Analytical Modelling

In addition to its Minotaur™ product portfolio, Neural Technologies carries out bespoke projects to develop predictive analytical models.  Analytical models provide valuable decision-support to assist organisations in planning their business strategies.

The models are built using an organisation's own data and as such are tailored to their specific business requirements.  Here are just some of their applications:

Marketing

Helping to understand prospective customers' motivations and focus marketing efforts by identifying only the relevant people to receive a specific offer or product, resulting in:

• Maximum marketing response
• Reduced mailing and acquisition costs
• Increased customer satisfaction

Cross Sell/Up Sell

Reducing acquisition costs by capitalizing on sales opportunities in the current customer portfolio, using profiling to identify product and services affinity to:

• Explore linkages between the products/services customers presently buy and the ones they might be persuaded to buy
• Increase customer satisfaction by only offering products for which they qualify
• Increase customer retention by providing customers with more than one product or service

Customer Retention

Predicting the loss of valuable customers well in advance to enable the formulation of effective retention strategies, such as:

• Special offers
• Discounts
• Enhanced credit limits
• Product/service relevant to the customer, such as a new/different credit card or tariff plan

Customer Lifetime Value

Analysing the customer base as a whole to identify key customer segments and establish a framework for different treatments and interactions, e.g. cross-sell new product offerings:

• Obtain a picture of the percentage of customers most critical to the revenue stream to ensure they are retained
• Monitor which high-value customers are spending less in a given month and which low-value customers have started spending more to plan future customer retention and cross-selling strategies
• Use the information as justification for various customer acquisition/retention strategies and spending

Fraud/Credit Risk

Providing a consistent and objective assessment of credit risk (bad debt) or fraud:

• At the point of application to assist analysts/underwriters in making decisions about new customers rapidly
• At early stage of customer life (customer age less than 1, 2 or 3 months) using behavioural modelling
• For existing customers (behavioural modelling using payment data, usage/transactional data etc.
• This helps to focus analyst/underwriter expertise on marginal cases

Credit Limit Management

Reduce risk of default, whilst at the same time improve profits and customer satisfaction by establishing appropriate credit limits:

• Determine an initial credit limit based on application score
• Manage the credit limit and credit class dynamically using daily/monthly behavioural scores

Collections

Developing a focused collection strategy with the aid of behavioural scoring to proactively use limited resources to:

• Identify the 'auto-resolution' accounts and improve customer relations
• Identify the 'write-off' accounts at an early stage to apply appropriate collection strategies
• Identify the outstanding accounts where minimum payment is likely to be made and hence can be followed up for more
• Prioritize accounts to ensure maximum collections and optimized use of resources
• Identify the most suitable strategy (or prioritize the strategies) to recover the debt, e.g. initial letters, telephone calls, reminders, outsourcing to collection agencies etc.

To find out more .