Credit decisioning in the banking, financial services and insurance industries in three APAC markets can be improved: study
In a Nov 2021 survey of 164 banking, fintech, and non-banking lending decision makers managing credit risk in Australia, Indonesia and India, respondents were increasingly aware of the critical need to improve their assistance to customers to help them avoid falling into financial hardship.
Poor credit decisioning can negatively impact customers’ financial situations amid the COVID-19 pandemic: 54% of banks and lenders in the survey indicated that that putting customers in a hard situation was one of the top implications of a poor credit decisioning, just behind financial loss (60%).
Yet, respondents had to consider that providing fast and easy credit to more people could put consumers at risk of overextending themselves. Therefore, using alternative data to ensure credit risk assessments are accurate in setting personalized spending limits was also an important risk management strategy.
Across the three markets surveyed, three trends came to light:
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Credit decisioning automation
- Increasing automation was ranked by 73% of respondents as a high or critical priority for credit risk assessment and management in the next 12 months
- 52% of respondents indicated this was to increase the speed of credit decisions
- 50% of respondents indicated this was to reduce manual errors in the risk decisioning and management process
- 50% of respondents indicated this was to reduce manual errors in the risk decisioning and management process
- 50% of respondents indicated this was to reduce manual errors in the risk decisioning and management process
- Broad spectrum of data sources needed
- 44% of respondents indicated that improving the use of data and insights in business decision making had emerged as a top priority for businesses
- 34% of respondents agreed to prompts that their organization has declined applications from viable customers due to insufficient credit data.
- 41% of respondents indicated the intention to improve risk assessment and management by leveraging more traditional forms of data such as banking or credit bureau data over the next 12 months; 40% intended to tap new data sources such as alternative credit data for credit risk and management over the next 12 months.
- Alternative data sources include telco data, consumer data, or e-commerce data. The use of alternative data means lenders can better assess their customers’ creditworthiness, providing them with critical access to credit which could transform their lives for the better.
- Prioritization of long-term customer relationships
- 23% of respondents were focused on reducing cost when managing the increased volume of customer interactions online; with others investing more in better customer engagement and relationship building.
- 43% of respondents considered improving CX as the one of the most important business priorities, while 42% cited growing revenue
- Outside of this survey, external data had indicated that 59% of respondents would give a company more business if they felt that they were treated fairly
The study also found that 80% of respondents were focusing on developing monitoring and early-warning systems as a top risk management priority over the next one to three years. This could help them predict and identify early signs of financial stress, including taking on higher-cost loans; a loss or drop in income; greater reliance on savings; and a shift in spending on high priority items. In response, personalized management plans can be offered to affected customers through the difficult times.
According to Malin Holmberg, CEO (EMEA and Asia Pacific), Experian, which commissioned the survey: “We’ve seen a shift since the start of the pandemic, where businesses were forced to digitalize quickly and focus on immediate concerns such as cutting costs. These companies are now looking at longer term strategies and are focused on addressing existing gaps. Many banks and lenders are investing in the right technology to improve the speed of their credit decisioning, and using automated decisioning, data and analytics to quickly identify customers in distress to provide a more holistic customer experience.”