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How Predictive Scoring Is Being Used To Increase Business ROI

May 25, 2017 at 2:16 PM

As a Marketer or Customer Engagement professional, imagine the cost-savings if you knew who in your database or lead list were likely to be the most profitable customers or most likely to respond? Would you bother mailing a list of a million contacts if you knew that only 100,000 of those contacts were worth targeting and very likely to respond?

Innovation is not necessarily the invention of something new, but be the result of finding a new use for an existing product, service, methodology or practice. Take the use of predictive scoring in Marketing. Scoring is no longer only about identifying credit-worthy customers, but is now being used by marketers to identify "target-worthy" leads or customers.

Predictive scoring has helped credit lenders identify people who were most likely to behave optimally as account holders, i.e. those who take out a loan and repay the minimum instalments within the given period of time period and were also based on demographics and payment behaviour. Every time you make payment on a loan or pay for a product or service in monthly instalments, you’re generating data that will be fed into a scorecard (read "What is a Scorecard?") to determine your credit score, or credit-worthiness.

Think of it this way: Predictive scoring answers the question "Who is most likely to...?" based on the application of weighting to criteria that creditors created to show the results of a certain type of behaviour.

Innovative marketers are beginning to use this same methodology to determine their contacts’ “target-worthiness,” i.e. who is most likely to respond or who is most likely to be a profitable customer? By using predictive scoring and scorecards, Marketers are now able to reduce target list sizes from millions to only thousands of “target-worthy” contacts.

By identifying variables within such data sources as demographic data, purchase behaviour and credit bureau data, predictive scoring and scorecards can be used to assign points to each variable and administer a score to the consumer that indicates how likely they are to respond to your campaign. By applying scoring to your customer or prospect base you can:

  • Increase the response rates with a more focused, targeted audience,
  • Decrease the cost of customer acquisitions by targeting only the most desirable contact profiles,
  • Reduce the weakening of your brand by decreasing the number of leads in your campaign who are unlikely to be interested in your offering, and
  • Segment offers by different needs, wants and responses to marketing messages; which lets you receive more relevant data and improve the rate at which people respond.

How Marketers are using predictive scoring in 3 industries


Principa has helped a South African insurer to take pre-emptive action on its existing customer base by using a number of behavioural characteristics that collectively anticipate human behaviour. As a result, the client is able to rely on statistical predictions to identify and rank their client base by propensity to miss payments or equally by potential to expand policy coverage. Equipped with this information, the client is now in a position to make an informed decision on growth and retention and as a result decide who should receive attention and to what degree. It all begins with a 1st generation model (or scorecard) built using historical data; fresh campaign performance data is then used to update the scorecard on an ongoing basis.


This industry uses intelligent analytic solutions to draw insights from their customers' purchasing behaviour to better understand their needs and preferences. This allows them to review their product mix (the 4 P’s: Product, Pricing, Promotions and Placement), and continually adjust to improve marketing ROI and overall profitability.

Hilton Hotel Worldwide uses geographic, demographic, psychographic (different personality traits, values, attitudes, interests, lifestyles) and benefit-oriented variables to divide its target market into segments or groups. In this way, the most attractive or suitable service and product campaigns are targeted very efficiently and effectively. With this marketing strategy, reports show that the revenue of Hilton Worldwide from 2009 to 2015 continued to increase and that they generated approximately 10.5 billion U.S. dollars in 2014 alone. 


This industry has used market segmentation to identify typical traveler behaviour and characteristics for many years. They used the normal socio-demographic variables (age, sex, education, income, marital status) to determine customers' preferences, but they found they also needed a way to reveal what motivates this behaviour. A prime example of how this works well is with Southwest Airlines. By focusing on predictive analytical marketing strategies Southwest Airlines improved their campaign ROI and now use predictive scoring to target their most desirable customer profiles. By collecting data using weighted scores, they found that not only do variables such as passengers’ educational levels affect their expectations and perceptions; but scores also differ by frequency of flight and flight purposes.

Predictive scoring can reduce your overall campaign cost by reducing your target list size to only those contacts you’ve deemed “target-worthy” and likely to respond.



Contact us to discuss how you can use predictive scoring in your marketing to reduce the cost of your Acquisition, Loyalty and Retention campaigns or click on the above banner to learn more about Genius Leads and how Artificial Intelligence and Machine Learning can improve your campaign results.

Luke Turnbull
Luke Turnbull
Luke Turnbull was the Head of Customer and Lead Analytics at Principa, until the end of 2017, after which he returned to his home country of New Zealand. He worked in the financial services industry since 1995, during which time he worked in process, strategy and operational design across a range of organisations in New Zealand, the United Kingdom and South Africa. Luke had been with Principa for 9 years and led consulting engagements with Principa’s local retail clients across the customer lifecycle, with a particular focus on customer engagement and lead generation.

