WELCOME TO
THE WORLD OF AI POWERED LENDING
HALO is an analytics product with AI/ML capability, aimed at pre-qualifying leads and making automated credit decisions for banks and financial institutions.
Lending businesses can reduce the overall credit cost by improving the quality of loan disbursals. HALO can also enhance the underwriting process efficiency by reducing the time lost on bad clients, thus increasing the number of right approvals.
AI-Driven Credit Underwriting Software – HALO
HALO is driven by the Generative Adversarial Network class of machine learning algorithms.
In other words, it uses statistical data to derive deep, accurate and practical insights.
Expedite Underwriting!
WHY HALO ?
HALO offers high accuracy modelling capabilities that tweak data to provide a balanced view to lenders. As a result, HALO provides realistic insights, unlike mere social scoring approaches. The four major categories of data that HALO uses include:
Applicant Data
such as web forms or physical inputs
Collection Data
including payment dates
Credit Data
which include delinquency rates
Existing CX Data
to understand customer behaviour
DRAWBACKS OF TRADITIONAL UNDERWRITING
Why do we need to relook at traditional underwriting anyway? Well, they are saddled with a few major issues that negatively affect the end results of the process.
Traditional underwriting decisions are based on limited data points such as payment history, debt/credit ratios, credit length and so on. Limited data leads to sub-optimal decision making.
Manual processes tend to induce biases in underwriting decisions that ultimately impact market share. The result is more time, higher costs and lower accuracy.
Typical rating systems (such as FICO, CIBL etc.) tend to leave out large segments of the potential market due to the limitations of scoring methodologies. Thus, a significant number of prospective customers are generally under-served or totally un-served.
CUSTOMER TESTIMONIAL
HALO solution sets up to learn on its own, without the need for manual adjustment to the rules. Zuci’s team built this model based on lead, applicant, and consumer historical data with the ability to self-train and re-train itself based on any updated data received by the system.
Zuci Systems helped significantly improve lead rejection accuracy and lead selection accuracy within 6 months of implementation. We are confident that HALO will continue to provide us with significant improvements over time.
James C. Jacobson
President at First Financial Service Center
GET CONSUMER LENDING RIGHT WITH HALO
HALO offers multiple advantages over other systems:
