Credit Risk Management in a Post-COVID World
Neural Technologies’ Credit Risk Management solution provides a scalable credit risk management solution for enterprises across a wide range of industries, with risk prediction models that allow smooth onboarding of customers in even a fraught financial landscape.
The need for a dynamic credit risk management strategy is evident in an ecosystem still framed by the uncertainty of COVID-19. Global debt has spiraled to eye-watering figures during the pandemic, with research by the Brookings Institute indicating that total global debt saw its largest single-year increase since 1970.
Private domestic debt made up a significant portion of this increase, highlighting the real challenges that many households are facing, and accounting for more than 60% of the total rise in global debt. This figure was even more stark in emerging market economies, where domestic debt accounted for more than 90% of total rise in debt, compared to around one-half in advanced economies.
Enterprises need smart credit risk solutions that are fit-for-purpose in this landscape, balancing the need to maintain nuanced but vital credit risk decisions against the unprecedented challenges facing households.
Credit risk in a COVID world
Global debt reached a record USD226tril in 2020 according to the latest data by the International Monetary Fund (IMF), representing the largest debt surge since World War II.
These figures are almost impossible to contemplate, and in many ways can almost obscure the individual pressures that households—and indeed corporations—face in this challenging environment.
A study from Pew Research in the US shows that 30% of US adults are worried every day, or almost every day, about their level of debt, and approximately half of non-retired adults say the economic consequences will make it harder to achieve their financial goals.
The impact of household debt is not unique to the US. Singapore saw expanding household debt through 2020-2021, reaching 70% of GDP by the third quarter of 2021, rising 6.8% in absolute terms. The figures for neighboring Thailand are even more stark, rising to USD430.16 billion in Q3 2020, equal to 89.3% of GDP. These are just two further examples in a world facing growing debt pressures.
Almost a year on since we first explored this topic, it’s clear that credit risks remain a looming concern for businesses, households, and economies. While some of the worst predictions were narrowly avoided—global debt peaking USD50tril below some predictions—the situation remains extremely strained.
In recognition of this challenging environment, banking authorities and regulators around the world have made significant efforts to ensure credit risk management strategies are appropriate for the strained landscape.
The European Central Bank undertook a major analysis in Q2 2021, and highlighted the steps which must be taken to address this challenge. It’s first recommendation was that “A strong data infrastructure is vital as it underpins a bank’s ability to understand the risks it is facing. Data should be readily available and easily aggregated.”
This ethos of smart decision making based on effective data systems is at the heart of our own Credit Risk Management solution, and offers a compelling message for enterprises far beyond the institutional banking system.
Credit risk solutions from Neural Technologies
Neural Technologies’ credit risk management solution leverages behavioral modeling to deliver a predictive credit risk management that can be uniquely tailored to your enterprise requirements. It analyzes customer lifecycles, credit limits, risk scores, and other key credit data, with customisable thresholds and rules that can be adapted to your operating environment.
The automated, machine learning-driven solution can also provide rapid analysis and decisions in a landscape with high volumes of applications or debt defaults, backed by risk prediction models that speed up the process while quickly capturing any flagged risks.
An intuitive alert system flags any high-risk cases to an analyst team as desired, while low-risk cases can be quickly and automatically processed with accept/decline/defer decisions without the need to tie up resources with manual oversight.
This combination of adaptable risk thresholds and automated approval pathways provides a highly scalable solution—a critical functionality in the current high-debt landscape. This means enterprises can maintain rigorous credit risk assessment standards without compromising on customer experience with long delays from manual processing, or hyper-cautious responses through more rigid rules-based solutions.
Even as we look optimistically towards a post-pandemic future, we must recognize that the debt problems triggered during this period will not vanish overnight. That’s why an appropriate credit risk management strategy must prepare for high-volume activity as the norm, and embrace the right technologies to operate successfully in this landscape without compromising on responsible risk management.