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The 7 types of credit risk in SME lending

  It is common knowledge in the industry that the credit risk assessment of a consumer applying for credit is far less complex than that of a business that is applying for credit. Why is this the case? Simply put, consumers are usually very similar in their requirements and risks (homogenous) whilst businesses have far more varying risk elements (heterogenous). In this blog we will look at all the different risk elements within a business (here SME) credit application. These are: Risk of proprietors Risk of business Reason for loan Financial ratios Size of loan Risk industry Risk of region Before we delve into this list, it is worth noting that all of these factors need to be deployable as assessment tools within your originations system so it is key that you ensure your system can manage them. If you are on the look out for a loans origination system, then look no further than Principa’s AppSmart. If you are looking for a decision engine to manage your scorecards, policy rules and terms of business then take a look at our DecisionSmart business rules engine. AppSmart and DecisionSmart are part of Principa’s FinSmart Universe allowing for effective credit management across the customer life-cycle.   The different risk elements within a business credit application 1) Risk of proprietors For smaller organisations the risk of the business is inextricably linked to the financial well-being of the proprietors. How small is small? The rule of thumb is companies with up to two to three proprietors should have their proprietors assessed for risk too. This fits in with the SME segment. What data should be looked at? Generally in countries with mature credit bureaux, credit data is looked at including the score (there is normally a score cut-off) and then negative information such as the existence of judgements or defaults; these are typically used within policy rules. Those businesses with proprietors with excessive numbers of “negatives” may be disqualified from the loan application. Some credit bureaux offer a score of an individual based on the performance of all the businesses with which they are associated. This can also be useful in the credit risk assessment process. Another innovation being adopted internationally is the use of psychometrics in credit evaluation of the proprietors. To find out more about adopting credit scoring, read our blog on how to adopt credit scoring.   2) Risk of business The risk of the business should be managed through both scores and policy rules. Lenders will look at information such as the age of company, the experience of directors and the size of company etc. within a score. Alternatively, many lenders utilise the business score offered by credit bureaux. These scores are typically not as strong as consumer scores as the underlying data is limited and sometimes problematic. For example, large successful organisations may have judgements registered against their name which, unlike for consumers, is not necessarily a direct indication of the inability to service debt.   3) Reason for loan The reason for a loan is used more widely in business lending as opposed to unsecured consumer lending. Venture capital, working capital, invoice discounting and bridging finance are just some of many types of loan/facilities available and lenders need to equip themselves with the ability to manage each of these customer types whether it is within originations or collections. Prudent lenders venturing into the SME space for the first time often focus on one or two of these loan types and then expand later – as the operational implication for each type of loan is complex.   4) Financial ratios Financial ratios are core to commercial credit risk assessment. The main challenge here is to ensure that reliable financials are available from the customer. Small businesses may not be audited and thus the financials may be less trustworthy. Financial ratios can be divided into four categories: Profitability Leverage Coverage Liquidity Profitability can be further divided into margin ratios and return ratios. Lenders are frequently interested in gross profit margins; this is normally explicit on the income statement. The EBIDTA margin and operating profit margins are also used as well as return ratios such as return on assets, return on equity and risk-adjusted-returns. Leverage ratios are useful to lenders as they reflect the portion of the business that is financed by debt. Lower leverage ratios indicate stability. Leverage ratios assessed often incorporate debt-to-asset, debt-to-equity and asset-to-equity. Coverage ratios indicate the coverage that income or assets provide for the servicing of debt or interest expenses. The higher the coverage ratio the better it is for the lender. Coverage ratios are worked out considering the loan/facility that is being applied for. Finally, liquidity ratios indicate the ability for a company to convert its assets into cash. There are a variety of ratios used here. The current ratio is simply the ratio of assets to liabilities. The quick ratio is the ability for the business to pay its current debts off with readily available assets. The higher the liquidity ratios the better. Ratios are used both within credit scorecards as well as within policy rules. You can read more about these ratios here.   5) Size of loan When assessing credit risk for a consumer, the risk of the consumer does not normally change with the change of loan amount or facility (subject to the consumer passing affordability criteria). With business loans, loan amounts can range quite dramatically, and the risk of the applicant is normally tied to the loan amount requested. 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In the graph below the performance of an industry is tracked for two years and then projected over the next 6 months; this is then compared to the country’s GDP. As the industry appears to track above the projected GDP, a positive outlook is given to this applicant and this may affect them favourably in the credit application.                   7) Risk of Region   The last area of assessment is risk of region. Of the seven, this one is used the least. Here businesses,  either on book or on the bureau, are assessed against their geo-code. Each geo-code is clustered, and the projected outlook is given as positive, static or negative. As with industry this can be used within the assessment process as a policy rule or within a scorecard.   Bringing the seven risk categories together in a risk assessment These seven risk assessment categories are all important in the risk assessment process. How you bring it all together is critical. 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