top of page

CASE STUDY

Fraud prevention & detection 

How we reduced a large financial institution’s vulnerability to fraud in their origination process

We worked with a large financial institution experiencing a high level of fraud in its origination process, particularly its loan application process. The institution was concerned that the high level of fraud was negatively impacting its profitability, and damaging its reputation as a reliable and trustworthy financial institution.

 

As a result, the institution was able to improve its fraud prevention and detection capabilities and reduce the level of fraud in its origination process. Additionally, it was able to better protect its customers from fraudulent activity and improve its reputation as a reliable and trustworthy financial institution.

Key results

Vector.png
Vector.png
Vector.png

Fraud levels reduced

Customers better protected

Improved reputation

Our approach

Review

Our team began by reviewing the bank’s existing credit loss models, including its methods for estimating credit losses under both ‘normal’ and ‘stressed’ economic conditions. Based on this review, we identified several areas where the bank’s models could be improved. 

 

Scenario analysis

The bank’s existing models relied on a limited number of economic scenarios, which may not have adequately captured the potential range of outcomes that could result from severe economic downturns. We recommended they use a broader range of scenarios, including scenarios that were more severe than those used in the past. 

 

Data quality

We found that the historical data used to estimate credit losses may not have been adequate for predicting losses under severe economic conditions. By reviewing and improving its data quality and considering using alternative data sources, such as macroeconomic indicators, the bank could supplement its historical data to better capture potential losses.

 

Model validation

As the models had not been rigorously validated to ensure they were accurate and reliable, we recommended that the bank conduct a model validation exercise to identify any weaknesses in its models and improve their accuracy. 

 

Deliverables

Based on our recommendations, we worked with the bank to develop new credit loss models and helped the bank to implement a more comprehensive scenario analysis process, including more severe scenarios and comprehensive data inputs. We also worked with them to develop a more rigorous model validation process, including back-testing and sensitivity analysis. 

Find out more 

Our work demonstrated the value of engaging a third-party consultancy to conduct stress tests on credit loss models. Our expertise and guidance helped the bank to identify weaknesses in its existing models and develop new models that were more robust and accurate. 

 

Whether you’re migrating, implementing or enhancing your models, we can support you by developing tools and strategies to provide insights and controls. 

GET IN TOUCH

bottom of page