Benefits business can achieve using automatic scoring

Introduction:

Underwriting modernization is a top-priority step for credit institutions that want to remain competitive and efficient. In this post we will share some benefits for the companies to stick to automated underwriting solutions:

1. Consistent decision-making process

Manual underwriting is inconsistent, likely to include human mistakes, inaccuracies and confusions about individual underwriting decisions. Having cycle of automated scoring eliminates time-consuming manual entries of data, reduces the time of the risk assessment and ensures up-to-date and accurate decision-making process. Performance of decisions becomes easily comparable over time and model adjustments can be done much quickly.

2. Costs and time saving

The analysts’ time spent for collecting, entering, organizing, cleaning and searching for data can be entirely or partially eliminated with system that automatically uploads and categorizes information. As a result, automation leads to better and more effective resource allocation as well as better service for the customers and growth for the organization.

3. Better issues tracking and improved workflow

Automated risk assessment allows to track problems and misclassifications easier as well as faster determine their root causes. As automatization decreases the points of manual failure, fields in electronic application can’t be left blank and handwriting is not possible to be misread.

With robust and modern automated underwriting analysts are able to focus on more important and complex tasks, such as the workflow improvement, rather than spending time for boring data preparation. Also, if the organization has an automated decision engine it is able to adapt faster to the changes in legislation by just changing some logic in the engine’s formula, instead of training the staff how the new law will influence manual decision making process.

4. Easier testing of various underwriting scenarios

Automated decision engine gives an opportunity to send different scenarios for loans. For example, one path can reject bunch of loans having some particular suspicious criteria, another will, within seconds, approve the least risky applications, without wasting time of an analyst for any checks, third will create a flag that only one customer’s characteristic needs to be double-checked before making the decision of granting the credit. Within time the performance of the loans that came through different paths can be compared or the path itself can be easily adjusted if improvement is needed. Decisions are becoming almost instant allowing also for quicker communication with the customer.

Customer, who already repaid the granted credit without any delays can have simplified auto approval process. Automatically calculated credit score can also serve as a hint to the credit officer: the higher it is the less time is needed for additional manual checks.