The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

Mastering The Swiss-Army Knife Of Business Software: The Business Rules Management System

April 3, 2018 at 9:08 AM

Business Rules Management Systems (BRMS's) are the Swiss-army knives of business software. Despite this, very few companies we work with are getting the most out of their decision engines.

In this blog, we explore how BRMSs are used across the customer lifecycle.



The acquisition phase incorporates the prospecting for new customers. Once data is obtained on a candidate list, models can be applied to the data to understand the likelihood of response to a campaign offer, the risk, the underlying probability of attrition and perhaps the overall profitability.


The data can then be sent down a waterfall decision-tree to identify those who should be targeted.

As well as managing the selection. The channel and messaging of these customers should also be managed too. A good BRMS should allow you to test communication channels, messaging type, the right time to contact, etc. For clean tests, randomisation should be used.

Read more about Randomisation in the Credit Lifecycle here. 


OriginationsAs data-sourcing, analytical modelling techniques and legislative requirements increase and become more complex, so the demand for sophistication in a decision engine grows. This is particularly true in originations where a variety of decisions and calculations are required.

Of similar importance is flexibility. Changes to strategy and calculations should be in the hands of business and not IT. For the originations lifecycle, you need a scoring module, matrices and decision trees to combine scores, calculations executed (e.g. affordability, limit calculations, premium values or contract tariffs).

Account management

In credit, a critical component in account management strategies is the customer’s behavioural score. The behavioural score incorporates a variety of information (most notably balances, limits, repayments, delinquency statuses) from typically the last 12 months. The score produced indicates a probability of moving to three cycles delinquent in the next 6/12 months. 

A good BRMS should allow for the scoring of behavioural data to produce a behavioural score to be used in account management and account provision calculations.

  • Management of credit limits

One of the biggest drivers of profitability within a retail revolving credit business is through effective management of credit limits.  Data-driven strategies should be built to help tier credit-limit offers to ensure that appropriate limits are given to suitable account holders. Through a combination of scorecards, matrices, decision trees, and outcome tables a final % limit increase offer is determined within a BRMS. The final limit offer amount can be calculated based on limit, balance, percentage increase, maximum limit, minimum incremental increase, etc.

All strategies should be implemented on a champion/challenger basis.

The resulting limit increase offer is typically fed back to the host system that will then send out offers via the various channels.

Hand swiping debit card on pos terminal.jpeg
  • Authorisations

Although a simple “authorisation for the month” strategy (run alongside the monthly CLM batch) is common, most bank credit cards run more sophisticated authorisations. Authorisations should complement credit limit management strategies offering customers both a “fit” and “cushion” limit and potentially offering a holiday option too.

For authorisations, at a point-of-sale device, a transaction will be identified as pushing the customer above their credit limit. A call to the host system that in turn calls the BRMS is required.

Using the scoring engine, decision trees, authorisation table and calculations, a BRMS determines the “fit” and “cushion” percentages. This will be fed back to the POS to approve or decline the transaction.

Customer engagement strategy

Smiling blonde doing shopping in clothes store.jpegUnderstanding your customers through analytics enables a company to position an up-sell/cross-sell at the right time. Personalised actions can also be used to stimulate specific actions from the customer.  Customer engagement to reduce attrition, grow good balances and re-activate dormant customers are common. A BRMS can offer scoring, segmentation, clustering and action-tables for customer engagement.

If transactional data is used, then more advanced engagements utilising “next-best-product” are also available.

Given the importance of single point of truth and the awareness of product holdings for cross-sell purposes across the customer base, a BRMS ideally requires a level of flexibility and control.



Customer segmentation in collections is a critical requirement whether it’s determining which accounts to target for a pre-delinquency campaign, to prioritise accounts in early and late stage collection and to manage the legal process.

Customer segmentation is done through a combination of scoring and segmentation. The key segments are then allocated treatments also managed through a BRMS.

Additional tools can include:

  • Right-time-to-call models

Right-time-to-call (RTTC) models enable call-centres to improve their right-person connect rates for collections. This should be deployable within a BRMS. Collections prioritisation should incorporate risk, balance and contactability.

  • Outsourcing books

Your BRMS can be used to manage the out-sourcing of books to External Debt Collectors. 

  • Settlement optimisation

The allocation of an optimal settlement discount based on propensity to pay and indebtedness can assist a collection manager offer settlement most appropriate for each debtor. A BRMS can assist in passing maximum settlement discounts to assist in the collector’s negotiation process.

Monthly provisions/capital calculations

As a monthly compliance requirement, credit granting institutions require the calculation of monthly provisions. In addition to capital regulatory, capital calculations are also required to be produced for a bank. 

What this typically means is that organisations need an operational process whereby data is extracted from the host system, models and segmentation are applied to each account, the models are combined to obtain an expected loss (IFRS9) or risk-weighted asset (Basel). The provided amount is then reported on.

Read more on IFRS 9 for Retail Lending here. 


A good BRMS system should allow for the deployment of these models (typically behavioural scores, PD, LGD, EAD), the running of calculations and the production of reports. Data should also be extractable that will allow for monitoring of the models.


A part of the collections process is to know when to sell your non-performing accounts. By running a payment projection score on these accounts and understanding the collections costs, one can easily identify the candidate accounts for debt sale as well as a “fair price”. 

A BRMS can assist in managing these models. For sophisticated books, multiple models may be used not just looking at the “average” that’s likely be collected, but “best case” and “worst case” valuations.

At Principa we’ve built our BRMS, DecisionSmart, with business applications in mind. Currently, our software is deployed across multiple clients who use it for a variety of different applications across the customer lifecycle. Learn more about DecisionSmart here.

how to select a credit lifecycle software whitepaper

Thomas Maydon
Thomas Maydon
Thomas Maydon is the Head of Credit Solutions at Principa. With over 17 years of experience in the Southern African, West African and Middle Eastern retail credit markets, Tom has primarily been involved in consulting, analytics, credit bureau and predictive modelling services. He has experience in all aspects of the credit life cycle (in multiple industries) including intelligent prospecting, originations, strategy simulation, affordability analysis, behavioural modelling, pricing analysis, collections processes, and provisions (including Basel II) and profitability calculations.

Latest Posts

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. The loan/facility amount will of course change the ratios (mentioned in the last section) which could affect a positive/negative outcome. The outcome of the loan application is usually directly linked to a loan amount and any marked change to this loan amount would change the risk profile of the application.   6) Risk of industry The risk of an industry in which the SME operates can have a strong deterministic relationship with the entity being able to service the debt. Some lenders use this and those who do not normally identify this as a missing element in their risk assessment process. The identification of industry is always important. If you are in manufacturing, but your clients are the mines, then you are perhaps better identified as operating in mining as opposed to manufacturing. Most lenders who assess industry, will periodically rule out certain industries and perhaps also incorporate industry within their scorecard. Others take a more scientific approach. 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. If you would like to discuss your SME evaluation challenges or find out more about what we offer in credit management software (like AppSmart and DecisionSmart), get in touch with us here.

Collections Resilience post COVID-19 - part 2

Principa Decisions (Pty) L

Collections Resilience post COVID-19

Principa Decisions (Pty) L