CUSTOMER PORTAL
Third-party onboarding rarely slows down because of one major obstacle. More often, delays build one step at a time. An incomplete questionnaire comes back for correction. An analyst searches for supporting evidence. A financial review sits in a queue.
When you’re operating at the scale of a global financial institution, those small delays can add up to thousands of hours and hold up the business initiatives that depend on new third parties.
This is where the business case for natively embedded AI in third-party risk management becomes clear. The value comes from applying focused AI agents to high-volume work where they can improve submission quality, complete analysis faster, and give risk professionals better information for their decisions.
One of Aravo’s Fortune 100 financial services customers put this approach into practice with Aravo AI. Operating across 19 countries, the organization manages more than 40,000 third parties and onboards approximately 1,900 new third parties each month.
The organization deployed two Aravo AI agents at critical points in its onboarding process. One improves questionnaire quality before analyst review. The other accelerates the financial risk assessments that follow.
Questionnaire rework creates a costly cycle during third-party onboarding. A third party submits incomplete or inconsistent answers. An analyst identifies the problems and returns the questionnaire. The third party revises its answers and submits the questionnaire again.
Each correction may seem minor, but the repeated handoffs add up.
For this financial services organization, teams process tens of thousands of questionnaires every year. A typical submission required two or three review cycles, adding days or even weeks to the assessment timeline. Analysts spent valuable time checking responses and identifying preventable errors instead of evaluating risk.
The organization used Aravo to create an Intelligent Questionnaire Validation Agent that improves submission quality before a questionnaire reaches an analyst.
Natively embedded in the Aravo platform, the agent:
Moving these checks earlier in the process has produced measurable results. The agent catches more than 80% of submission issues before analyst review. Questionnaire completion is 30% to 40% faster, while reject-and-resubmit cycles have fallen by 50% to 70%.
The benefits extend beyond faster questionnaire completion. Analysts receive more complete submissions and spend less time finding errors that could have been addressed before review. The organization can also process more assessments without increasing staff at the same rate as third-party volume.
Once a third party submits the required information, financial risk analysis can become the next onboarding bottleneck.
Analysts may need to review several years of financial statements, calculate key ratios, identify trends, and explain what those findings mean for the organization. The work requires financial expertise, but much of the preparation is repetitive and time-consuming.
At this financial institution, each financial and contract review required approximately four to six hours of analyst time.
The organization used Aravo to create a Financial Risk Assessor Agent to handle much of the analytical preparation. The agent:
With the agent, financial analysis that previously took four to six hours can be completed in approximately three minutes.
Analysts can spend less time collecting information and performing calculations. They can focus their attention on validating the results, investigating exceptions, and applying the business context that requires human judgment.
The agent also strengthens governance by applying a consistent analytical approach across the organization’s third-party population. This helps reduce variation between assessments while preserving human oversight of risk decisions.
The two agents address different sources of friction within the same onboarding journey.
The Intelligent Questionnaire Validation Agent improves the quality of information entering the process. The Financial Risk Assessor Agent accelerates the specialized analysis that takes place once that information is available.
Together, the agents help the organization:
This is where the return on AI begins to compound. Better submissions move forward sooner. Financial reviews take minutes instead of hours. Analysts recover time they can redirect toward exceptions, higher-risk relationships, and decisions that require their expertise.
Faster onboarding also creates value outside the risk team. When assessments move forward more efficiently, business teams can begin working with the providers they need sooner. AI helps remove operational delays that can slow broader business initiatives while maintaining the governance expected of a global financial institution.
In financial services, efficiency cannot come at the expense of control.
Aravo AI agents create value by completing defined tasks within governed TPRM workflows. They validate information, perform analysis, summarize findings, and flag potential concerns. Risk professionals remain responsible for reviewing the output, investigating material issues, and making decisions based on the organization’s policies and risk appetite.
This balance allows financial institutions to automate repetitive work without removing people from the decisions that matter.
It also gives organizations a practical way to measure AI ROI. Instead of focusing on the number of AI features deployed, teams can track operational outcomes such as questionnaire completion time, resubmission rates, analyst hours, assessment capacity, and total onboarding time.
The business case for AI becomes easier to defend when organizations connect it to measurable operational results.
For this financial services organization, the value shows up in work its teams perform every day: fewer preventable submission issues, shorter questionnaire cycles, financial analysis completed in minutes, and greater onboarding capacity without proportional headcount growth.
The broader lesson is that AI ROI does not require one sweeping transformation. It can begin with focused agents assigned to high-volume tasks at specific points in the third-party lifecycle. When those agents operate within the same platform, workflow, and governance framework, their value extends across the process.
For financial institutions under pressure to move faster while maintaining disciplined third-party oversight, Aravo AI offers a practical standard for success: measurable improvements in capacity, consistency, and time to decision.
Contact Aravo to learn how natively embedded AI agents can help your organization improve third-party onboarding and financial risk assessment.
Share with Your Friends: