Use of advanced analytics to optimize risk-based pricing decisions

What it is about

Marcelo Fernandes, of Advanced Analytics and Optimization LAC at FICO, explained at the Second Annual Risk Conference (September 27, 2024) how risk-based price optimization makes it possible to set rates that balance volume, margin and risk. It is a presentation by a technology vendor.

The 34 slides present the situation of the Dominican banking system (the six largest banks hold 84% of assets and the evolution of lending and deposit rates), the challenges of pricing in banking, what risk-based price optimization is, who should lead the process, the methodology (volume, response, prepayment and profitability models), the financial benefits and case studies at banks in Peru, the Czech Republic, the United Kingdom and the Middle East.

Objectives

• Explain what risk-based price optimization is and how it connects with the bank's strategy.
• Describe the methodology: data, predictive models, objective function, constraints and optimization algorithm.
• Show the financial benefits and the case studies reported by the vendor.

Key takeaways

1. Setting prices requires balancing customer preference, competition and regulation, the financial impact on portfolio profitability and the operationalization of the strategy.
2. Volume and margin optimization is fundamental: price sensitivity is a key factor for response and acceptance models, and the optimal rate is the one that maximizes expected revenue.
3. Typical models include estimated proposal volume, response (price elasticity), prepayment and profitability or loss prediction.
4. According to the presentation, the vendor's customers with price optimization projects achieved average profitability increases of between 7% and 15% over their previous strategy.
5. The case studies (Peru's BCP, Česká spořitelna, a UK bank and a Middle East bank) are results reported by the vendor and should be read in that context.