Retail Banking: Case Studies

Segmentation Analysis

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Problem: A top-20 retail bank was facing a $100mm shortfall from its goal of double-digit earnings growth.

Solution: Novantas worked with a team of core executives to analyze customer segments, which led to a revised distinctive value proposition. From there we identified and prioritized a set of tactical initiatives.

Result: The result was a plan to generate an incremental $150mm of earnings within three years.

Pricing Optimization

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Problem: A top-10 bank was experiencing slow deposit growth and tightening spreads due to intense deposit pricing competition. It was unable to aggressively price liquid savings because it had a book of low-rate MMDA that it could not reprice.

Solution: Novantas used a customer elasticity analysis to develop a pricing strategy that identified opportunities to reduce rates on inelastic products, tiers and regions while increasing rates on elastic portions of the portfolio. In addition, we implemented a set of price optimization software that allowed the bank to manage prices on an ongoing basis.

Result: The bank beat the plan in both volume growth and margins, generating $55mm in increased annual earnings.

Risk-based Pricing

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Problem: A top-10 bank was facing slowing growth in home equity and intense competition for credit-worthy borrowers. The bank had applied a ‘one-size-fits-all’ approach to pricing home equity loans and lines.

Solution: Novantas developed a risk-adjusted account-level profitability database to identify opportunities for risk-based pricing. The result was a revised pricing matrix with over 1,000 ‘cells.᾿ We analyzed price elasticities for each cell and identified opportunities to ‘harvest᾿ or ‘grow.᾿

Result: A net increase in spreads of 11 bp, with no diminishment in volume.

Local Market Based Goal Setting

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Problem: A 1,500+ branch bank was not meeting productivity goals. We identified that one of the drivers was inappropriate goals not tailored by the local market opportunity.

Solution: Using Novantas᾿ Branchscape database, we were able to tailor goals for every branch in the network. The outcome was higher goals for a set of branches (where money was being left ‘on the table᾿ and incentives were overpaid) and lower goals where opportunities were less robust.

Result: The result was overall branch sales productivity improved by 2% in the first year. In addition, we identified markets where a substantial cause of under-performance was a sub-scale branch network. We developed a de novo plan, based on an understanding of ‘micro-markets᾿ within each MSA and we identified opportunities to ‘self-fund᾿ de novos through closures, relocations and ‘two-for-ones.᾿