What Could Big Data Mean for Debt Management?

What Could Big Data Mean for Debt Management?

Big data is changing the way the financial world handles client interaction. No matter what sector data analytics are employed in (IT, marketing, sales etc.), its implications are leading to a new wave of Business Intelligence (BI).

Any company that uses analytics on a daily basis will understand the ability of big data to transform Customer relations and optimize management processes. In particular, big data solutions are enabling debt management software to make autonomous decisions on client handling procedures.

Until now, many debt collectors have relied on a one-size-fits-all method of debt management. Most Individual Voluntary Agreements (IVAs) and Debt Management Plans (DMPs) are managed using the same parameters, regardless of the severity of each case. In this habitual chain of events, clients who fall slightly behind on payments face the same sanctions as those who regularly avoid them. The lack of gradation often leads to increased hostility between collector and debtor, resulting in further infringements.

With the correct implementation of big data, debt management companies can create bespoke strategies for individual clients. Debt management software is reaching a level where it can successfully determine the right cause of action on a case-by-case basis, through automated analytics. In a broader sense, this has turned debt management software into a Customer Relationship Management (CRM) program.

For banks and debt collectors, these advancements in data usage have enabled them to create bespoke business solutions for everyone on their books. Traditionally, debt management has been viewed as a callous business. But, those in the field have a vital role to play in the overall health of a country’s economy.

 

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