Arva Platform

Update a case

To update a case, you must first get the ID of the customer the case belongs to. You will have received this ID when you created the case.

You can then update the case by sending a POST request to the following endpoint:

https://platform.arva.ai/api/v0/customer/update

In the request body, you can provide a patch for the user-provided information, websites and file uploads to update the case. The fields you provide here will depend on which checks you have enabled for the agent. Each time you provide an update, the case will be re-evaluated and an outcome returned.

curl -X POST "https://platform.arva.ai/api/v0/customer/update" \
-H "Authorization: Bearer <API_KEY>" \
-H "Content-Type: multipart/form-data" \
-F "customerId=<CUSTOMER_ID>" \
 #  The fields you provide here will depend on which checks you have enabled for the agent
-F 'userInfoPatch={
    "dba": <string>, # optional
    "fkas": <string[]>, # optional
    "natureOfBusiness": <string>, # optional
    "operatingAddress": <string>, # optional
    "tin": <string>, # optional
    "addedEntities": Entity[] # optional
    "editedEntities": Partial<Entity>[] # optional, must include the ID field
    "removedEntityIds": <string[]> # optional, list of entity IDs to remove
    # Optional, pass this to run only a subset of the enabled checks e.g. ['INCORPORATION']
    # This will skip the overall verdict and RFI but will return the results for those checks
    "checks": <CheckType[]>,
}' \
 # E.g. Company website, LinkedIn, etc.
-F "websites=<ARRAY_OF_USER_WEBSITE_URLS>" \
 # E.g. Certificate of Incorporation, CP-575 letter, etc.
-F "file=@<FILE_1_PATH>" \
-F "file=@<FILE_2_PATH>"

npm i @arva-ai/sdk

import { Arva } from '@arva-ai/sdk'

const client = new Arva(
  <string> // Your API key
)

const customer = await client.customers.update({
  id: <string>, // The ID of the customer
  userInfoPatch: {
    // The fields you provide here will depend on which checks you have enabled for the agent
    dba: <string> | undefined,
    fkas: <string[]> | undefined,
    natureOfBusiness: <string> | undefined,
    operatingAddress: <string> | undefined,
    tin: <string> | undefined,
    addedEntities: EntityWithScreeningResults[] | undefined,
    editedEntities: Partial<Entity>[] | undefined, // must include the ID field
    removedEntityIds: <string[]> | undefined, // list of entity IDs to remove
  },
  websites: <string[]>,
  files: <File[]>,
  // Optional, pass this to run only a subset of the enabled checks e.g. ['INCORPORATION']
  // This will skip the overall verdict and RFI but will return the results for those checks
  checks: <CheckType[]> | undefined
})

import json
import requests
import os
from requests_toolbelt import MultipartEncoder

user_info_patch = {
  # The fields you provide here will depend on which checks you have enabled for the agent
  'dba': <string> | None,
  'fkas': <string[]> | None,
  'natureOfBusiness': <string> | None,
  'operatingAddress': <string> | None,
  'tin': <string> | None,
  'addedEntities': Entity[] | None,
  'editedEntities': Partial<Entity>[] | None, # must include the ID field
  'removedEntityIds': <string[]> | None, # list of entity IDs to remove
}

websites = <string[]>

file_paths = <string[]>

files = [open(fp, 'rb') for fp in file_paths]
file_tuples = [('file', (os.path.basename(f.name), f, 'application/pdf')) for f in files]

# Optional, pass this to run only a subset of the enabled checks, e.g. ['INCORPORATION']
# This will skip the overall verdict and RFI but will return the results for those checks
checks = ['INCORPORATION']

mp_encoder = MultipartEncoder(
  fields=[
    ('customerId', customerId),
    ('user_info_patch', json.dumps(user_info_patch)),
    ('websites', json.dumps(websites)),
    ('checks', json.dumps(checks))
  ] + file_tuples
)

verdict = requests.post(
  'https://platform.arva.ai/api/v0/customer/update',
  headers={
    'Authorization': 'Bearer ' + apiKey,
    'Content-Type': mp_encoder.content_type
  },
  data=mp_encoder,
)

