For Stockbrokers

by | Jan 10, 2023

Stockbrokers are increasingly reliant on the quality of their data, given its critical impact on the experience of their business generators and the level of service they can deliver to clients.

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Poor data is common due to the lack of validation on legacy systems, producing problems that can manifest in multiple areas:

Client reporting

Client Reporting

misleading, inaccurate or out of date policy/plan data being reported
Dealing errors

Dealing Errors

from incorrect security set up

Incorrect commission calculations

Incorrect commission calculations

due to invalid scales linked to the client, manager & counterparties

CASS breaches

CASS Breaches

such as miscalculated fees being charged or erroneous regulatory submissions

Inaccurate MI

Inaccurate MI

used for critical and strategic decision making

The consequences of bad data can be significant:

  • Damaged client relationships caused by inaccurate communications
  • Lost reputation if the above happens at any scale
  • Increased staff costs to monitor and resolve data-related issues
  • Reduced productivity from continuously allocating valuable resource to address data problems
  • Regulatory fines if customer data is misrepresented or regulatory reporting is inaccurate
  • Strategic decisions based on poor data can be damaging to both clients and the firm
  • Cost of compliance will grow if data issues are ignored

Stockbrokers need to keep a keen eye on how data is acquired, processed and reported to ensure they can run an efficient operation, avoid falling foul of the regulator and maintain customer trust, especially given the widespread use of ageing systems in the industry.

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To find out how to avoid these pitfalls

DCI Data Analyst Screenshot

Insights for Stockbrokers

DCI The hidden cost of bad data

The hidden cost of bad data

Regulatory Imperative

Regulatory imperative

Bad data pain points

Pain points from bad data