Bridging the Productivity Gap in Third-Party Risk Management with AI
FIGURE A:
How have the number of third-party relationships changed for your organization over the past 2-3 years?
FIGURE B:
To what extent has your budget for risk management changed during the same period? 10
FIGURE C:
How would you manage an increased workload and responsibilities for your team without a proportionate increase in resources?
11
13
15
22
FIGURE D:
Which of the following areas are still largely manual at your organization?
FIGURE E:
How much time would you estimate a typical third party spends on answering questionnaires and assessments during your due diligence process?
FIGURE F:
Collectively, how much time is typically spent by members of your team?
FIGURE G:
What do you think are the biggest barriers to adopting such AI-driven solutions? 24
FIGURE H:
What are the biggest challenges you face in managing third party risks?
26
27
28
32
FIGURE I:
What percentage improvement in efficiency have you seen as a result of AI adoption?
FIGURE J:
If your team suddenly had 10% more bandwidth starting next week, how would you use the extra resources?
FIGURE K:
How likely are you to implement more GenAI solutions for TPRM in the next 1-2 years?
FIGURE L:
How many third-party relationships does your organization currently have?
About Us
About CeFPro
The Center for Financial Professionals (CeFPro) is an international research organization and the focal point for the global community of finance, technology, risk, and compliance professionals from across the financial services industry. CeFPro is driven by high-quality, reliable, primary market research. It has developed a comprehensive methodology that incorporates data from its global community that has been validated by an international team of independent experts.
Examples of some of CeFPro’s research include:
• Non-Financial Risk Leaders: the most comprehensive independent study of trends, opportunities, and challenges within non-financial risk
• Fintech Leaders: an international survey to assess the status of the fintech industry and provide details for informed decisions on technology and business-related matters.
To find out more, visit www.cefpro.com/research
About Certa
Certa is the leading Third Party Risk Management (TPRM) solution. With its comprehensive Third Party Operating System (Third Party OS), Certa lets you manage risk across all third party types, all risk domains, all in one OS. Certa leverages AI across the third party lifecycle—automating onboarding, risk analysis, compliance, and monitoring. Its nocode workflows, AI-driven decisioning, and realtime data integrations help you adapt to evolving regulations and business needs. With full spectrum risk coverage, Certa delivers due diligence 80% faster, driving smarter and more efficient third party management for global enterprises.
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Methodology
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As supply chains expand, managing third-party relationships becomes more complex. Our survey indicates that 81% of firms have seen an uptick in third-party relationships in the last three years. Despite this, financial support for managing these risks hasn’t kept up. While 60% of respondents have seen their risk management budgets increase, 40% face stagnant or reduced funding.
This lack of funding creates a productivity gap, meaning that organizations don’t have the resources to keep up with their rising responsibilities. In the absence of a greater budget, organizations must learn to do more with less. This paper explores the productivity challenges in third-party risk management (TPRM) and how generative artificial intelligence (GenAI) can help overcome them.
A:
How have the number of third-party relationships changed for your organization over the past 2-3 years?
*Data
81% of firms report increased third-party relationships, yet 40% face stagnant or reduced risk management budgets.
Figure
Figure B:
To what extent has your budget for risk management changed during the same period?
Methodology
This report is based on a two-phase research process. Our survey engaged 131 organizations across several sectors, including banking, asset/wealth/investment management and insurance, focusing on varying sizes from those managing under $10 million to those with over $500 million assets under management (AUM). Additionally, research with industry experts through one-to-one calls provided deeper insights and real-world context to the survey findings. Key demographics of the respondents included:
Sector representation:
A significant portion (41%) of respondents were from banks.
Size of institutions:
Nearly half (46%) of participants reported having under $10 billion in AUM.
Third-party relationships:
A substantial portion (47%) of respondents indicated that their organizations manage more than 1,000 third-party relationships.
Coping strategies for stagnant budgets
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Continual reliance on manual processes
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Coping strategies for stagnant budgets
Figure C:
How would you manage an increased workload and responsibilities for your team without a proportionate increase in resources? (Select all that apply)
When faced with increased workloads and responsibilities without a corresponding resource increase, 68% of respondents said they would implement automation tools to streamline processes, reinforcing technology as a strategic response to budget constraints.
