Automated Financial and Legal Documents Analysis for Investment Managers
Financial Ops Automation
Financial Ops Automation is an AI-based enterprise application software that is capable of automating the digitization, comprehensive analysis, and information extraction from a large array of financial and legal documents in various formats like scanned paper, PDF machine readable, XBRL/XML, JSON, Word, PPT, Excel and CSV.

Use Cases
Reconcile weekly, monthly, and yearly NAV estimates
Reconcile fee calculation and calculation of fee waterfall
Verify and reconcile price calculations
Reconcile contract notes and trade confirmations
Reconcile treasury transactions
Reconcile investor fee and liquidity terms
Reconcile rate of return emails
Reconcile trade and cash positions
Automated online reporting
Reconcile balance sheets, income statements, cash-flow statements, changes in equity
OTC confirmation and reconciliation
Collatio Serves
Hedge funds
Funds of funds
Managed accounts
Family offices
Real estate
investment trusts
Mutual fund
companies
Private equity
and venture
capital
Corporations
Third party
administrators
and custodians

Collatio®
AI-based Financial Ops Automation to for Efficient Decision Making
Financial Ops Automation by Scry Analytics delivers tremendous gains in productivity and cost reduction, while guaranteeing unprecedented levels of accuracy at scale. It is powered by extensive automation that is implemented at each stage of process.
More DetailCollatio has been built using
the following technologies
-
Bayesian
networks -
Reinforcement
learning -
Generic rule-
based machine
learning -
Heuristic
algorithms -
Reverse
engineering
-
Data mining
-
Big data
integration -
Big data
analytics
Key Differentiators &
Business Benefits
-
User Interface and APIs
Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ existing workflow
-
Knowledge Graphs
30+ probabilistic spatial and temporal graph algorithms to determine links and connected entities.
-
Accuracy
90%+ accuracy achieved with pre-trained algorithms and domain ontology
-
Time and Cost
Up to 85% reduction in time and cost with automated extraction and reconciliation of attributes.
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