AI Solution Selection for Robotic Tasks Using Brain Activity Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Lending transactions face challenges such as opacity and asymmetry of information, moral hazard, complexity in application and negotiation processes, burdensome regulatory regimes, and difficulties in determining collateral value and financial health of entities.
Innovation Solution
A lending transaction enablement platform incorporating data-integrated microservices, including data collection and monitoring, blockchain, and smart contract services, with Internet of Things (IoT) and crowdsourcing systems for real-time data monitoring and adaptive intelligence to automate loan processes and manage collateral and debt.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional lending processes are used, then manual negotiation and assessment can be performed, but information asymmetry and opacity persist
Solution Approach 1:
The patent replaces manual mechanical assessment processes with automated AI/ML systems that objectively evaluate borrower creditworthiness, collateral value, and loan performance. This substitution eliminates information asymmetry by using standardized data-driven models rather than subjective human judgment, while reducing dependency on manual negotiation and processing.
2Reliability
If complex regulatory compliance procedures are implemented, then regulatory requirements can be met, but process complexity and time consumption increase
Solution Approach 1:
The patent incorporates regulatory compliance checks and risk assessments into the initial loan application and underwriting process. By performing compliance verification upfront rather than as separate subsequent steps, the system ensures regulatory requirements are met while reducing overall process complexity and time consumption.
3Adaptability or versatility
If dynamic loan term adjustments are implemented, then loan flexibility and adaptability improve, but system complexity increases
Solution Approach 1:
The patent implements dynamic loan terms through AI-driven systems that automatically adjust interest rates, repayment schedules, and other loan parameters based on real-time data about borrower performance, market conditions, and collateral value. This dynamic adjustment mechanism provides loan flexibility while managing system complexity through automated decision-making algorithms rather than manual renegotiation.
4Measurement precision
If manual collateral valuation and monitoring are performed, then detailed assessment can be conducted, but time consumption and cost increase
Solution Approach 1:
The patent replaces manual collateral valuation and monitoring with automated systems using IoT sensors, satellite imagery, and AI/ML algorithms to continuously assess collateral value and condition. This substitution maintains measurement precision through objective data-driven valuation while dramatically reducing the time and cost associated with manual assessment processes.
Data Source
AI summary
A method for selecting an AI solution for an automated robotic process including receiving at least one functional media including information indicative of brain activity by a human engaged in a task of interest, analyzing the functional media, identifying an activity level in at least one brain region, identifying a brain region parameter and an activity parameter; identifying an action parameter based in part on the brain region parameter or the activity parameter; and selecting a component of the AI solution in part on the brain region parameter, the activity parameter, or the action parameter.