Megaladata Decision Maker

Finance

Megaladata Decision Maker is an automated decision support system that helps businesses process e high volumes of complex requests quickly and accurately.

When dealing with multi-stage business processes and a growing flow of incoming applications, it becomes impossible to manually ensure high decision-making speed and acceptable service quality. Automation reduces human error, which accounts for over 60% of operational losses: mistakes, incomplete checks, internal fraud and inefficient workflows. Megaladata Decision Maker eliminates these risks.

How it works:

Identifies clients across internal sources (core banking systems, CRM, etc.) and extracts all relevant data
Automatically sends requests to external data sources and consolidates responses
Applies business rules, scoring models, and risk matrices to evaluate each application
Produces a final decision or a set of recommendations for the underwriter

Ideal for:

Banks and credit institutions managing consumer or corporate lending pipelines
Microfinance and leasing companies needing fast, scalable credit decisions
Insurance providers requiring automated risk assessment and underwriting
Marketing and compliance teams needing structured counterparty or supplier analysis

Its modular design lets you combine or use components separately, in any order.

This flexibility supports custom workflows that align with your regulations and processes.
In an environment where speed and accuracy directly impact revenue and customer experience, Megaladata Decision Maker ensures both without compromising control or compliance.

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Automated Multi-Source Verification

Performs real-time checks across internal systems (core banking, CRM) and external services (credit bureaus, government registries, mobile operators) and consolidates all data into a single client profile.

Business Rules Management (BRMS) & Scoring

Supports complex business rules with multiple levels, including pre-scoring, stop-factor checks, and blacklist verification. All rules are customizable to match your internal policies. Scoring models can be updated without any system downtime.

High-performance decision engine

Designed for scalability, the system processes over 10,000 applications daily on a single server, even under peak loads. A full creditworthiness assessment, including multiple bureau queries takes 1-3 minutes per application.

Features

Internal source checks

Identifies clients across internal systems (ABS, CRM), extracts all relevant customer data and applies fuzzy matching for deduplication, accounting for typos and inconsistencies.
Checking in external services

Automatically generates and sends requests to external sources, consolidates account data, caches responses and compiles a unified credit history from reports across multiple credit institutions.
Business Rules Check (BRS)

Assigns risk groups to each application using configurable risk matrices and determines decision parameters based on the resulting risk assessment.
Scoring

Combines credit reports from multiple bureaus into a single consolidated credit history per applicant.
Decision Making

Calculates risk groups using configurable risk matrices, defines loan terms and conditions, and delivers either an automated decision or structured recommendations for underwriters.
Analytical Reporting

validates application fields, tracks progress, logs calls and responses, and generates analytical reports.

Vendor

Megaladata

Deployment time: Modular architecture enables phased implementation, individual modules can be deployed and activated independently

Megaladata is a low-code data analytics platform company headquartered in Yerevan, Armenia. The company develops tools for businesses and data professionals who need speed, flexibility and efficiency in working with data. Megaladata Decision Maker is one of their specialised solutions built on top of the Megaladata core platform, targeting financial services, lending, and risk management use cases.

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