About

FairBorrow™.Ai

Artificial Intelligence for a good cause

FairBorrow.Ai utilizes AI for unbiased lending decisions, leveraging public data like HMDA to reduce regulatory issues and enhance financial integrity.

Leverage the latest GenerativeAI features to gain critical insights and enhance the consistency of your decision making process.

Key Users

Testimonial

What they say

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We have implemented using publicly available HMDA data

Underwriter for Mortgage Lending

Our proprietary, AI-based process enables decision- makers to test their decisions for consistency within their company, region, by product or any other accepted underwriting factor. FairBorrow™.Ai leverages its proprietary AI-based Data Management processes and produces insightful summaries automatically.

FairBorrow™.Ai is not a decisioning model. We do not recommend reversing or changing any loan decisions made on the basis of consistency checks. The purpose of FairBorrow™.Ai is to help identify improvements in the decision-making process itself by understanding the causes of decision inconsistencies. The outcome of an inconsistency check does not imply a right or wrong decision, or any other wrongdoing.

FairBorrow™.Ai does not impose any of its own restrictions or biases in this process and leverages various key risk indictors from within the decision data set to arrive at the insightful conclusion whether the specific decision(s) being checked are consistent or not.

Decision-makers will follow their institution’s policies and procedures to make their decisions, and then check the consistency of their decisions. Such checks inform the decision-makers about opportunities in streamlining their processes.

Our proprietary AI-based process enables decision-makers to test their decisions for consistency within their company, region, by product or any other accepted underwriting factor. FairBorrow™.Ai leverages its proprietary AI-based Data Management processes and produces insightful summaries automatically.

FairBorrow™.Ai is not a decisioning model. We do not recommend reversing or changing any loan decisions made on the basis of consistency checks. The purpose of FairBorrow™.Ai is to help identify improvements in the decision-making process itself by understanding the causes of decision inconsistencies. The outcome of an inconsistency check does not imply a right or wrong decision, or any other wrongdoing.

FairBorrow™.Ai does not impose any of its own restrictions or biases in this process and leverages various key risk indicators from within the decision data set to arrive at the insightful conclusion whether the specific decision(s) being checked are consistent or not.

Decision-makers will follow their institution’s policies and procedures to make their decisions, and then check the consistency of their decisions. Such checks inform the decision-makers about opportunities in streamlining their processes.

We have implemented using publicly available HMDA data

Risk Manager

A risk manager could be a quality assurance professional, underwriting team manager, or compliance professional including a Fair Lending compliance officer). A risk manager would normally review past decisions for inconsistencies and anomalies to identify potential enhancements in the decisioning process.

In identifying anomalies, FairBorrow™.Ai leverages disparity in decision rates as one of the key risk indicators. Use of Data Driven Artificial Intelligence, with no external assumptions and bias imposed allows a risk manager to quickly identify groups of loans with highest decision anomaly, based on product, geography and any of the factors used in the decisioning process. The presence of anomalies in past decisions does not necessarily indicate any wrong decisions and any other wrongdoing.
A risk manager can leverage such lists of anomalies and AI driven comparative loans to determine what process enhancement would create a more consistent decision process. Increased consistency in decisions

Higher levels of consistency in decision making reduces any potential or perceived bias and produces results that are more closely aligned with business objectives.

A risk manager could be a quality assurance professional, underwriting team manager, or compliance professional, including a Fair Lending  compliance officer). A risk manager would normally review past decisions for inconsistencies and anomalies to identify potential enhancements in the decisioning process.

In identifying anomalies, FairBorrow™.Ai leverages the disparity in decision rates as one of the key risk indicators. Use of Data-Driven Artificial Intelligence (AI), with no external assumptions and bias imposed, allows a risk manager to quickly identify groups of loans with the highest decision anomaly, based on product, geography, and any of the factors used in the decision process. (Note, however, that the presence of anomalies in past decisions does not necessarily indicate any wrong decisions and any other wrongdoing.)

A risk manager can leverage such lists of anomalies and AI-driven comparative loans to determine what process enhancement would create a more consistent decision process.

Higher levels of consistency in decision-making reduce any potential or perceived bias and produce results that are more closely aligned with business objectives.

We have implemented using publicly available HMDA data

Researcher

A researcher could be anyone who would like to gain deep AI driven insights into data, which contains charts, summary level information and automatically produced narratives. The researcher neither needs to fully understand the intricacies of the data they are researching, nor do they need to be concerned with Data Science.

Our proprietary Data Management Processes allow simple chat interface, to guide the researcher into the best choices possible for these deep insights. Chat interactions are kept strictly confidential and rea used for improving the experience.

FairBorrow™.Ai produces deep insights into data and does not impose its own opinions or judgment. We do not recommend for or against any lender or Financial Institution, and the presence of any clickable links in our reports that take you to a Financial Institution’s web site is not a sign of our endorsement. In some cases, we may collect a referral compensation from such a Financial Institution if you do click on their link. Please see our Privacy policy for further details.

A researcher could be anyone who would like to gain deep AI-driven insights into data, which contains charts, summary level information, and automatically produced narratives. The researcher does not need to fully understand the intricacies of the data they are researching, nor do they need to be concerned with Data Science.

Our proprietary Data Management Processes allow simple chat interface, which guide the researcher into the best choices possible for these deep insights. Chat interactions are kept strictly confidential and are used for improving the experience.

We have implemented using publicly available HMDA data

Potential Mortgage Borrower

FairBorrow™.Ai is neither a mortgage provider nor a financial institution of any kind. Any information collected by us does not constitute a mortgage application, just as any responses from the FairBorrow™.Ai system to your queries do not guarantee a loan approval, denial, or any specific outcomes such as interest rates.

FairBorrow™.Ai uses its proprietary Data Management Processes and HMDA data to produce deep and easy-to-understand insights for potential borrowers so that they can make informed decisions.

We do not recommend or critique any lender or financial institution. The presence of any clickable links in our reports, which may take you to a financial institution’s or other lender’s web site, is not an endorsement of that financial institution or other lender. In some cases, we may collect referral compensation from such a financial institution if you do click on their link. Please see our Privacy policy for further details.