Risk & Fraud Analytics, powered by MLOps.

Detect anomalies, prevent fraud, make smarter decisions, and enhance business performance.

Half Dot Pattern WhiteHalf Dot Pattern White

Fraud detection and prevention systems need real-time fraud analysis capabilities, using analytics.

Risk and fraud management systems must be able to analyze a broad range of data, past and present, to make instantaneous decisions for future organizational gain.

Leading practices can provide a catalyst to help organizations strengthen their fraud risk management program activities, particularly the application and enhanced use of data analytics to identify, validate, and monitor the risks of fraud.

Lorem Ipsum

Our AI Analytics and Data capabilities:

Delivery Services | AI Service Center Services | Co-innovate

SAP Analytics

SAC SAP BW/4HANA BOBJ/Lumira Embedded Analytics

Cloud Data Engineering

Azure | AWS | GCP Data Lake Data Pipelines

AI & Analytics

Data Science/ML Predictive Models Visualization

Data & BI

DWH | ETL | BI | MDM | DM | DG | Data Mart

Clients we work with

Partner-Logos-1
Partner-Logos-2
Partner-Logos-3
Partner-Logos-4
Partner-Logos-5
Partner-Logos-11
Partner-Logos-17
Partner-Logos-6
Partner-Logos-20
Partner-Logos-16
Partner-Logos-9
Partner-Logos-19
Partner-Logos-8
Partner-Logos-15
Partner-Logos-18
Partner-Logos-14
Partner-Logos-12
Partner-Logos-7
Partner-Logos-13
Partner-Logos-10

Affirmative Scoring, powered by MLOps

How 'Affirmative Risk Scoring' helps organizations to detect risk and prevent fraud

Affirmative scoring is applied to historical data and real-time online behaviour, to find patterns that can't be detected manually to predict future behaviour and events. The use of advanced analytics, data science and ML and AI techniques recognize customers that are identified as 'debt risk' profiles. Develop a 360-degree view, engage with your customers more effectively, and increase debt collection through voluntary payment compliance. Early automatic digital nudge techniques can be used rather than reminder letters to reduce cost of debt collection.

The process is underpinned by a multi-pronged approach which fuses innovation, business value, and insights from AI and ML capabilities, and can be applied across industries. Here’s a few examples:

Public Sector

Local Government: such as council risk predictions, predictions of vulnerable adults and children at risk, to enable early prevention strategies.

Healthcare: prediction of high-risk segments, so early interventions can be implemented. Prediction of demand can be based on various parameters: weather, seasonality, pandemic, and other factors.

Immigration authorities: traveller risk profiles to predict risk citizens, helping to reduce crimes and national security.

Private Sector

Utilities: predict customer churn, machine failures, predictive maintenance and more.

Retailers: use an amalgamation of data to assess consumers relationships and predict what customers will buy next.

Manufacturers: avoid unexpected and costly machine breakdowns, predict supply planning with higher levels accuracy, and provide a far more exceptional service.

customer-value-analytics

Our approach

Our approach at invenioLSI is to create an actionable insight driven transformation approach, enabling organizations to manage datasets ensuring accuracy and efficiency. Our methodology automates the entire data analysis workflow, providing more efficient and comprehensive insights. Our experts can help you address unique business challenges, while adding real business value, using our unique invenioLSI approach.

Send us a message

The invenioLSI team is standing by to answer your questions. Whether it's about our company, support & services, the industries we work in, or you just want to learn more, we are here to help.