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Comparing Debt Collection Software with Traditional Methods

Comparing Debt Collection Software with Traditional Methods

Traditional debt collection processes cost financial service providers a fortune in time, money, and human effort.

Before the introduction of the now-trending automated debt collection, loan service providers across the globe struggled with several challenges that come with using traditional means of recovering loans, including:

  • High legal fees
  • Time-consuming processes
  • Poor risk management
  • High operational costs
  • Human errors, e.g., wrong customer contact, input errors

To stay competitive in the global market—where services are fast going digital—financial companies are quickly revisiting their debt collection strategies.

Many loan services and debt recovery agents have abandoned the traditional method of retrieving debt in favor of an automated, software-assisted approach.

Overview of Traditional Debt Collection Methods

The old pattern of retrieving loans is managed by a recovery team or agency that ensures borrowers meet the loan repayment terms.

The most popular traditional debt collection strategies include:

  • Regular phone calls and repetitive reminder letters via mail
  • In-person physical visits to debtors’ homes or offices to discuss loan terms and payment alternatives
  • Hiring professional third-party debt recovery agents
  • Taking legal actions against loan defaulters
  • Manual tracking

For customers, the repetitive phone calls, regular mail, in-person visits, and threats of legal action can be depressing.

These overly physical debt collection techniques can offend borrowers who, in many cases, discontinue doing business with the loan service providers.

In a UK survey by InDebted, 2 out of 3 adults said they’ve had stressful experiences with debt collection agents.

It’s a whole different ball game with an automated process where software manages debt collection.

What’s Debt Collection Software?

Debt collection systems use artificial intelligence and machine learning to automate and manage debt recovery processes.

This digital method of loan recovery slashes operational costs, increases the debt recovery success rate, and significantly reduces borrower-lender conflicts.

Unlike the old methods, the loan recovery software automates the recovery approach with automation, data analytics, and customer segmentation. Adopting software for debt collection can save costs and reduce delinquency cases—without hurting the customer-client relationship.

Benefits of Collection Software Over Traditional Debt Collection Methods

More Streamlined, Efficient Processes

Debt recovery software provides easy access to customer data across all units of the organization. This includes sales, accounts receivable, and risk management.

The loan collection software can integrate smoothly with existing payment gateways, CRM, customer service, and accounting software used in the organization. This way, debt collection teams can efficiently monitor and manage several stages of the recovery process from a single central dashboard.

This central dashboard reports borrowers’ credit behavior and identifies delinquent accounts without spending hours flipping through piles of paper documents.

Accurate Input, Data Gathering, and Data Analysis

Human errors common with traditional manual data entry. This includes mistyped account numbers and searching in the wrong places for borrowers’ information. These errors can significantly frustrate the debt collection process and reduce the debt recovery success rate.

The near-flawless accuracy of digital debt collection systems places software collection methods many points ahead of the old-aged loan recovery methods.

Automated Processes, Less Labor, Less Operational Cost

Behind most successful and timely debt recovery processes are many hands and a good budget to manage the different aspects, such as regular visits and hiring law firms for legal actions.

These costs can significantly reduce a business’s return on investment (ROI). On the other hand, a debt collection platform auto-manages most tasks in the debt recovery process. This reduces operational costs and increases profit.

Financial services that switch to automated digital debt recovery systems can boost their profit margins significantly. With fully automated credit checks, payment processing, account selection, and documentation, loan recoverers can save a lot of time and budget.

Staying Compliant with Automated Debt Collection Software

With frequent updates in loan recovery regulations, maintaining compliance remains a common concern among debt collectors.

Many companies have been caught in the legal web. They have paid heavy fines for failure to comply with the industry’s rulebook.

The software’s ability to update in response to changes in industry regulations is quite fascinating.

Debt collection platform ensures all actions and loan recovery activities with customers align with industry and legal standards. This helps to avoid penalties that may ruin a business and/or its reputation.

Software solutions come with features that help financial service providers stay within legal and ethical boundaries throughout the debt recovery process.

Software debt collection solutions offer a more transparent, compliant, and safe debt collection system with features such as automated audit trails, auto-documentation, and online security.

Recover Debt More Smoothly with Debt Collection Software

The traditional phone calls, reminder letters, physical visits, and legal actions used in debt collection can be costly, time-consuming, and prone to human errors.

Thankfully, debt recovery software introduces AI and machine learning to loan recovery. This digital approach is more efficient, accurate, and compliant while slashing operational costs and reducing customer-lender rifts.

With its smooth integration with existing systems and user-friendly interface, financial service providers still using old debt collection methods can easily switch to software-based debt collection without disrupting operations.

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