Oxxford UCIS - Banking / Financial Module

Overview

Oxxford UCIS's Banking / Financial Module provides financial entities, and others, a consistent approach to analyzing and identifying marketing opportunities across customers and prospects. Specifically, the data enables to identify opportunities for cross-selling products across multiple silos of customer data, as well as to identify specific opportunities to market to prospects.

The financial module contains both alpha scoring for propensity attributes and numeric representation of financial estimates for predictive attributes. The information in the module is easily appended to Dun & Bradstreet's marketing data base using the Dun & Bradstreet D‑U‑N‑S^® Number so clients can supplement all firmographic data concerning growth, banking, risk, and more.

Use Cases

Oxxford UCIS's Banking / Financial Module helps users to qualify and quantify their existing customers and prospect markets. Current customers within the financial arena use data for cross-selling financial products (loans, sweep accounts, credit cards, mortgages, CDs, and more). Both financial and corporate clients utilize the data for analyzing availability or lack of availability of estimated cash on hand at a business, as well as the ability of businesses to make investment in both capital and financial products.

The Oxxford UCIS Banking / Financial Module helps users:

• Examine the concentration ratios of deposits and loan balances within the customer database to establish opportunities for profitable change.
• Merge disparate “silos” of customer data to examine customers' needs in a more detailed manner for efficiency and marketing processes.
• Identify product profitability based on direct margin spreads to assess profitability of relationships, industries, and markets served by the bank.
• Identify share of wallet within each product group to assess the potential for incremental volume.
• Identify personal relationships with business owners that bank with competitors.
• Identify the average length of time that businesses maintain a relationship with a bank to determine the correlation between account age and profitability.
• Identify the opportunity for sales of specific products by account, based either on Product Usage Propensity (PUP) scores or on custom models developed for the financial entity.
• Identify industry concentrations and wallet shares by industry to determine the relative risk and product growth opportunities from industry specialization.
• Identify sales’ size distribution within the customer base in order to prioritize the matching results. Typically, larger customers are marketed to on a personal basis, while smaller customers that are marketed to through branch contacts, direct mail, e-commerce, or phone channels.
• Identify product complexity, including the concentration for sales of individual products and the impact on costs and profits.
• Identify share of served market(s) to identify industry void, gaps, and concentration in surrounding branch markets.
• Identify competitive share of each branch and its served market area to determine resource allocations for branch concentration.
• Identify prospects with served market areas.