Skip to content

p_05 · Capital Markets

Stock Brokerage Analytics

Segment-wise trade and revenue analytics to find high potential HNI clients, with active and passive client tracking that helped RMs prioritise advisory effort.

  • SQL
  • Power BI
  • DAX

01 / Problem

Sales teams and relationship managers needed to know which clients had the most potential and which accounts had gone quiet.

02 / Data

  • Client trade and brokerage data: gross, net and partner brokerage, ARPU, traded and total clients, daily incremental brokerage.
  • Split by segment (equity, derivative, commodity), team leader, direct or sub-broker and branch.

03 / Approach

  • SQL to prepare trade and revenue data, a Power BI model with DAX measures.
  • Segment-wise trade and revenue views to surface high potential HNI clients.
  • Active and passive client behaviour tracking.
  • Pages for brokerage, KYC, group, team, FY trend, 30 day trend and mutual funds.

  1. stage_1

    SQL

    Trade and revenue data

  2. stage_2

    Power BI model

    DAX measures

  3. stage_3

    Report

    Segments · activity

04 / Live dashboard

preview · power bi

Open in Power BI(opens in a new tab)
Stock brokerage analytics Power BI report with brokerage KPIs, client counts and a segment split donut
Open full dashboard(opens in a new tab)

05 / Business impact

  • Sales teams could identify high potential HNI clients.
  • Relationship managers prioritised advisory effort using active and passive behaviour tracking.

06 / Tools

  • SQL
  • Power BI
  • DAX
Next projectHR Management Analytics