The pandemic has undoubtedly caused a turbulent period for many organisations, especially SMEs. This period required a great deal of adaptation and flexibility to meet the new normal. Yet, financial institutions were also required to adjust their parameters for responsible lending and assess risk for organisations that were receiving larger government subsidies, but overall produced less income.
Establish collective data sets for debt support
Creditors and associations in the credit management sector have been striving for a fair debt policy to help prevent over crediting and improve debt counselling. Organisations such as the Royal Dutch Bailiffs Association (KBvG), the Dutch Association of Certified Collection Agencies (NVI), the Dutch Association of Credit Management Companies (VCMB) and the Dutch Association for Credit Management (VVCM) are striving for more collective debt data sets for consumers and small businesses, in the hope to obtain a clearer, holistic, and shared picture of the (irresponsible) debts of consumers and SMEs.
In general, there should be a trend towards increased co-operation in the entire lifecycle, including (social) debt-rescheduling and debt-support. This, in addition to maintaining common KPIs and discussion with regards to effectiveness of debt-rescheduling and debt-support.
Responsible Artificial Intelligence
Artificial intelligence can help maximise value and drive your growth, but when designing algorithms, it is essential that we assemble socially conscious, diverse teams who can constantly question how these algorithms might disadvantage specific communities – especially those that are already vulnerable. In addition, credit lenders should implement tools that help ensure lending is done in a fair, responsible, and transparent manner.
It is also important that customer experiences (CX) are designed to create value, are transparent and ultimately support the customer on their own data journey.
In 2022, it will be paramount to have a conscious and responsible mindset when observing data and designing algorithms. The right mindset combined with the right tools is essential to ensure fairness and accountability.
Transition to cloud and open banking
With an accelerating shift towards digital banking, more and more people are taking advantage of a new wave of convenient apps and services that can help them manage their finances. As a result of the pandemic, many individuals have turned to cloud applications – as accessing branches, or using cash, became increasingly difficult.
Open Banking for SMEs is likely to rapidly increase in 2022. Early adopters of the system will become increasingly advanced and in return, have a competitive advantage. Additionally, we will likely see more lenders improving customer experiences and decision making via PSD2 possibilities. Experian’s PSD2 solution uses the wealth of data that Open Banking has made available.
Use cases for PSD2, in combination with self-service, will standardise so that there is a match between payment capacity and payment arrangements. Most use cases will be seen in the onboarding of new customers and loan applications. In sectors where income verification is required (house rental, telecom, etc.), more and more use cases will be used to allow the process to be more consumer-friendly with more efficiency and accuracy.
The first use cases are already emerging in debt collection and credit management, where PSD2 is used to ensure payment arrangements are better fitted with customer’s payment capabilities.
A new understanding of Environmental, Social and Governance (ESG) risks
According to the European Banking Authority (EBA), ESG can have both a positive or negative impact on individuals, businesses, and financial institutions. After spending almost two years in the pandemic, weathering natural disasters and a changing economy, ESG matters must be considered in future decision making and credit risk taking.
Banks and lenders need to be aware of ESG issues and how these could increase risk to individuals they are lending to. By 2022, financial institutions and regulators should have action plans to respond to rapidly changing circumstances and ensure the resilience of the financial sector.
Increased use of machine learning (ML) and artificial intelligence (AI)
In April 2021, a draft of the EU Artificial Intelligence (AI) act was created, aiming at a legal framework for the use of AI and machine learning (ML). AI technology allows customers to better support their business decisions. Many businesses in the credit risk management sector have already been looking at ways to adapt AI and ML into their practices. However, the focus for 2022 will be on creating and explaining fair and transparent models.
The implementation and optimisation of AI within the customer journey will also be useful in empowering contact centre agents rather than replacing them. For simple interactions, chatbots will be increasingly used in contact centres. For more in-depth conversations, human interaction remains essential.
With proper data use, contact centers can be elevated from cost centers to revenue drivers. Maintaining and increasing customer satisfaction will create more upsell and cross-sell opportunities by making smart use of available internal and external data.