This year we met at the 14th Annual Banking Credit Risk Management Summit in a totally different formula than before. Since the Pandemic hit, all the world went on-line, so did the conference. Although we were not able to directly interact with all participants and actively take part in 2-day event, it was a great pleasure to meet those wonderful people who shared with us their experience, best practices and extreme knowledge.
So let’s see what we were talking about this year.
The attention of the conference was driven by two main topics – risk management in the post Covid-19 world and machine learning (ML) application, especially for the credit risk. There were presented a couple of great case studies showing a risk strategy adjustment that banks needed to undertake to meet a new Pandemic reality and challenges. As it was mentioned, banks needed to face it with a new approach in mind - be more forward looking and proactive. As one of the presenter told there were a great change in customer segments from those we know before the Pandemic. A new reality that every person needed to face during Covid-19 impacted their life, income, way of money spending and created new needs and expectations. Some banks managed to quickly adjust to respond to new expectations of their customers, and effectively responding to needs of the new customer segments.
The second part of the event, in fact very interesting, was a subject of Machine Learning (ML), to say so how to adopt algorithms that can learn from the existing data in order to predict future outcomes. The application of ML in bank can cover different areas from credit scoring and decisioning, stress testing, credit monitoring to collection and recovering. However, the biggest focus was on adopting ML for credit scoring and risk management. Although the ML is a very hot topic, its adoptions meet many challenges. As stated by speakers some of them are supervisory understanding to use process, difficulties to explain process, data quality and lack of appropriately skilled staff. Even though the ML is not a piece of cake, there were very interesting presentations showing use cases of ML or models implementation in their organization in the area of credit risk. Their outcomes and lessons learned.
We are looking forward to meet again next year, hopefully in a traditional on-site formula to be able not only listen to those great people but also be able to interact more actively.Anna Kowalik, International Business Development Manager at VSoft