Credit risk – The bank data challenge in frontier markets

As the regulatory net tightens, banks working in and across frontier regions are under pressure to source and maintain more accurate data in the assessment of counterparty credit risk, but some are investing in tools to tackle the problem

For credit risk analysis to be truly effective, banks need to be able to access the right kind of information to analyse risk and manage exposure to counterparties. However – particularly in frontier markets – it can be a struggle to not only find accurate data, but also ensure it is analysed consistently across the credit risk management function. 

Financial regulators in many parts of the world are coalescing around a common set of principles for financial services organisations. One effect is increased demand among banks for greater volumes of data to feed risk management systems and processes. At the same time, banks must demonstrate they can use this information consistently and accurately. 

It is not only important to gather the information – we also need to gather the correct information and to be able to use it effectively in assessing credit risk

Fatma Sayari, wholesale credit risk analyst, Bank ABC

“In countries where [the Basel Committee on Banking Supervision’s Core principles for effective banking supervision] have been adopted, banks have to go through the Internal Capital Adequacy Assessment Process, for example,” says Paul Whitmore, global head, counterparty risk solutions at Fitch Solutions. “That means proving a certain level of understanding to the regulators in terms of the methodology being used to assess risk, as well as what it is being benchmarked against.”

As a result, market participants in a growing variety of regions are vying for access to the necessary data to ensure they can manage risk, satisfy regulatory requirements and compete in both local and international markets. 

So, what data challenges do banks face when measuring and reporting on credit risks in the current market environment? And how can organisations ensure they are analysing accurate data consistently across the credit risk management function? 

“It is not only important to gather the information – we also need to gather the correct information and to be able to use it effectively in assessing credit risk,” explains Fatma Sayari, wholesale credit risk analyst at Bank ABC in Tunisia.

While larger, established banks can typically draw on large volumes of data from many years in the market, smaller or less seasoned entities may not have the same internal infrastructure or market experience to support information-gathering efforts. As such, a lack of default data for certain asset classes and fundamental data from clients can be a major challenge for some organisations in developing markets. 

Another hurdle lies in the task of creating the necessary models to analyse both quantitative and qualitative information, according to Whitmore. While establishing quantitative models to measure credit exposure is relatively easy for most banks, he explains that qualitative metrics can be more difficult to identify and measure. 

“Qualitative data can often be neglected because it’s very difficult to put a structure around that kind of information – for example, how do you quantify weak management compared to good management practice?” he says.

While banks in these markets currently have some resources to address these issues, many are also planning to invest further in new technology. 

Accessing the necessary information to ensure accurate analysis of credit risk is becoming easier, but investment in the latest tools, systems and processes to gather and process data efficiently and effectively is key

Valentin Valentin Redondo, senior credit risk analyst, corporate banking, Banco Cooperativo Español

“As a second line of defence, we rely mainly on relationship managers to collect the required information, including anything that may impact a credit profile, for example management information, cyclical activities or strategic decision-making information,” Sayari says, adding that analysts at her organisation also conduct sector studies every six months to assess current trends and analyse the impact of future events.

According to Valentin Valentin Redondo, senior credit risk analyst, corporate banking at Banco Cooperativo Español, “Accessing the necessary information to ensure accurate analysis of credit risk is becoming easier, but investment in the latest tools, systems and processes to gather and process data efficiently and effectively is key.”

Discussing the more bespoke offerings and detailed sector profiles available in the credit risk analysis space, he says: “For me, these tools have very valuable information.” Such products can be adapted to fit the current programmes or more general credit risk needs of a bank, he explains, which makes the additional expenditure worthwhile. “It is true that it involves a greater investment of resources and money, but instead it saves a lot of time to develop other processes in parallel,” Redondo adds.

Banco Cooperativo Español sees investing in this area as “essential”, according to Redondo. “The firm allocates a significant part of the annual budget to hire people and develop these services,” he says. 

Likewise, Sayari notes that, alongside many organisations in Tunisia, Bank ABC is investing in new tools to bolster its credit risk systems and processes, and boost connectivity with other organisations and counterparties for information-gathering purposes.

Timely access to relevant, accurate data is crucial to financial organisations as they compete in an increasingly global marketplace. As such, developing or accessing tools to support areas in which internal data reserves are lacking is key to establishing a robust credit risk analysis function.

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