Accelerate Regulatory Compliance
Arcadia Data accelerates regulatory compliance because it provides subject matter experts with the accessibility and transparency required to proactively mitigate risk, not just react to it.
Three core concepts must be considered in to satisfy the heightened expectations of regulators, investors, and customers in the financial services industry:
- Granularity is first and foremost: Data granularity must be maintained so that you can demonstrate modelability and ensure fidelity of the data, two main concerns of regulators.
- All data must be leveraged: The financial landscape is represented through all types of data: structured and unstructured, real time and historical, traditional and alternative. A robust and defensible regulatory program must leverage all data types, big or small.
- Subject matter experts drive solutions: Analysts in compliance, risk, finance, operations, and the front office understand the nuances of how to derive meaning from data. Cross functional collaboration is key to understanding the full story of any transaction.
See below for examples of how BI and visual analytics that is native to modern big data environments respond to the key directives above. Arcadia Data accelerates regulatory compliance because it provides subject matter experts with accessibility and transparency required to proactively mitigate risk, not just react to it. It is your front end to regulatory compliance.
See how native visual analytics is applied to specific regulatory challenges such as CLAR, CAT, FRTB, and RENTD.
Resources
How Does Liquidity Coverage Ratio (LCR) Affect Data Collection?
Visual Analytics for Fundamental Review of the Trading Book
Consolidated Audit Trail: Outside Looking In
RegTech: Leveraging Alternative Data for Compliance
A Front End for Data-Driven Regulatory Compliance
Connect the Dots: Post-Trade Reporting as Part of Title VII of the Dodd-Frank Wall Street Reform Act
Evaluate Comprehensive Capital Analysis and Review (CCAR) and the Dodd-Frank Act Stress Test (DFAST) in Granular Detail
Facilitating a Responsive Basel III Liquidity Coverage Ratio (LCR)
Adapt & Respond to the Volcker Rule’s RENTD
Addressing the Challenges of the Comprehensive Liquidity Assessment Review (CLAR) and Liquidity Monitoring Reports with Native Visual Analytics

Cross Organizational Model Validation
Evaluate how entities perform against a series of adverse market scenarios. You can imagine in the background, algorithms testing different ways to free up liquidity. Those changes could be reflected here. When you see a graph you like, you can package it as an app and use it as part of a management plan provided to auditors.
Data Quality - Now
You don’t have to wait for your organization's big data strategy to mature with multiple sources. Enhance your data quality initiatives by generating multi-functional visualizations from one large data source.


Dynamic Data Quality
Identify material changes in upstream data sources that affect active transactions in order to prioritize remediation efforts. Join machine learning data quality risk models with pre-trade electronic communications, trade execution, and post trade events for timely and effective trade reconstruction.
Correlation and Divergence
Visualize algorithmically-generated data with billions of rows of transaction data to prove that it is both sufficient in volume and adequate in quality. Arcadia Data visual analytics can help evaluate the performance of multiple entities against a series of valuation models. Plan desk structure and organizational changes through an enterprise-wide lens while proving that models are based on real market data.

Native Visual Analytics Applied to Specific Regulatory Challenges
The table below provides examples of specific regulatory challenges and how the capabilities of native visual analytics enable holistic solutions.
Regulation | ||||||||||||
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Comprehensive Liquidity Assessment and Review (CLAR) and Liquidity Monitoring Reports |
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Basel III Liquidity Coverage Ratio (LCR) and New Stable Funding Ratio (NSFR) |
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