IDENTIFY
CREDITWORTHY BORROWERS
AT SCALE
IMPROVE
LEAD REJECTION AND
SELECTION ACCURACY
REDUCE
OPERATIONAL BANDWIDTH
FOR CREDIT ASSESSMENT

    IDENTIFY
    CREDITWORTHY BORROWERS
    AT SCALE
    IMPROVE
    LEAD REJECTION AND
    SELECTION ACCURACY
    REDUCE
    OPERATIONAL BANDWIDTH
    FOR CREDIT ASSESSMENT

      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.

      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

      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:

      HALO promises to be a game-changer for the underwriting process.

      0%
      Increase in creditworthy borrowers
      0%
      Reduction in losses
      0%
      Improvement in overall underwriting efficiency

      GET CREDITWORTHY BORROWERS TODAY

      HALO’s milestone-based pricing model translates into a 40% cost advantage as compared to competitors.
      Find out how HALO can help your organization improve efficiency!

        WHY HALO DELIVERS BETTER RESULTS

        HALO uses a machine-learning-based scoring model, which helps eliminate bad leads and approve good leads, by analyzing past data. Thus it helps lenders fund more of the right merchants and less of the wrong ones! It performs powerful Big Data analyses of credit reports, bank statements, and other relevant data to build a scorecard — that self-trains and improves itself continuously!

        Expand your market share, reach more customers faster, minimize errors, and cut your expenses.
        Find out how HALO can transform your underwriting process!