e4eebb13-21c2-447b-a8d9-c086de2c569d.png

Director, Functional Architect

a6e5b969-be6e-4756-ae53-47d3cb899ca4.png

Despite emergence of self service channels, a large proportion of the clients (institutional and retail) continue to use Emails as a primary channel for communication with the bank. Most of these communications are related to clarify issues/ queries on their account, account servicing requests or complaints, issues with payments. 

The bank’s Customer Servicing and Fulfillment support teams processes the email/ free text based request, create a service request record in system and addresses the actual request in respective banking system, resolve the request, reply back to client over Email and closes the request in system. All this takes huge time of the bank’s operations team to resolve individual service request end-to-end and also causes great dissatisfaction to end client due to long service cycle led by multiple manual interventions. Also, such requests are very recurring and require huge task force. A typical large bank has 100s of operations team members for classifying, raising tickets and routing the tasks to appropriate teams in bank for each of the product and service line.

UiPath's Customer Service Request Classification Accelerator extracts narratives from customer emails and auto classifies each of the customer email into 3 categories - Banking Product, Sub Product and Issue Type using Evolution AI based NLP models. Finally, the accelerator auto creates a new case for each email in Salesforce Case Management Application.

**Features:**

*   Pre trained classification models based on real world customer emails
*   Pre configured integration with Salesforce Case Management
*   Option to reconfigure with bank's existing servicing platforms

**NLP/NLC Models powered by** [**EvolutionAI**](https://evolution.ai)

**Developed by:**  , 

Streamline your Customer Service function through AI powered auto classification and routing of customer requests

**Description**

Wholesale Banking underwriting teams require information extraction from customer documents for small and medium business loans. These financials are submitted in varying forms. Typically, these documents are scanned, put through OCR and then typically manually extracted leading to longer timelines for loan approval. Apart from operational efficiency, automation also allows banks to amplify their credit analysis teams, i.e. ability to approve and close more loans with same levels of staff. This accelerator assists in automation of process steps within the Financial Spreading process as part of overall lending lifecycle. The automation journey begins with UiPath Robot picking up each of the balance sheet documents submitted by a prospect. Thereafter, UiPath Robot invokes Evolution AI API in order to extract key financials from each of these balance sheets. Evolution AI API returns the set of extracted fields back to UiPath Robot. Thereafter, UiPath Robot uses Company's registration number and extracts additional information about the company from 3rd party website (UK Company House in this case). Once all the required information has been extracted, UiPath Robot prepares a pre formatted spreadsheet for Credit Analysis.

Amplify your credit analysis teams and close more business loans using auto extraction from Financial Statements

**Beneficial Ownership Extraction:** This process is an integral part of the Anti-Money Laundering or similar regulatory Risk Assessment and all Financial Services firms must comply with this in order to maintain licenses. During customer on-boarding process for a client, the KYC analysts must collect and update client profile including beneficial ownership information to correctly assess client risk. The analysts must ensure that all necessary information required to complete the KYC record is available and accurate. After on-boarding a client, the KYC Profile will be monitored for substantive changes to the original information captured. And finally, they must ensure that that the risk assessment of the customer has not materially changed.

In most banks, ascertaining Beneficial Ownership is time consuming and prone to errors largely due to unstructured nature of the documents that serve as single source of truth. Some of these documents include Proxy Statements, Form 13F and 13D filed with SEC. Top 20 US banks spend close to USD 50 MM per annum on KYC alone and UBO is a significant overhead in this lifecycle.

UiPath KYC (Ultimate Beneficial Ownership) Accelerator extracts ultimate beneficial owners from SEC Def 14A (Proxy documents), runs these list of owners through sanctions screening and politically exposed person (PEP) checks.

Accelerator extracts ultimate beneficial owners from SEC Def 14A (Proxy documents), runs these list of owners through sanctions screening and politically exposed person (PEP) checks.

About me