The COVID-19 pandemic has certainly caused a striking deterioration across all industries, compelling us to rethink business strategies to wade through the crisis. While other industries are likely to overcome its immediate effects, the financial services industry will have to bear its economic impact in the long term.
The overall delinquencies on industrial and personal loans have increased to reach a serious level. The COVID-19 crisis is going to change the way people think about debt and new mortgages because of its consequences of unemployment, loss of revenue, cautious spending habits, and a fall in disposable income.
Even governments across the globe are providing relief packages to individuals and business borrowers to help them sail through this crisis. As a result, lending institutions have been constrained to offer temporary postponements of loan payments and other modifications. This all is going to have a direct impact on banks, credit unions, and financial institutions on how and how much they can collect from debtors.
However, AI-based debt recovery can help you maintain cash flow, improve the flow of incoming revenue and reduce Days Sales Outstanding (DSO). Therefore, finance leaders are looking to foster business resiliency through agile technologies such as artificial intelligence and RPA to manage credit risks.
Artificial Intelligence Delivering Business Resilience to Banks and Financial Institutions
The contribution of AI in business resiliency can be traced in three major areas, amongst others: cash flow, coworker safety, and wellness, and customer retention. Businesses can remain resilient by accommodating AI and intelligent automation in these areas.
1.Cash Flow:
The foremost priority of the financial leaders is to make informed decisions on cash flow while ensuring all the stakeholder relationships are kept intact. Financial organizations would require a close analysis of processes that impact receivables to overcome leakages and bottlenecks. With the use of AI in business, financial leaders can discover and analyze these processes to forecast quickly and minimize revenue loss.
2.Coworker Safety and Wellness:
In the initial days of lockdown across geographies, managers at all levels wanted to know their coworkers’ health situations and where they were. This is because employees’ wellness is tied to their workloads and the reduction in resources because of lockdown may overwhelm the remaining staff with spiking workloads. Here, if the bank is struggling with unmanageable stacks of financial paperwork and back-office operations, the bank can leverage artificial intelligence solutions to process this backlog of documents with improved accuracy.
3.Customer Retention:
Every brand needs to stay close to its customers to retain them. Most financial services consumers expect omnichannel banking experience and personalized financial advice. AI-driven customer retention strategies can help here by ensuring timely and appropriate responses. Artificial intelligence solutions can pull off such efficient customer engagement through customer service automation, customer insights, etc.
Debt Collection with AI for Improving Receivable Management
Lenders can use artificial intelligence in various ways to collect debt effectively. With the use of intelligent debt collection solutions, lenders will not only be able to identify and manage credit risks but will also reap rewards like higher collection liquidation rates and reduced cost of collection. AI-driven debt collection can help financial institutions with customer-centric debt collection, regulatory compliance, and customized insight-led solutions, all of which are key to successful receivable management.
Here Are The Top Three Ways You Can Use AI In Debt Collections:
- Using real-time, high-velocity data for better collection rates: Generating insights across customer’s journeys is a key to identify trends, anomalies, and opportunities. Traditional debt collection tactics used to rely on human instincts. Here, we will rather use siloed data sets and logical sequential data to develop insight-led solutions.
Advanced AI/ML analytics will translate some insights into actions such as identifying early potential defaulters using predictive modeling, notifying collectors to check on at-risk debtors proactively and provide credit counseling support, and restructuring payment plans. - Using behavioral science to personalize customer experience: Debt collection strategies can be modified using insights based on customer’s demographic and socio-economic data, salary, occupation, and historical interactions. This will ensure the right channel and follow-up actions where you will probably get a positive response.
- Enhanced customer experience: Artificial intelligence solutions with automation bots can carry out smart dialogues between businesses and customers via email, SMS, or any social media platform. This will enable collectors to reach exactly where the customer logs in several times a day and can pay the outstanding debt online, resulting in faster delivery of receivables.
Benefits of Intelligent Debt Collections
AI makes debt collection more efficient and a customer-centric process, which leads to several benefits that include:
- Improved communication
- Streamlined processes
- A better understanding of customers
- Optimized debt collection strategies
- Better pay-back rates
- Fewer insolvencies
- Automated communication
Conclusion
AI is a powerful debt collection tool that can turn your debt collection resolution into a user-friendly journey. Even better, by implementing AI, you will set the stage for enhanced business intelligence and borrower analytics, providing a 360° view of the customers you are lending to.
