Abstract

To meet their growing financial services needs, today's banking customers are holding a greater number of distinct products in their portfolios. Increasingly, customers are choosing "best fit" products across multiple institutions, in an effort to obtain the lowest rates. To maximize customer "wallet share", relationship managers propose bundles of products, usually with rate and/or fee concessions to make the entire package more attractive. Individualizing a "best fit" package for each customer is known as "One on One Customization".

Drivers

Customer portfolio fragmentation across Institutions is driving banks to offer custom pricing for product packages to obtain and/or retain customer wallet share. Core banking systems do not easily support package pricing across product applications, so RM's must determine if/when concessions, discounts and waivers are applicable to an individual customer. It often difficult for a customer to visualize the benefits of package level pricing concessions verses individual product pricing (i.e. Is it better to have a particular transaction fee waived, or to have a slightly higher interest rate?). Finally, it can be very difficult for an Institution to establish discretionary discounting boundaries for RM's, and even more difficult to determine where unmerited discounting is contributing to "revenue leakage".

Solution

Zafin Lab's One on One Customization Solution includes a number of capabilities for delivering individualized package pricing, including:

• Standard Product Packages are predefined by Product Managers anticipating package requirements for individuals in target segments. Package level concessions and customer eligibility requirements are optimized and automated to easily select the "best fit" package for each customer.
• Individualized Product Packages can be created on the fly by RM's by combining products into a new package, or modifying existing packages that are a "close fit". Role based limits allow for a measurable degree of discretionary discounting to be conducted based on individualized requirements.
• Customer Package Pricing Simulations allow customers to visualize the expected overall charges for the package, as compared to a non-packaged set of products, including all interest, flat, and transactional fees. Simulations can use actual customer historical (transaction) data or can generate/simulate transactions based upon configurable specifications.
• Mass Customized Product Packages can be created, when an individualized customer package is deemed to be highly re-usable. When RM's see a trend in package customization, this custom package can be converted into a standard package offering with specific customer eligibility criteria.
• Revenue Leakage Analysis and Controls allow the institution to track revenue leakage by package, product, program, market segment, geography, branch, or by RM. Excessive or undo discounting patterns can be identified and mitigated through discretionary controls, stricter eligibility requirements, or through discount "budgets" for branches and/or RM's.

The miRevenue interactive sales dialogue experience follows a six step process:

1. Customer Identification - The RM obtains customer background information for potential product/package eligibility.
2. Customer Requirements - The RM captures current and new customer product requirements, including existing products with other Institutions as potential candidates for consolidation.
3. Package Selection/Creation - The RM requests miRevenue to find the best fit package(s) based upon customer requirements, eligibility, financial institution product & pricing strategies, product compatibility, customer relationship value etc... Individual products may be added to a package if/when required.
4. Pricing Simulation - The RM projects the customers' funds inflows/outflows for the New Offering through simulations, enabling them to make an informed comparison and decision.
5. Customization - The RM can tailor the pricing for the customer within the bounds of their discretionary permissions and controls.
6. Offer - The RM generates a custom legal offer for the customer to sign up.

Benefits

Using miRevenue to support One on One Customizations has a number of advantages including:

• Institutions can provide any number of product package pricing variations without incremental modifications to existing core banking applications
• Enforced eligibility requirements allows packages to be targeted at specific market segments
• RM's automatically find "best fit" packages to meet individual customer needs and preferences
• RM's can help customer visualize actual customer savings advantages for proposed packages
• RM's can further customize package pricing to meet customer expectations
• Institutions can track and mitigate undo revenue leakage from discretionary RM discounting

Conclusion

The One to One customization solution from Zafin Labs enables a Financial Service Provider to work with customers to identify "best fit" offerings through an interactive sales dialogue process, then to customize the offering to arrive at price points which appease both the parties. The result is a Win-Win proposition for all. Customers are satisfied with individualized offerings which fits their needs while Financial Institutions increase their wallet share through product consolidation , and increase customer retention through a differentiated experience.

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