Regulation and market disruption is forcing a convergence of delinquency and lending assessment.
Gain a competitive advantage by integrating this all under a new credit risk management structure.
Dynamically react to market changes and risk through predictive analysis, AI and machine learning
Credit Assessment needs to brought into the future
Outdated credit scoring has not kept pace with market change.
The cost:
- Locking banks out of new markets
- Exposing banks to risk creep, (What was safe no longer holds true)
- Government pressure on market failure like SME lending
Funding costs increases for traditional lenders
Shrinking deposit pools, increase competition, global movements of rates are going to put upward pressure on cost and access to retail deposits.
Do you have the sophisticated tools to demonstrate the quality of the loan book and the risk management processes to alternative sources of funding?
IFRS9 and Basel IV – Forcing Change
In calculating probability of default for IFRS9, you are duplicating the credit score process. This is forcing a rethink of the traditional lending process and how banks price loans.
- Traditional lending models are inconsistent with Regulatory direction
- Historical risk analysis is inconsistent with Regulatory expectation of predictive analysis
- Stakeholder expectations are changing (Rating agencies, wholesale funds, customers)
Software for the future
S4S-Credit Risk is taking banks on the journey from traditional lending and risk to the Credit Risk Management systems of the future.
If you are looking at how to take your lending and credit risk management into the future with sophisticated tools such as AI, machine learning, predictive analytics then talk to us.