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In Focus Risk

Following an unprecedented period of growth which resulted in a thirteen-fold increase in accounts (to 30 million) and receivables (to $33bn) between 2005 and 2014, the credit card industry has not been left unscathed by the poor economic situation. Characterised by weakening levels of

expenditure, recently imposed interest rate caps, as well as a rapidly decreasing risk appetite to extend facilities, card issuers, in particular, have felt the full wrath of the economic crisis. Recent statistics suggest that the

deterioration shows no signs of abating, when looking at the FICO Credit Health Index, a measure of Russia’s credit health based on the percentage of consumer assets that are delinquent by more than 60 days. Having steadily declined from its peak in early 2012, the ratio of loans and credit cards in an adverse state was in excess of 13.4% in February 2015, compared to just 7.1% in January 2012. However, in each crisis there are

indisputable dangers that mandate treatment – but, at the same time, there are opportunities waiting to be harvested. The challenge for banks is identifying these opportunities whilst addressing the pitfalls during turbulent times. Issuers face two parallel challenges –

knowing how to manage the risk and sustaining the quality of their back book whilst ensuring that the front book (meaning new accounts) is representative of the most profitable acquisitions. Given their huge tribulations, issuers will

need to be certain that the steps taken are those which best retain card utility for customers whilst at the same time managing risk to within acceptable levels.

Credit risk solutions There are several solutions recommended for Russian banks to generate the maximum benefit in the most responsible and profitable manner. The most proactive, or least restrictive, as well as immediately beneficial, is credit limit management. Credit limits represent the core

functionality underpinning the utility of a 38

credit card, and are of paramount importance for successful risk management – more so during crises, due to the increased regulatory scrutiny on capital exposures. In essence, limit management encompasses: l Initial assignment. l Limit increases. l Limit decreases. Whilst aimed at achieving different

objectives, each substantially influences the risk and profitability of a portfolio.

Initial limit assignment There are typically three levels of initial assignment complexity deployed by regional issuers. The effectiveness of each varies significantly depending on a number of factors, such as lending environment maturity, analytical capabilities of banks, and credit bureau availability.

Decision optimisation There have been material advances in initial assignment, effectively representing a ‘fourth level’ of complexity referred to as ‘decision optimisation’. It provides issuers with the optimal initial

assignment strategy by assessing the relationship between actions (initial assignment) and their impact in terms of activation, usage, risk, attrition and resultant profit.

Each of these factors are used as inputs

to optimise profitability based on pre- determined business constraints, such as maximum total limit exposure.

Applicability to the Russian market Given the number and disparity of Russian banks, it is hardly surprising that there are palpable differences in complexity, effectively translating to a substantial opportunity to improve the initial assignment practices across the industry. Consider the following illustration.

Medium complexity frameworks typically provide income-to-limit multipliers that are primarily risk-based and linear, so that a better risk means a bigger limit. However, an issuer’s framework can be evolved from a risk-based assignment to instead adopt an advanced profit-based assignment, especially pertinent during economic crises. Using predictive models, advanced

methodologies aim to constrain losses to the highest unit risk segments by assigning the lowest limits. This constrains losses to the lowest unit risk segments by setting initial limits that consider the trade-off between a high value loss on the few bads against typically low usage or utilisation on good accounts. It maximises the high usage propensity in the middle unit risk segment where usage and revenue is likely to be robust and bad rates average.

February 2016

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