pip install arva-sdk

from arva import Arva

client = Arva(
  api_key=<string>
)

user_info_patch = {
  # The fields you provide here will depend on which checks you have enabled for the agent
  'dba': <string>,
  'fkas': <string[]> | None,
  'natureOfBusiness': <string> | None,
  'operatingAddress': <string> | None,
  'tin': <string> | None,
  'addedEntities': Entity[] | None, # optional
  'editedEntities': Partial<Entity>[] | None, # optional, must include the ID field
  'removedEntityIds': <string[]> | None, # list of entity IDs to remove
}

websites = <string[]>

file_paths = <string[]>

files = [open(fp, 'rb') for fp in file_paths]

# Optional, pass this to run only a subset of the enabled checks, e.g. ['INCORPORATION']
# This will skip the overall verdict and RFI but will return the results for those checks
checks = ['INCORPORATION']

verdict = client.customers.update(
  id=<string>
  user_info_patch=user_info_patch,
  websites=websites,
  files=files,
  checks=checks
)

If the request is successful, the response from the API will be an object with the following schema:

{
  id: string // customer ID
  name: string
  state: string | undefined
  createdAt: Date
  verdict: 'ACCEPT' | 'REJECT' | 'REQUEST_INFORMATION' | 'PENDING'
  riskLevel: 'HIGH' | 'MEDIUM' | 'LOW' | undefined
  periodicReviewYears: number | undefined // undefined unless the verdict is ACCEPT
  rfi: string | undefined // undefined unless the verdict is REQUEST_INFORMATION
  requiresManualReview: boolean
  checks: {
    type: string
    verdict: 'ACCEPT' | 'REJECT' | 'REQUEST_INFORMATION' | 'PENDING'
    riskLevel: 'HIGH' | 'MEDIUM' | 'LOW' | undefined // undefined unless the verdict is ACCEPT
    reason: string
    periodicReviewYears: number | undefined // undefined unless the verdict is ACCEPT
    requiresManualReview: boolean
    proofs: Proof[]
    // Some checks return additional details e.g. registry results
    details: Record<string, unknown> | undefined
  }[]
  entities: EntityWithScreeningResults[]
}

Where:

type Proof = {
  id: string
  type: 'DOCUMENT' | 'WEBSITE'
  inferredType: string
  name: string
  url: string
}

type IndividualEntity = {
  type: 'individual'
  metadata: {
    firstName: string
    middleNames: string | undefined
    lastName: string
    dateOfBirth: {
      day: number | undefined
      month: number | undefined
      year: number
    } | undefined
    address: string | undefined
    country: string | undefined
  }
}

type CorporateOrTrustEntity = {
  type: 'corporate' | 'trust'
  metadata: {
    name: string
    registrationJurisdiction: string | undefined
    registrationNumber: string | undefined
    address: string | undefined
  }
  relationships: Relationship[]
}

type Entity = IndividualEntity | CorporateOrTrustEntity

type Relationship = {
  type: 'director' | 'officer' | 'psc'
  positions: string[]
} | {
  type: 'owner'
  ownershipPercentage: number
  entityId?: string // ID of the owned entity, if not the customer entity
} | {
  type: 'additional'
  reason: string
}


type EntityWithScreeningResults = Entity & {
  screeningHits: ScreeningResult[]
}

type ScreeningResult = {
  type: 'adverse_media' | 'sanctions_screening' | 'peps_screening' | 'other_screening'
  verdict: 'LOW' | 'MEDIUM' | 'HIGH' | 'REJECT' | 'DISCOUNTED' | 'REVIEW'
  reason: string
  source: string // e.g. 'webSearch', 'complyAdvantage'
  fromMonitoring: boolean
  externalIds: {
    // varies by provider
  }
  matchingName: string
  // Additional fields vary by type and provider
  names: string[] | undefined
  url: string | undefined
  date: string | undefined
  lists: {
    name: string
    identifier: string
    url: string
    countryCodes: string[]
    dateAdded: string
  }[] | undefined
  groupId: string | undefined // Adverse media hits that share the same groupId are likely to be the same event
}

Next, see how you can submit a manual review.