Understanding the technology sector is easy. After all, necessity is the mother of invention. While there are sporadic enterprise challenges being solved, everyday by software developers, long-standing everyday challenges are conquered by big shifts in the IT landscape.
For most enterprises, techniques to kill overheads are regularly practiced, but at times, overheads are found a necessary impediment. Before the financial crisis, consumer lending in the US was one such example. That is why it took a major shift, from legacy systems to cloud-based services, and it has proved to be one of the most successful episodes for the IT-finance community in the US.
The primary challenges involved handling the complexity of migrating to the new system. In aftermath, banks were already looking for means to get more conservative, and that meant fewer purchases. Would an IT transition be affordable?
Banks simply couldn’t afford to run their extensive networks of agents for consumer loans. Technology had to be used to reach consumers directly.
Although the IT shift was going to be a challenging one, with data adaptors, developers successfully surrounded legacy systems with the latest technologies. It meant the old systems, which were in many cases, jus a year old, did not go waste. There was ample opportunity to utilize those systems for database integration with adaptive techniques. It meant that old Excel sheets could be reused through seamless integration with the new real-time database and analytics.
Opportunity grows with adaptability in your mortgage technology software. It is important to be able to “build on” or extend your existing IT system, instead of having to replace it. You should avoid migrating important stuff to a new platform or sub-system every time a need arrives, as it increases errors. Responding is easy when your IT network is capable of maturing seamlessly.
One of the most effective developments in consumer-lending mortgage software has been cloud connectivity. Besides apps for borrowers and other bank customers, cloud connectivity allows banks to receive a loan application with the individual’s details, and map them to cloud data, which includes Facebook, credit bureaus, all the global banks’ default records, criminal records in the person’s country, etc. Underwriting, as a result, becomes a much more diligent process. Banks can validate loan applications much more justifiably and cut their risks consistently.
While banks saw the regulatory guidelines as an impediment to profits, being compliant actually meant better assessment of liabilities. Some of your old customers may still apply to borrow. If you have a replace strategy for IT, or go for an overhaul, it will be difficult to include those prospects’ history for underwriting.
Your old database is worth its weight in gold! By using a surround strategy instead, you can better assess prospective borrowers, without loopholes. Maximum permission-based data feed is by far the best way to assess a borrower’s capability to repay, and the larger your data set, the more accurate your risk index. And with all that data, underwriting simply must be automated.
Software capabilities these days include effective machine learning. It helps management intelligence to such an extent, that it equips consumer-facing personnel to respond instantaneously to individuals in spite of their diverse needs. Such an approach is best supported by an interface for customers, which connects directly to your organization and creates a seamless channel for data to arrive. At your end, you can feed that and the cloud data into your powerful analytics system and gain maximum traction for sales and marketing.