How AI is Revolutionising Financial Services: From Underwriting to Collections

Artificial intelligence (AI) is transforming the financial industry, particularly in underwriting and collections processes for insurance, loans and credit cards.

Its ability to analyse vast amounts of data quickly and accurately has led to more efficient, objective, and reliable decision-making processes, benefiting both lenders and customers.

How AI is being used in underwriting

In underwriting, AI is helping financial institutions to assess creditworthiness more precisely and swiftly. Traditionally, underwriting relied heavily on limited financial data, such as credit scores and income levels, to evaluate whether a borrower could repay a loan. 

However, AI can now incorporate a wider range of data sources, including alternative data like social media behaviour, utility bill payments, and even shopping habits. 

By analysing this expanded data set, AI can generate a more detailed profile of a borrower, allowing lenders to make more informed decisions. 

A key advantage is that AI can assess these data points in real-time, significantly speeding up the approval process. According to a study by McKinsey, banks using AI in underwriting can reduce loan approval times by up to 40%, enhancing the customer experience by offering almost instant decisions.

AI’s role in underwriting also extends to improving risk assessments. Machine learning algorithms, which are a subset of AI, can identify patterns in historical data that may be missed by human underwriters. 

For example, the AI can detect subtle signs of financial distress or irregularities in spending patterns that indicate higher credit risk. This predictive ability enables lenders to better gauge the likelihood of default, reducing the risk of loans with bad credit and other high default loans.

Additionally, AI models can be updated continuously as new data becomes available, making the risk assessment process dynamic and adaptable to changing economic conditions. This is a major improvement over traditional static models, which can quickly become outdated in fluctuating markets.

How AI is being used in collections

In collections, AI is being used to enhance both efficiency and effectiveness. One of the primary ways it does this is by personalising the debt collection process. In the past, collections were often managed using a one-size-fits-all approach, where all borrowers received the same type of communication regardless of their specific situation. AI can analyse a borrower’s financial behaviour and communication history to tailor the collection strategy. For instance, some customers may respond better to friendly reminders via text messages, while others may prefer formal email notifications. A survey by the World Economic Forum found that AI-enabled collections systems could improve recovery rates by as much as 20% due to these personalised strategies.

AI also assists in predicting when borrowers are most likely to pay for things like credit cards and fast cash loans. By analysing past payment behaviours, AI models can suggest the optimal times to contact borrowers, increasing the chances of successful collection. 

Moreover, AI-powered systems can prioritise accounts based on the likelihood of repayment, allowing collection agents to focus their efforts on cases where they are most likely to recover debt. This targeted approach not only saves time but also reduces the overall costs associated with the collections process.

Furthermore, AI helps in maintaining a fair and compliant collections process. By automating certain steps, such as sending reminders or processing payments, AI minimises the chances of human error or biased decision-making, ensuring that all customers are treated consistently and fairly. This is especially important given the strict regulations governing debt collection practices.

In conclusion, AI is revolutionising both underwriting and collections by improving efficiency, accuracy, and customer experience. By leveraging large sets of data and advanced algorithms, lenders can make better credit decisions and recover debts more effectively. As AI technology continues to evolve, its role in these processes will likely become even more integral to the financial industry.