1
P&L reporting
P&L reporting, which involves data collection from accounting systems and financial records, account
reconciliation, and transaction classification, is susceptible to inaccuracies and errors when done
manually. Solutions with agentic automation and RPA capabilities can help finance teams streamline the
creation of P&L reports by collecting data on sales, cost of products sold, operating expenses, interest
rates, and taxes from the general ledger, cross-checking it for completeness and accuracy, identifying
discrepancies, and classifying all the transactions. They can also be configured to enter this data into
templates and generate P&L reports, as well as distribute the reports among stakeholders on a scheduled
basis.
2
Investment & asset management
Wealth management companies and other financial institutions can use software robots and agents powered by
artificial intelligence to streamline a wide range of investment management activities. For instance, such
process automation solutions can extract data from broker emails or handwritten or non-standard documents
in the form of PDFs and images when equipped with optical character recognition capabilities, structuring
the retrieved information and sending it to the investment management system to update client portfolios
or create investment reports.
Additionally, agentic and robotic process automation solutions can aggregate market and portfolio
performance data from disparate external and internal sources and upload it to financial BI and predictive analytics solutions to help investment
teams measure asset profitability and return on investment, assess the effectiveness of clients’ investment
strategies, and detect emerging investment risks. They can also be set up to distribute portfolio performance
data and reports via emails to promptly inform clients and investors about any updates.
3
Reconciliation
Bank reconciliation involves matching cash balances and transactions in the company’s books with cash
balances and transactions from bank statements. When done manually, reconciling a bank account is prone to
human errors, which reduces process efficiency and leads to costly mistakes.
Integrated with accounting software, robotic or AI process automation solutions can merge and standardize
data from different accounts and bank statements and cross-check them against internal ledger entries
based on criteria such as date, amount, reference number, and account code. Then, they can search for any
inconsistencies and variances between payment details and bank records, apply established rules to handle
well-known exceptions, or route exceptions and requests for record validation to human specialists. Upon
verifying final balances match and obtaining the required approvals from supervisors, bots can compile
financial statements, update reconciliation logs, and fill out supporting documentation for audit and
compliance purposes.
4
Accounts payable management
Agentic and robotic automation can prove highly useful in helping organizations keep track of their
financial obligations and ensure all debts are paid off on time. Financial service providers can use these
solutions to extract data from invoices of different formats, categorize the invoices, and perform their
two-way and three-way matching. Bots and agents can also normalize invoice data and route it to the
financial software or approvers, as well as schedule payments and track invoice processing statuses.
5
Accounts receivable management
The accounts receivable process involves a lot of manual activities to make sure that money owed for goods
or services provided is collected in time. Companies can use RPA software and agentic automation solutions
to generate and distribute invoices, match them to purchase orders, track and process customer payments,
send follow-ups and payment reminders to clients, as well as create routine AR reports, reducing the time
required to collect payments and increasing financial data accuracy. Apart from invoice generation and
payment matching, AI-powered agents can also identify customers who are at risk of non-payment based on
invoice aging data, as well as consolidate invoice data and send it to financial analytics solutions for further examination of a company’s cash flow.
6
Tax reporting
Tax reporting requires the highest level of precision to ensure smooth audits and helps businesses avoid
legal penalties and fines. Process automation bots and agents can be used to streamline most of the
routine tax accounting and financial reporting activities.
For instance, they can automate data collection from tax and finance systems, interpret, classify, and
route tax notices from various jurisdictions, classify transactions for taxation, and compare and reformat
trial balances to facilitate tax reporting, reducing manual work and helping companies maintain legal
compliance and financial stability. In addition, these solutions can be useful for processing tax
regulation changes, alerting relevant stakeholders about the legal updates and whether they can impact the
company’s tax position, and scheduling tax planning meetings with stakeholders.
7
Compliance reporting
To limit the risks of fines and reputational damage caused by regulatory non-compliance, banks and
investment companies can employ RPA bots and agentic automation solutions for various compliance-related
tasks. One of them is monitoring regulatory changes from pre-established sources and alerting stakeholders
to have the company promptly introduce required changes in their workflows. These solutions can also
consolidate financial transactions and customer information from different systems or documents and
compile compliance reports for stakeholders, such as the company’s board of directors or a government
agency.
Agentic and RPA automation solutions can also assist employees with know-your-customer (KYC) and
anti-money laundering (AML) checks, handling and processing data to verify the identity of new customers
faster and more accurately.
8
Fraud detection
By monitoring transaction streams and system logs of the actions performed by employees in real time,
process automation solutions can detect suspicious events quickly and accurately, becoming invaluable for
preventing fraud. RPA bots and AI-powered agents can also help detect customer fraud by cross-checking
payment details against government and corporate fraud databases, identifying unusual payment patterns,
and spotting inconsistencies between payment details and bank records.
Additionally, these software solutions can consolidate evidence of fraud, create case summaries, and
trigger alerts about possible anomalies. In known fraud cases, automation solutions can block the
transaction or ask clients for proof of their legitimacy.
9
Customer onboarding
Because of the process complexity, financial services organizations traditionally spend significant time
and effort onboarding new clients. With the help of RPA, companies can automate mundane tasks such as
verifying customer data accuracy, setting up accounts, and performing background checks. Agentic
automation solutions, in turn, can employ OCR and other technologies to extract data from unstructured
documents sent by clients, as well as request missing details from them, provide financial plan
recommendations to wealth managers, and send welcome emails to customers.
Such automation accelerates the KYC procedures and reduces the onboarding time, allowing organizations to
focus on customer service to improve customer satisfaction and increase engagement rates.
To accurately calculate salaries, pensions, and compensation for paid leave, overtime, or important life
events, accountants need to collect and validate diverse data on employee working hours, breaks, and
benefits. Process automation solutions can take on a fair share of these activities, consolidating employee
data, validating timesheet and sick leave entries, flagging anomalies like recorded overtime hours for human
review, and generating payslips, filling them out with the data on working hours, taxes, and deductions.
Additionally, process automation tools can process sick leave and benefits requests, check them against
company policies to confirm their eligibility, and synchronize data on the provided compensations with
workforce management systems.
