Regulations and Compliance in Finance and Beyond
The nexus of regulation and data
Regulatory compliance obligations place enormous demand on the financial industry’s use of its data. Information requests can span multiple operating units and follow customer relationships touching data in multiple business lines and jurisdictions. Complete and rapid response to regulators requires mapping relationships in data owned by different units or groups across the enterprise and across jurisdictions.
The myth of easy answers
For large financial enterprises, even the simplest question from regulators, law enforcement, or an internal controls check can be hard and expensive to answer. Short timeframes and an influx of questions at once compound the problem and add exponential expense.
An inquiry might start simply. “Does the enterprise do business with this party?” To find the answer definitions have to be clear: “Does the ‘party’ mean the person or the company?” Definitions change by country and culture, and so does the stored data. An answer requires some definitions as simple as an identity card number and others as complex as family and business relationships—relationships that are layered and often in flux.
Consider questions that cut across different units and departments. “How much money is at risk if a particular customer has financial trouble?” This isn’t easy to answer. Different business units see the same customer as a borrower (revolving line of credit), an investor (participant in an investment fund with future commitments), an investment (issuer of bonds held as an investment), or a guarantor (trade finance) of other debt. Assembling the data for a single customer requires detailed data from different businesses. This is more difficult when business units have been merged-in, or accounting rules are different and currencies must be handled(China, GAAP, IFRS). In each case the ‘metadata’ (understanding what the data held by a business unit means) can be nightmarishly complicated in itself.
Quite simply, traditional tools to search computer databases aren’t designed or equipped to query based on these relationships.
Conexus CQL enables speed, certainty, and cost-effectiveness
CQL empowers staff to look at data in new ways, with unprecedented power and efficiency, dynamically constructing new structures on top of existing databases. CQL makes it easy to search and answer questions based on these newly mapped relationships. Comply with confidence, even in the most complex conditions.
Conexus CQL ensures that answers are responsive (timely), complete (all the data to be found), and authoritative (statement of truths). By providing traceability and clarity to data transformations and collection (provenance) Conexus CQL confirms that decision-makers can rely on its clear answers. Data is presented in context (a number needs to have a currency attached, for instance), with specificity (banking days versus calendar days), and linked together in a clear way (documenting the relationship). Further specifics (such as translating local market calendars, in Japan for example, to global calendars) can be maintained so that the implicit relationships in stored data are made explicit when the data is used later.
Conexus CQL helps designers and developers see connections across data pools, enabling faster and less expensive answers. Its understanding of relationships, access patterns for related data, and management of constraints promotes rapid and trustworthy exploitation of vast, siloed databases in conjunction with one another. Reduced rework, testing, and evaluation saves hard dollars and reduces risk:
- CQL’s capability to define constraints reduces data failures and software testing.
- Tight specifications of interfaces between applications reduces operational costs and improves implementation quality.
- Data verification using automated methods provides confidence in results while reducing costs.
Conexus CQL can be introduced rapidly and effectively, using our external resources to augment design and project teams while building their skill levels.
Conclusion
Conexus CQL brings breakthrough advances and better methods to meet regulatory demands. By shortening projects, improving time to answers, and delivering confidence, deploying Conexus CQL brings efficiency, lowers costs, and helps you get it right. However many places your data lives, however complex its relationships, Conexus CQL offers an easy path to answers—for regulatory compliance or other business decision-making.