Germany facing a tsunami of bad loans

For the german financial center, this development is a real danger due to the high dependency of many financial institutions on the lending business and the comparatively high cost ratio, especially since massive headwinds are to be expected not only in the corporate business. Private customers also face risks in their loan portfolios – real estate financing is particularly prominent here. If the recession continues, payment difficulties can be expected, especially after the boom of the last decade.

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Identify problems early

With non-performing loans becoming a dominant issue for the financial industry in the coming years, the question of how institutions can appropriately weather the impending storm is pressing. In contrast to the financial crisis of 2008, banks now have access to technological solutions that offer outstanding potential in the handling of loans.

The immense amount of data that banks can access on the basis of the accounts offered enables institutions to implement an efficient early warning system. Thanks to predictive analysis, institutions are usually able to foresee in advance whether and why a borrower will run into payment difficulties. Banks can proactively seek contact with clients and make suggestions for restructuring their payments even before the loan has to be classified as non-performing. This improved transparency allows banks to make targeted provisions and at the same time develop joint solution approaches with the customer.

Optimized recovery rate thanks to AI-driven restructuring

If the borrower is actually no longer able to make the agreed payments to the bank, the bank can support the user via a self-service portal. Online, the customer has the chance to restructure the loan. Assistance can be provided via chatbots, but also by bank employees on request. The banks would have to try to initiate the necessary steps and help the customer with his new planning on the basis of a defined set of rules.

AI can be used to determine a payment rate that is feasible for the debtor and the appropriate term, taking into account customer-specific data, but also by accessing historical data from other customers. Such a proposal from the bank could be worked out in detail with the customer via chatbot. Artificial intelligence is thus an essential tool that can be used to significantly improve the revenue ratio for banks. The debtor also benefits directly from the optimized recovery rate, as the new optimized planning enables him to pay off his loan after all.

Automated processes enable the ability to act even in crisis situations

Germany's banks have also been operating in a state of emergency since mid-march. Despite the emergency measures, the kfw loan program had to be distributed to customers under severe time pressure. This had to be understood as a wake-up call for digitalization and automation. However, the challenges facing institutions will not diminish in the coming months. In the fall, a massive additional effort is required in the area of credit management in order to be able to support customers with payment problems promptly and adequately.

Robotic process automation represents a good opportunity to achieve the urgently needed level of automation in the environment of legacy systems and manual processes. There is an urgent need to increase process efficiencies. Digital document processing (OCR) is also a simple and quickly deployable tool to prepare for the further impact of the crisis.

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AI & co: competitive factors even beyond the crisis

The local banking landscape has been struggling for years with high cost ratios and poor profitability figures. Digital technologies have emerged – and will emerge – as a decisive competitive factor in the credit business, which is essential for many banks. The peak of the crisis in march and april showed that digital application lines, for example, must form the basis for future credit management: especially in times of crisis, customers need to be supported quickly and proactively.

This is where the proactive implementation of new technologies for automation and process optimization becomes a crucial competitive factor. Improving efficiency in particular will be a key challenge, as additional burdens are unavoidable in the medium term and cost pressure will increase in the long term. Institutes are urged not to continue postponing necessary steps. The pressure on margins within the industry is too great. In fact, it is imperative to implement new solutions with a positive user experience in mind.