DECISION ENGINE
Examples of the present disclosure describe systems and methods related to a decision engine. In an example, proposals, work orders, invoices, and assets may be managed by the decision engine, such that recommendations may be generated and automatic actions may be performed on behalf of a subscriber. For example, a model may be trained based on historical data, which may be used to generate recommendations as to whether proposal should be approved or rejected. In examples, the proposal may be presented along with additional information, such as asset information or information relating to similar proposals, thereby enabling improved decision making. In other examples, invoice approval rules may be generated based on the historical information applied to invoices as they are received from contractors, which reduces the amount of manual effort involved in approving and rejecting invoices.
1 . A system comprising:
at least one processor; and
memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations, the set of operations comprising:
receiving a proposal associated with a subscriber, wherein the proposal is associated with an asset;
accessing a model, wherein the model is trained based at least in part on historical data associated with the subscriber;
generating, using the model, a proposal recommendation for the received proposal;
generating a display of the proposal recommendation comprising asset information associated with the asset and information associated with one or more similar proposals to the received proposal, wherein the display further comprises a visual indication of a strength associated with the proposal recommendation and an actions dropdown usable to select an action to perform for the proposal;
receiving, from the computing device, an indication to approve or reject the proposal based at least in part on the generated display; and
generating a response to the proposal based on the received indication.
2 . The system of claim 1 , wherein the set of operations further comprises:
determining whether the indication is contrary to the generated proposal recommendation;
based on determining that the indication contrary to the generated proposal recommendation, retraining the model based at least in part on the received indication.
3 . The system of claim 1 , wherein the model is trained based at least in part on historical data associated with one or more other subscribers, and wherein the one or more other subscribers are in a similar industry as the subscriber.
4 . The system of claim 1 , wherein the one or more similar proposals are identified based on a problem code associated with the received proposal.
5 . The system of claim 2 , wherein retraining the model comprises:
determining a first subset of the historical data for training the model and a second subset of the historical data for model verification;
retraining the model using the first subset of the historical data; and
verifying the model using the second subset of the historical data.
6 . The system of claim 1 , wherein the display of the proposal recommendation comprises a graphical representation of the proposal recommendation.
7 . The system of claim 1 , wherein the proposal is associated with a contractor; and wherein the display of the proposal recommendation comprises information associated with the contractor.
8 . A system comprising:
at least one processor; and
memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations, the set of operations comprising:
receiving an invoice associated with a subscriber;
generating a display of the received invoice;
providing the generated display to a computing device of the subscriber;
receiving an indication from the computing device to approve or reject the received invoice;
determining, based on the indication and historical data associated with the subscriber, whether an invoice approval rule may be generated;
when it is determined that an invoice approval rule may be generated, generating an invoice approval rule based on the indication and the historical data associated with the subscriber; and
storing the generated invoice approval rule.
9 . The system of claim 8 , wherein the set of operations further comprises:
receiving a second invoice associated with the subscriber;
determining that the generated invoice approval rule applies to the received second invoice; and
automatically processing the second invoice based on the generated invoice approval rule.
10 . The system of claim 9 , wherein automatically processing the second invoice comprises one of:
automatically approving the second invoice; and
automatically rejecting the second invoice.
11 . The system of claim 8 , wherein the invoice approval rule is generated based on receiving a user indication to generate the invoice approval rule.
12 . The system of claim 8 , wherein the generated display comprises a display of additional information regarding similar historical invoices to the received invoice.
13 . The system of claim 12 , wherein the similar historical invoices are identified based on a problem code associated with the received invoice.
14 . A system comprising:
at least one processor; and
memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations, the set of operations comprising:
receiving a proposal associated with a subscriber;
accessing a model, wherein the model is trained based at least in part on historical data associated with the subscriber;
generating, using the model, a proposal recommendation for the received proposal;
generating a display of the proposal recommendation;
receiving, from the computing device, an indication to approve or reject the proposal based at least in part on the generated display; and
generating a response to the proposal based on the received indication.
15 . The system of claim 14 , wherein the set of operations further comprises:
determining whether the indication is contrary to the generated proposal recommendation;
based on determining that the indication contrary to the generated proposal recommendation, retraining the model based at least in part on the received indication.
16 . The system of claim 14 , wherein the model is trained based at least in part on historical data associated with one or more other subscribers, and wherein the one or more other subscribers are in a similar industry as the subscriber.
17 . The system of claim 14 , wherein the proposal is associated with an asset of the subscriber.
18 . The system of claim 17 , wherein generating the display further comprises incorporating information associated with the asset.
19 . The system of claim 14 , wherein generating the display further comprises incorporating information associated with one or more similar proposals to the proposal.
20 . The system of claim 19 , wherein the one or more similar proposals are identified based on a problem code associated with the proposal.