An Evolving Risk Model for an Evolving Credit Risk Landscape

The past 12 months have been remarkably challenging for credit risk management. The world has been hit by a once-in-a-generation crisis, as the global pandemic disrupted society and ravaged economies. Even the most pessimistic credit risk modeling of previous years is unlikely to have predicted or captured the true economic shock of COVID-19 in advance.

The International Monetary Fund now estimates that the global economy contracted by 3.5% in 2020. While that reflects a slight improvement on previous forecasts, it nevertheless highlights the remarkable hurdles for businesses and governments in rebounding from the economic dip following this crisis. That provides a particularly acute challenge in the area of enterprise credit risk management. 

Neural Technologies’ Credit Risk Management product offers an adaptive and flexible solution to credit risk management, providing a customizable end-to-end opportunity built on the power of machine learning. That unlocks an automated and adaptive approach that’s vital to effective management of credit risk in this uncertain global environment. 

The COVID-19 crisis has highlighted the need for evolving credit risk analysis, and a credit risk solution that can adapt to the pressures of this volatile landscape. 

Pressures of global credit risk

There has never been a more pressing imperative to adapt your enterprise’s credit risk approach. Building an appropriate credit risk management solution that leverages detailed real-time data to provide informed analytics is crucial.

While an end to COVID-19 is now a glimmer of hope on the horizon thanks to remarkable vaccination efforts around the world, the credit risk overhang is likely to linger for years to come. In the UK alone almost 15% of businesses are at risk of closing by April according to the latest research by the Office of National Statistics. An EU-based McKinsey study in October revealed one-in-five SMEs was concerned about defaulting on loans and laying off employees. Similar findings are echoed in many markets around the world. 

Global economies are creaking at the seams, with global debt increasing by USD20tril since the third quarter of 2019. Total global debt is expected to have reached USD277tril by the end of 2020, equal to 365% of world GDP. 

Personal household debt is also facing a period of significant hardship. The United States National Bureau of Economic Research expects that more than 60mil borrowers will miss an estimated USD70bil of debt payments by the end of the first quarter 2021, following on from over USD2tril of loans entering forbearance between March and October 2020. 

These stark figures put into context the need for a modern, adaptive credit risk solution.

Evolving your credit risk solution with Neural Technologies

Neural Technologies has a long history of working with clients to deliver cutting-edge and data-driven credit risk solutions. The Optimus Credit Risk Management product is a responsive and scalable credit risk management software solution that can adapt to meet the needs of a high-volume data landscape.

Optimus Credit Risk Management is designed to offer predictive credit risk management based on advanced behavioral modelling, analyzing customer lifecycles, credit limits, risk scores, and other critical credit data. The adaptive learning model, combined with customizable rules and thresholds, offers an effective credit risk solution that meets the unique requirements of your business.

By utilizing machine learning technologies, Optimus Credit Risk Management provides a powerful automated solution to credit risk analysis. Risk prediction models can identify and analyze key credit risks such as bad debt prediction, usage prediction, and anomaly detection, leveraging time-series decomposition and behavioral understanding to flag key credit risks. 

Comprehensive link analysis ensures that credit risk analysis goes beyond simple static data points, and instead builds a complete picture of the links and associated credit risks for an applicant or customer. That provides a powerful solution to tackle key fraud risks such as subscription fraud, as well as limiting exposure to bad debt.

Neural Technologies’ data analysis functionality is designed to provide a simple pathway for agents to identify and oversee risk, while providing automated solutions that greatly improve application approval and credit risk decision making. A simple alert system flags high-risk cases to risk management teams, and categorizes risks for ease of oversight.

Credit risk can be further mitigated through use of the Optimus Application Risk solution, offering fast and accurate accept/decline/defer decisions that support credit management and enable your teams to focus on high-risk cases. This solution offers personalized and automated credit limit recommendations based on applicant data, ensuring guardrails for your credit risk exposure. The automated approach is crucial in enabling your team to focus on demanding cases, while ensuring seamless onboarding of customers that may otherwise be delayed or deferred by less accurate credit risk modelling software. 

Neural Technologies’ advanced data solutions work to complement your credit risk case management approach, offering advanced investigation, business intelligence, and data mining tools, adding greater depth to your credit risk oversight. This enables users to manage each and every case effectively, as well as performing ad-hoc queries on customers and transactional data to further investigate hidden risks or unusual activity.

The credit risk landscape is evolving at an increasingly rapid pace. That means an effective credit risk management solution must be able to adapt and meet the needs of that changing environment. 

With the power of Neural Technologies’ machine learning-driven Credit Risk solution, you can prevent revenue leakage and decrease exposure to bad debt in even the most high-volume billing and application landscape.