Consumers demand instant, personalized services. Regulators enforce financial institutions to support improved decision making and to apply personalized strategies for vulnerable customers. Advanced Risk Analytics enables lenders to do so.
In this in stable economic climate with a long time low interest rates, bubbles may burst overnight. Regulators enforce banks and insurers to play a role in protecting consumers against over consumption of credit but also to apply personalized strategies for vulnerable customers once they are in the base. New legislation (IFRS 9) obliges banks and lenders to create forward looking impairment models.
AdviceRobo supports banks and insurers by providing continuous risk monitoring on an individual basis. Its behavioural credit scoring targets, profiles and monitors customers based on Machine Learning (ML). It predicts default, churn, loss giving default, and bad debt to enable banks to pro-actively service those customers that do need attention. In doing this banks and insurers can not only take care of customers but at the same time improve the customer lifetime value and profitability of their customer bases.
Benefits predictive credit scoring
Help financially troubled customers
Predict and prevent foreclosures and arrears
Lower default and churn rates
Compliant with IFRS9 ruling
Lower risk costs
Improvement of the quality of the portfolio
Additional behavioural information
Low cost SaaS solution
Fast set up process
Safe and secure data flow
Continuous monitoring on individual customer level
Results available 24/7
For our Advanced Risk Analytics we apply Artificial Intelligence on large data sets of financial and non financial data. The subsequent risk models (algorithms) are deployed on the AdviceRobo AI in risk platform.
Use case: A Dutch bank selling mortgages
- To increase the Gini score of the default model with 20%
- To decrease the default of the mortgage portfolio
- Data quality scan
- Application of AdviceRobo’s default model on the behavioural data of the customer base
- Increase AuRoc of 21%
- Increase of Gini of 61%
- Advice on improvement of data quality