its own key, that choice is its to make.
Does the AI approve credit on its own?
Only if the institution designs the flow that way. The templates deliver an opinion, a risk band and a recommendation with reasoning. What runs automatically and what goes to an analyst is set with decision blocks and human approval.
Can we use our own credit policy?
Yes. The template is a starting point. Policies, manuals and internal rules go into the workspace knowledge base, and the flow checks those documents before issuing its opinion.
How does a flow talk to our systems?
Every published flow exposes an API endpoint authenticated by token. Your core system, credit pipeline or CRM sends the data and receives a structured response. HTTP, webhook and MCP integrations are also available.
How is it priced?
Fixed license, with capacity limits set in the contract. There are no fees per analysis, per token or per user.
Where do we start?
With a diagnosis of the process with the most volume or the most risk. Then we install the platform in your environment, put a first flow into a pilot and expand from the results.
Demo
See the flows running on a case from your institution.
Tell us what you want to automate first. The conversation starts with the process, not the tool.
- 1We map the process and the volume you want to tackle
- 2We show the templates applied to that case
- 3We design a single-flow pilot on your infrastructure