MNC Data Solutions
MNC DATA SOLUTIONS

See what happened
around the activity.

THE ALERT IS ONLY PART OF THE STORY.

15+ years in trade surveillanceBuilt by the team behind MNC SolutionsTechnology-agnostic implementation

MNC Data Solutions connects economic outcomes, trading behavior, external events, entity relationships, and data assurance to help institutions understand the broader intelligence surrounding surveillance activity.

THE PROBLEM

Alerts do not always tell the whole story.

A surveillance alert may identify an event. Understanding that event can require context from the entity’s history, recurring behavior, economic outcomes, market movement, public events, related activity, and the quality of the underlying data. Often the most important question is the simplest: who consistently benefits — and what surrounds that profitability?

MNC Data Solutions connects that context.

THE FIVE PILLARS

Five pillars. One connected picture.

MNC Data Solutions brings multiple analytical perspectives together to help institutions understand the broader context surrounding activity.

P&L ASSESSMENT ENGINE

Understand the economic result.

Economic outcomes can provide important analytical context when viewed alongside trading behavior, surveillance activity, historical patterns, and related evidence.

Profitability alone is not a conclusion about conduct.

EXPLORE THE P&L ASSESSMENT ENGINE →
ENTITY PROFILE
360° view of the entity’s P&L
ILLUSTRATIVE
ENTITY PERFORMANCEALERT-ASSOCIATED OUTCOMESOUTCOME TRENDSPERSISTENT BENEFICIARYLOSS-BEARER EXPOSURE
TRADING BEHAVIOR SIGNATURE

Every entity has a signature. Departures matter.

Longitudinal behavioral analysis — frequency, concentration, participation, and exposure — measured against the entity’s own history, including cross-product positioning across equities and their derivatives. AI models learn each entity’s signature and flag departures and emerging trends.

A departure is context, not a conclusion.

EXPLORE TRADING BEHAVIOR SIGNATURE →
BEHAVIORAL SIGNATURE
Cross-product trade sequence vs. baseline
ILLUSTRATIVE
EQUITY LEG · XYZOPTION LEG ·XYZ 50 CALLPAIRED EXPOSURE»»↑109:31:00BUY 50K shares$48.20↓209:31:18SELL 500 calls$2.40↓310:12:00SELL 50K shares$51.10↑410:13:01BUY TO CLOSE 500$1.05OPEN SPREAD · 18 SEC BETWEEN LEGSCLOSE SPREAD · 61 SEC BETWEEN LEGS09:3009:4009:5010:0010:1010:15‹›ENTITY BASELINE · TYPICAL LEG INTERVAL 6–12 MIN
4.2×
typical notional
18 sec
entry interval
Cross-product
concentration
!DEPARTURE DETECTED · tightly paired legs differ from historical execution pattern
Sequence is illustrative. A departure is context, not a conclusion.↑ BUY↓ SELLBASELINEDEPARTURE
INFLUENCE & EVENT IMPACT

Connect the event to the activity.

Contextual analysis built on temporal association — what occurred before, after, and alongside the activity. Never causation.

STEP 01
DETECT THE SWING

MNC leverages AI to identify unusual increases in volume or liquidity, and substantial price swings — up or down — against prevailing market conditions.

→
STEP 02
FIND WHO PROFITED

Concentrated entities that profited by buying or selling just before — or shortly after — the swing are identified and profiled.

→
STEP 03
SWEEP PUBLIC SOURCES

An AI-driven sweep of public sources — news, social media posts, and prediction markets — identifies any public event or price-sensitive information around the window.

EXPLORE INFLUENCE & EVENT IMPACT →
TRADING NETWORK ANALYSIS

See the connections isolated analysis can miss.

AI-assisted connection analysis surfaces entity relationships, recurring overlap, common securities, shared markets, connected activity, and outcome networks — across markets. Select a node to isolate its analytical relationships.

EXPLORE TRADING NETWORK ANALYSIS →
DATA ASSURANCE

Intelligence is only as reliable as the data behind it.

Complete reconciliation of your internal OMS and trading data, matched against what your surveillance system actually processed — so all trading activity is captured, and the gaps are identified before potential manipulation can slip through unmonitored.

ASSURANCE SNAPSHOT
96.1%
Surveillance-ready coverage
12.4M
expected
11.8M
ready
482K
exceptions
Illustrative metrics
EXPECTED
12.4M records
What should have arrived
↓
DELIVERED
12.1M records
What actually arrived
↓
NORMALIZED
11.9M records
What was structured
↓
SURVEILLANCE-READY
11.8M records
What can be analyzed
302K missing or late
Entity gaps · Market gaps · Trading-day gaps
180K rejected
Schema failures · Duplicates · Identifier breaks
100K withheld
Lifecycle breaks · Eligibility rules · Unresolved lineage
Entity coverageDesk coverageMarket coverageTrading-day coverage
CompletenessTimelinessMessage reconciliation
Schema conformityIdentifier mappingLifecycle integrity
Data exceptionsLineageEligibility
EXPLORE DATA ASSURANCE →
ValidatedExceptionData flow
Illustrative reconciliation metrics shown for demonstration.
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