How Cognitive Technology Can Support Credit Risk Management
Technology is transforming the banking sector in more ways than one can imagine—from managing customer data to handling collateral through assessing credit risk. The evolving cognitive technology that derives computational capability from machine learning, natural language processing, and artificial intelligence enables banking sector to enhance the process efficiency and predictive accuracy while assessing credit risk of their clients. Besides, cognitive computing technology will benefit the banking industry in a myriad ways, especially in controlling and monitoring credit risk management. It will not only improve the management but will also help banks achieve greater cost-efficiency and better client relationship.
Cognitive computing has the potential to transform the credit lifecycle that encompasses loan negotiation, understanding capital requirements, and the recovery of principal and interest. Now, banks can easily comprehend the capital structure of their customers. Besides helping to enhance credit risk management efficiency, cognitive technology also enables banks to remain compliant with various regulatory and monetary policies. Based on the compliance requirements, credit risk officials are required to complete a minimum of 400 questions focused on customer’s business capital structure. The responses for credit risk assessment questions can be collected from clients as well as from external sources that are directly or indirectly associated with the client.
As a new frontier in banking innovation, cognitive technology can support compliance and risk in critical areas including know-your-customer (KYC) procedures. According to Finextra and Pega research, it takes nearly five weeks to onboard a new client and costs up to $30,000 dollars to complete the onboarding process, and 88 percent of banks are complaining that KYC requirements are negatively impacting these onboarding times.
Above all, this technology will revolutionize the process of managing credit risk, bringing enhanced visibility, accuracy, accountability and transparency in the system. Further, the job of client onboarding team responsible for controlling and monitoring client relationships becomes easy, enabling them to remain up-to-date. Moreover, the ability of cognitive technology to generate early warning signs to help credit risk professionals would be highly beneficial to manage each stage of credit risk lifecycle better.