RPA in banks

Software robotization
for financial sector

6 reasons to use RPA in banks

Vast majority of time is spent on information gathering and processing
Сотрудник за работой
Most tasks have regular repititive type
Business-processes are standardized and regulated
There is a number of separate and «legacy» systems
Человеческий фактор
Customer satisfaction critically depends
on «human factor»
From executioner perspective work is routine, monotonous and repetitive without any creativity
Incoming request processing, formation of html-templates, filling them out with core data, preparation of reply with neccessary documents attached
Automated replies to government regarding clients

What RPA can do in financial sector

Acquisition of salary registers from banking software and requisite verification, in case of mistakes - warns responsible manager about the neccessity of salary register correction, otherwise approves payment
Communication with client and support in different channels during all stages of applicaitions, document recognition (with OCR), correct set of documents verification, transition of documents to responsible manager, client notification regarding processes stage
Processing of salary registers
Document processing automation

and what should not be done manually

Extraction of required client information, creation of cards/forms in software, client onboarding, other actions required to open a bank account or produce a card
Automated bank account opening and card production

Opening of the account/profile/dossier in banking software, acquisition of information from client documents (with OCR), filling out the profile fields, archive document upload
Opening and filling out an account / profile / client dossier
Reminders regarding neccessity of document provision, acquisition, verification, complete set and correctes checkup, transition of document to the responsible manager
Collecting documents to monitor the financial condition of borrower

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Benefits of using RPA in banks

Skyrocket efficiency and speed due to business process optimization
Manual labour reduction
Number of mistakes reduction
Qualified staff has more time to do the job with more added value
Digital transformation without long and costly IT-integrations
Big Data analysis and Machine Learning capabilities in order to take rule-based decisions
Повышение производительности
Сокращение ручного труда
Уменьшение ошибок
Счастливые сотрудники

Our cases in financial sector

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