Drona’s Decision Operating System :: AIML Based Risk & Compliance Platform

In today’s fast-paced world of financial services, risk management and regulatory compliance are no longer just obligations — they are strategic priorities. The growth of digital payments, realtime lending, and online insurance has created both opportunity and risk. Criminals are evolving just as quickly, exploiting gaps through money mules, synthetic identities, and money laundering layering techniques.

Traditional systems often rely on rigid rules, slow investigations, and siloed databases. This approach struggles against modern fraud. What’s needed is a system that combines an array of data sources (Internal, External & Alternate) while leveraging AI, ML and Rules that support real-time decisioning and automation into one platform.

This is the vision behind Drona Pay’s Decision Operating System (DOS) — a layered, composable architecture designed to help financial institutions detect fraud earlier, ensure compliance faster, and deliver customer trust at scale.

The Three Layers of DOS

1. Data Layer — Unified, Scalable & Composable

Every intelligent decision starts with data. The Data Layer ingests structured and unstructured information — from payment transactions,  KYC data, AML/CFT data sources, health or motor claims, device fingerprints, and transaction logs — whether through realtime message streams, Rest APIs or batch uploads.

This eliminates silos and creates a single view of the customer across products and channels. With this foundation, institutions can better detect mule accounts, spot anomalies in claims, identify money laundering, prevent account take over and comply with regulatory reporting.

Built for scalability, the Data Layer adapts to on-premises, cloud, or hybrid deployments, ensuring Risk & Compliance teams can improve decision making in line with business needs.

2. Analytics Layer — From Raw Data to Financial AI

The Analytics Layer transforms raw inputs into actionable intelligence. It empowers risk teams to:

• Build behavioral biometrics profiles (typing patterns, navigation, device use) to flag account takeovers.

• Compare hospital / provider billing patterns, analyze historical claims to identify fraud, waste, and abuse.

• Use anomaly detection to uncover suspicious transaction patterns that can lead to fraud and money mule detection.

Here is where AI & ML comes to life. Teams can train, test, and deploy machine learning fraud detection models quickly — reducing false positives while catching emerging threats.

This layer offers the ability to construct features or red flag indicators which form the base to track money mule activity, bot farms and layering in money laundering, all of which are top concerns for regulators worldwide.

3. Decision Layer — The Nerve Center of Action

The Decision Layer operationalizes intelligence. It combines:

• Low-code/no-code rule builder for known fraud typologies.

• Machine Learning models for complex, evolving fraud.

• AI agents that evaluate alerts & investigate suspicious claims.

Decisions are executed instantly, triggering automated workflows such as blocking a card or account, escalating an AML case or sending a health claim for review by Doctors. This creates faster resolutions, fewer losses, and improved trust.

Real World Use Cases

• Realtime Transaction Monitoring: Identify card fraud, prevent chargebacks, detect mule accounts, and flag anomalies instantly.

• Behavioral Biometrics for Account Takeover Prevention: Identify imposters through unique digital fingerprints before fraud occurs.

• Fraud Waste and Abuse Detection in Claims (FWA): Profile providers, compare claims patterns, and route suspicious claims for investigation.

• AI Powered Underwriting: Leverage AI Agents to analyze unstructured data to validate risks and underwrite policies.

• AML Compliance: Detects suspicious transaction patterns, identifies money mule networks, and uncover the layering patterns in money laundering.

Why Drona’s DOS Wins

Unlike fragmented tools, Decision Operating System unifies data, analytics, and decision-making in one platform. The benefits:

• Detect money mules, mule accounts, and synthetic identities earlier

• Automate compliance with AML transaction monitoring and regulatory reporting

• Reduce false positives in fraud detection with machine learning

• Improve operational efficiency through AI-driven workflows

• Stay ahead of evolving fraud with composable, real-time decisioning

Conclusion

Drona Pay DOS is the next-generation platform that enables Risk & Compliance teams in Banks, Insurers, Payment Processors and Fintechs to leverage AIML. By combining a unified data layer, advanced analytics, and real-time decisioning, it empowers financial institutions to detect fraud faster, prevent losses, and build stronger trust with their customers.

From blocking money mules to uncovering money laundering to reducing waste & abuse in Claims, Drona Pay helps risk and compliance teams act with speed, precision, and confidence.