AI in finance need not be scary

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Does the use of artificial intelligence make sense in risk management processes?

The first practical experiences in business show that it does. Banks can use AI to build more models using more variables. This allows them to better segment clients for credit scoring or debt collection processes, preventing financial losses on bad loans. This is especially important in crises such as the pandemic because customer behaviour and savings and spending habits have changed.

The financial markets have noticed a huge change in payment flows. The credit risk has increased, as has the market risk. Financial institutions want to optimize their response to the requirements of a rapidly changing market. So they try to optimize credit policies and processes to allow them to continue to operate effectively while reducing the number of “bad” customers.

Banks and lenders are investing in AI-based scoring accelerator solutions that allow for quick reorganization of loan processes in changing times. These activities are a win-win strategy for both banks and customers.

'Homework' for anyone who wants to use AI to support business processes

Artificial Intelligence in good hands will certainly bring tangible financial benefits. However, it should be applied in a holistic and multithreaded way. AI algorithms are the heart of the system, but they must be set into a properly prepared environment, architecture and infrastructure. The value from AI will be realized only when the process is operationalized. Close cooperation between analysts, developers, ModelOps, validation and IT is crucial.

AI mechanisms must have access to a long series of historical data to support self-learning. This means they work best in profitable business processes that are proven and rich in data. It is better to leave difficult, complicated and incomprehensible processes for later, to avoid disappointment. We must also be realistic and not expect miracles. It will take time to learn how to use AI.

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About Author

Łukasz Libuda

Łukasz is responsible for supporting SAS customers in the Central Europe region in the effective development and transformation of Enterprise Risk Management areas with particular emphasis on Asset and Liability Management (ALM), Integrated Balance Sheet Management, identification and management of Credit, Market, and Operational Risk, Liquidity Management from a managerial and regulatory perspective (Basel III/IV, IFRS9). Passionate about new emerging topics like finding the most effective approaches to ESG (Environment, Social, Governance) analytics, calculation, and reporting. Based on many years of professional experience, Łukasz supports organizations in unlocking growth by creating processes and developing risk management concepts at the strategic enterprise-wide level, planning and implementing stress test mechanisms as key tools for risk managers in turbulent times. With his team, he supports customers in protecting profits by implementing AI-based analytics and real-time decision-making processes for Credit Origination, Early Warning System and Collections, obtaining compliance in comprehensive Risk Management, Governance and Compliance. Łukasz education matches very well with his business profile. He graduated from the Warsaw School of Economics and was awarded two master's degrees: 1) Finance and Banking and 2) Quantitative Methods and Information Systems. Additionally, he was awarded a master's degree in International Management by the Community of European Management Schools (CEMS) and finished postgraduate studies in Audit, Financial Control and Accounting.

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