White Swan’s digital platform and expert advisors makes it easy to get your clients any type of life insurance solution with the highest best-interest standards and most convenient experience.
Imports client data for pre-filling applications to enrich the user experience. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Retrieves information about clients referred from the user's White Swan account. See the documentation
Creates a new comprehensive quote request based on the information provided and generates the final quotation without further data requirements. See the documentation
The White Swan API provides predictive analytics for mitigating risks in financial portfolios using artificial intelligence. By leveraging the White Swan API in Pipedream, you can automate the process of gathering insights, monitoring market conditions, and integrating advanced risk analysis into your existing financial systems. With Pipedream's serverless platform, you can construct workflows to react in real-time to data from White Swan, send alerts, and even automate trades or adjustments based on risk thresholds or predictive signals.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
white_swan: {
type: "app",
app: "white_swan",
}
},
async run({steps, $}) {
return await axios($, {
method: "post",
url: `https://app.whiteswan.io/api/1.1/wf/plan_requests`,
headers: {
Authorization: `Bearer ${this.white_swan.$auth.api_key}`,
"Accept": `application/json`,
"Content-Type": `application/json`,
},
})
},
})
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt
file or running pip
.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}