Case Studies and Sample MVPs

Liquidity Management

Problem Statement Liquidity management is a key challenge for banks, especially in times of market volatility and uncertainty. Banks need to maintain sufficient cash reserves to meet their operational needs and regulatory requirements, while also investing excess cash to generate returns. However, predicting daily cash inflows and outflows across different business units, currencies, and geographies

Wealth Management – Attrition, Segmentation

Problem A challenge in growing the wealth management business, which offered high margins and customer loyalty, was faced by the bank. The bank had a small client base in this segment, with low growth rate and high competition from other financial institutions. The bank needed to find better ways of identifying and attracting profitable customers

Deposit Attrition, Business Banking

Problem The bank faced a serious challenge of deposit attrition, as more and more customers switched to other financial institutions or alternative channels for their banking needs. The bank’s deposit base was shrinking annually, resulting in lower interest income, reduced cross-selling opportunities, and higher operational costs. If this trend continued, the bank would lose its

Predictive lending, Attrition Forecasting

Problem One of the major challenges faced by banks in the competitive lending market is to retain their existing borrowers, who may be tempted to switch to other lenders that offer lower interest rates or better terms. This can result in a loss of revenue and market share for the bank, as well as a

Commercial Card Analytics

Problem A national bank faced two main challenges in its commercial card business: fraud risk and customer engagement. Fraud risk refers to the potential losses from unauthorized or fraudulent use of credit cards, which can damage the bank’s reputation and profitability. Customer engagement refers to the degree of loyalty and satisfaction that customers have with

Predictive lending, cross-sell/up-sell:

Problem: A large national bank wanted to increase its lending revenue by offering loans and mortgages to existing deposit clients who have a high propensity to borrow. However, the bank did not have a reliable way of identifying which clients are most likely to need a loan or mortgage in the near future, and how