Early warning system reveals financial distress 5 months earlier than normal

BSG worked with a South African bank on a proof-of-concept to enable the bank to predict financial distress using data analytics, resulting in a prioritised company watch list of high risk customers. Previously the bank had taken 6 months to highlight organisations in financial distress, the BSG designed system drops that down to 1 month.

  • Reduce unexpected losses across credit products in corporate and investment banking (CIB)
  • Automate manual process of identifying high risk clients
  • Transition from reactive to proactive risk management
  • Save the bank money lost as a result of customers defaulting on payments
  • Develop a tool to identify financial distress earlier and more accurately than existing credit models
  • Translate the tool’s outcomes into business terms stakeholders can understand
  • Improve the identification of risk by four to five months
  • Proactive risk management to enable the bank to assist clients by restructuring their debt
  • Time and money savings through proactive suggestions prior to a company going into distress

In a first for the bank, BSG consolidated internal and external data and fed this into a predictive analytics model to determine the probability of financial distress and learn more about their clients.

Do you want to save millions?

Through data modeling, we developed an early warning system that enabled our client to identify customers who were at risk of defaulting on their loans. Through this early warning system we saved our client millions of Rands. If you want to use the data you have to potentially save your company millions of Rands, get in touch with our data analytics team.

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