The Challenge
A growing organization has inherent challenges in reacting to business changes, evolving risks and new opportunities while continuing to stay aligned with its business vision. An increase in trading activity poses additional risks that traders face, putting the organization at risk. Capturing entire day’s trades, filtering and comparing them to identify wash trades, gets increasingly difficult. The result is an eventual lapse. Seeing that they’re manpower-intensive tasks, the reports cannot be available before the next day’s trading starts.
There needs to be a solution that can:
- Consolidate data from respective sources efficiently
- Possess configurable parameters for matching wash trades
- Available before the start of the next business day
- Possibility of identifying exact, tolerance and potential wash trades
- Report violations in a timely fashion with a suitable notification mechanism
- Reduce operational risk and improve resource utilization
The Solution
The desired approach was to provide a solution that can handle wash trades detection along with other common compliance rules. Ideally, it boiled down to EPIC due to its ability to easily connect to upstream and downstream data sources and model their business processes in the platform. EPIC automatically fetches daily trades data, applies the rule, tags wash trades and generates the report before the start of the business day.
With a defined mechanism in place, the firm was now able to tackle multiple business challenges:
- Wash trades detection: Detects wash trades in various categories like Exact Match, Tolerance-based and potential wash trades. Tolerance-based are wash trades with variations defined on the price type of commodities
- Flexible tolerance definitions: Tolerance limits are maintained in a user-defined table that can be changed as per business needs
- Consistent rules: The same set of rules are applied to detect all wash trades on every run. This ensures consistent detection of wash trades on daily trades
- Batch-driven: Pulling data from external sources, filtering it and applying rules to detect wash trades happens with a single click of a button. This can also be automated to have the report executed during off-business hours
- Report before the start of the business day: Users get the report for the previous day via emails delivered, much earlier than the start of the business day
Outcomes & Benefits
- Three types of wash trades are detected instead of one
- Data fetching, processing and report output, all done in a single click
- Anytime report generation
- Users become more self-sufficient
- Reliable, system- generated reports
- Timely report availability before the start of the business day
