Right-Time Analytics in Mortgage Lending

The residential lending market has fallen from its peak and has settled at a more realistic area where it is most likely to stabilize in the $1 to $2 trillion mark for the rest of the decade.  In the wake of the 2007 crisis, student loans have increased. The Millennials have piled up substantial debts and prefer to rent than buy. House prices have increased in major cities making it even more difficult to buy. Meanwhile, the cost to originate a loan is on the rise. And these are only some of the countless micro and macroeconomic trends currently impacting the mortgage lending sector.

Alongside, technology innovations for the mortgage sector have made path-breaking strides to the extent where legacy applications are being replaced by faster, customer-friendly applications.  While many companies are focusing on replacing or embracing their existing legacy systems, some of them are also diving deeper to get the best out of technology. These companies are using analytics to provide strategy, growth and revenue-related statistics. However, more often than not, many of these companies invest in analytics mostly to deliver reports to understand past behaviour and use that knowledge to improve processes and bridge existing gaps. The reports are usually sent to decision-makers on a periodic basis or delivered on demand. In most cases, the data is maybe a day old and is refreshed on a nightly basis. These reports serve the limited needs of the company to support its current operations. But to improve efficiency and reduce operational costs, it is essential to provide data at the time when it’s needed the most, not before and not after, this is called ‘Right-Time Business Analytics’.

What is Right-Time Analytics?

Information on important events which impact the business, have to reach decision makers as fast as possible. For example, if the employee attendance system detected an unusual sign-off for a loan officer who had to submit disclosures to customers on a particular day and if those disclosures have not been reassigned, then alerts need to be fired immediately to the second-in-command or the reporting manager, citing the number of violations that are about to happen. Such alerts, unfortunately, cannot be fired using traditional business intelligence methods where data is loaded into a data warehouse on a nightly basis.

For each event like this, the gains may not be as visible to the human eye as it would be when the total number of events is calculated. Though organizations spend a lot of time measuring the average cost per loan, pipeline velocity and cycle time, very few lenders measure and assess the number of hours spent on closing a loan.  This is where Right-Time Analysis comes in! Lenders who adapt to right-time business analytics will see natural improvements to operations beyond what is planned strategically.

Another important real-time metric that would create a sense of urgency amongst the workforce is a bullet chart that clearly shows the real-time performance of the loans they are working on as compared to the set target and the company average. These are great tools that a company should consider implementing to improve turnaround times in addition to the other regular operational improvements.

Social media is another area which benefits from analytics. Analysing user behaviour on websites is critical to detect user grievances and react to the same towards controlling the damage before it becomes viral.

Implementing right time analytics along with effective activity monitoring helps identify several areas where operational improvements can be implemented, thus reducing the cost of originating a loan. In a stagnating market, mortgage lenders who recognize the value of Right-Time Analysis will stand to benefit in the short and long term.

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