Agents handle the volume. People on your team, or Semantix specialists, decide the exceptions.
Customer onboarding and verification
Agents
Check documents and watchlists and score the customer’s risk.
People decide
Approval of high-risk customers.
You measure
Onboarding time
Transaction alert analysis
Agents
Discard false positives and build the file for suspicious cases.
People decide
Decision to report to the regulator.
You measure
Alerts handled on time
Audit evidence
Agents
Gather records, approvals and reports for each control.
People decide
Final validation of controls.
You measure
Audit preparation time
New regulations
Agents
Track regulators’ publications and flag what changes in the processes.
People decide
Updating internal policies.
You measure
Regulations implemented on time
One case from start to finish
Illustrative example
The case: An unusual transaction alert fires on a business account
Agents execute
They discard known patterns, gather the history and build the case file.
The specialist decides
The analyst confirms the suspicion and decides to report it to the regulator.
Result
Case handled on time, with the whole analysis recorded.
The operation learns
The confirmed signals strengthen the rule for future alerts.
Systems usually involved
Core banking systems
Watchlists
Anti-money laundering
ERP
GRC tools
The connection builds on the systems you already have, including the oldest ones.
Governance in your area
The regulator’s rules at every step
Central Bank, LGPD and industry rules applied during execution, with a record of each step.
Cases
Results from real projects
Clients are not named, for confidentiality.
Financial servicesRisk and fraud
Fraud prevention in payments
Challenge
Manual review of transactions and of fraud committed by users, merchants and corporate clients.
What we did
Unsupervised models for each product, business rules and automatic collection of company registration data.
−70%samples sent to manual review
+25%fraud detected
Measured result
Financial servicesRisk and fraud
Fraud score in auto insurance
Challenge
Claims fraud, misuse of roadside assistance and underwriting rules without data behind them.
What we did
Supervised and unsupervised models, explainable decisions and monitoring of the model life cycle.
−20%loss ratio
Measured result
Health and pharmaRisk and fraud
Abuse at a health insurer
Challenge
Manual pre-audit of procedures and fraud in high-cost procedures.
What we did
A denial probability model, automatic retraining, scoring every 2 hours and automatic decisions on low-value requests.
R$ 1.1Min authorizations that became automatic
R$ 1.3Min procedures flagged for denial
Measured result
Energy and utilitiesData platform
Forecasting regulatory penalties at a power distributor
Challenge
Fines for long outages, fragmented low-quality data and indicators calculated by hand.
What we did
A lakehouse with a medallion architecture (Bronze, Silver and Gold) on Databricks in Microsoft Azure, machine learning forecasts, a penalty simulator and dashboards.
36%more accurate than the business team’s forecast
R$ 3.4Min avoidable fines
Expected result · Forecast measured in the pilot; the avoided fine is an expected resultDatabricks · Microsoft Azure
Your team creates its own workflows in the Semantix AI Suite Studio, in your company’s environment, with the platform’s governance and Semantix’s support.