Systems and methods for peer-to-peer secured instrument securitization

A system, comprising:

• one or more processors;
• and
• memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:
• receive an application for a secured payment instrument, wherein the application includes contact information corresponding to a set of peers associated with a user;
• train a machine learning algorithm to automatically generate peer recommendations for different peers selectable for security deposit solicitations associated with different secured payment instruments, wherein the machine learning algorithm is trained by iteratively updating different coefficients of the machine learning algorithm according to outputs generated by the machine learning algorithm through iterative processing of a dataset including sample user account information, sample contributions to security deposits and associated with a set of sample peers, and actual contributions made by the set of sample peers to the security deposits;
• process the contact information through the machine learning algorithm to generate a peer recommendation corresponding to a subset of peers selectable for solicitations of a security deposit associated with the secured payment instrument;
• monitor user interaction with an interface to detect selection of one or more peers from the subset of peers presented in the peer recommendation, wherein the selection indicates individual security deposit amounts to be requested from the one or more peers;
• transmit a set of requests for the individual security deposit amounts towards the security deposit;
• monitor peer responses to the set of requests, wherein the peer responses include peer feedback and different security deposit amounts corresponding to the security deposit;
• update the dataset according to the peer feedback and other peer feedback corresponding to different security deposit amount requests associated with other applications for different secured payment instruments;
• issue the secured payment instrument, wherein the secured payment instrument is secured by the security deposit;
• iteratively update the different coefficients of the machine learning algorithm to obtain an updated machine learning algorithm, wherein the different coefficients are iteratively updated according to new outputs generated through iterative processing of the updated dataset and of transaction data corresponding to the secured payment instrument;
• and
• process new applications for new secured payment instruments through the updated machine learning algorithm to generate new peer recommendations.

A non-transitory, computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:

• receive an application for a secured payment instrument, wherein the application includes contact information corresponding to a set of peers associated with a user;
• train a machine learning algorithm to automatically generate peer recommendations for different peers selectable for security deposit solicitations associated with different secured payment instruments, wherein the machine learning algorithm is trained by iteratively updating different coefficients of the machine learning algorithm according to outputs generated by the machine learning algorithm through iterative processing of a dataset including sample user account information, sample contributions to security deposits and associated with a set of sample peers, and actual contributions made by the set of sample peers to the security deposits;
• process the contact information through the machine learning algorithm to generate a peer recommendation corresponding to a subset of peers selectable for solicitations of a security deposit associated with the secured payment instrument;
• monitor user interaction with an interface to detect selection of one or more peers from the subset of peers presented in the peer recommendation, wherein the selection indicates individual security deposit amounts to be requested from the one or more peers;
• transmit a set of requests for the individual security deposit amounts towards the security deposit;
• monitor peer responses to the set of requests, wherein the peer responses include peer feedback and different security deposit amounts corresponding to the security deposit;
• update the dataset according to the peer feedback and other peer feedback corresponding to different security deposit amount requests associated with other applications for different secured payment instruments;
• issue the secured payment instrument, wherein the secured payment instrument is secured by the security deposit;
• iteratively update the different coefficients of the machine learning algorithm to obtain an updated machine learning algorithm, wherein the different coefficients are iteratively updated according to new outputs generated through iterative processing of the updated dataset and of transaction data corresponding to the secured payment instrument;
• and
• process new applications for new secured payment instruments through the updated machine learning algorithm to generate new peer recommendations.