However, automation through conventional information technology (IT) systems has proven insufficient. Traditional TPRM platforms, which have been used for over a decade, are primarily designed to handle structured data — data that is organized within standardized formats. In contrast, procurement often deals with unstructured data, such as contractual clauses and vendor correspondence, which does not follow a predefined format.
For example, during the initial assessment and ongoing diligence of third parties, organizations must manage a mix of information from spreadsheets, questionnaires, policies, and documents. The need to manually handle data entry and integrate diverse data feeds from these various formats complicates the automation process, leading to bottlenecks.
In the absence of a better solution to managing increased workloads and static resources, many respondents said they would find other ways to manage their responsibilities. 63% of respondents said they would delay non-critical tasks when resources are limited. However, this strategy becomes problematic when all tasks are critical. Additionally, almost half (47%) would seek more resources or redistribute tasks among team members. Neither strategy is foolproof — new funding isn’t guaranteed, and shifting tasks risks overburdening teams and leading to burnout. These challenges highlight the struggles of effectively managing third-party risks without adequate budgets.
Continual reliance on manual processes
The survey highlights a significant reliance on manual processes across all parts of third-party management: 70% of respondents manually analyze thirdparty documents such as contracts and information security reports, while 63% translate changes in regulations and internal policies into actionable workflows.
Additionally, over half of the respondents (56%) manually conduct screening and due diligence for third parties, and the same percentage (56%) manually fill out questionnaires and assessments for compliance and risk management purposes.
Despite some standardization, such as Certificates of Insurance (COIs), System and Organization Controls Reports (SOC2), and ISO Certifications, the variability in policies and formats across third-party documents and specific company requirements are cited as reasons for continuing manual processes.
This is particularly true for analyzing contracts and assessments, which are labor-intensive due to their bespoke nature and the varying standards across companies. These documents, composed of unstructured data, normally require handson processing. Coupled with regulatory updates, they require repeated reviews to ensure compliance accuracy.
Experts point to other factors driving the persistence of manual processes in TPRM: diverse regulatory landscapes across jurisdictions, inconsistent processes within regions, and a cultural tendency among some management teams to equate extensive documentation with thoroughness, which is viewed as a protective measure against regulatory scrutiny.
Figure D:
THE BURDEN OF MANUAL TPRM WORKFLOWS
Manual data collection
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Manual data validation
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Policy and compliance interpretation
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Manual data collection
A significant bottleneck is the resistance of suppliers to complete required questionnaires and assessments. This challenge is particularly acute for smaller suppliers who might not have dedicated teams available to handle inquiries in a timely and accurate manner.
When asked how much time a typical third party spends on answering questionnaires and assessments during their due diligence process, the median respondent reported spending 11-20 hours per month. When viewed at scale, the cumulative burden is significant.
For the median organization managing 501-1000 suppliers1, even at the low end of reported time, this amounts to at least 5,511 hours per month spent solely on due diligence questionnaires. This represents a significant strain — not just for thirdparty vendors who compile the necessary information but also for risk teams that must review and validate these responses.
The extensive time investment in conducting due diligence overwhelms third parties, inundating them with questionnaires
and assessments. This heavy workload leads to significant delays, particularly as functional owners struggle to provide timely responses. In some instances, as noted by one interviewee, these delays can extend up to 90 days or longer. Such delays slow down the onboarding process and negatively impact the accuracy and completeness of the information provided. These inefficiencies can prevent the timely prioritization of essential security measures.
The median organization spends 5,511 hours per month on due diligence questionnaires.
How much time would you estimate a typical third party spends on answering questionnaires and assessments during your due diligence process?
Figure E:
Manual data validation
Manual data validation also poses challenges. Experts caution that the reported numbers in Figure E might underestimate the true effort involved, as third parties often submit incomplete or inconsistent information when answering questionnaires. Such inconsistencies often trigger cycles of follow-ups and reassessments, disrupting workflows and extending the time needed for due diligence.
Additionally, many firms batch these tasks, dedicating several weeks to compliance assessments rather than spreading them evenly throughout the year. This concentrated, often annual, effort can be far more disruptive than maintaining a steady monthly workload.
Since third parties serve multiple clients and many provide multiple services — each with unique risk, compliance and performance requirements and document formats — the lack of standardized, shared documentation leads to repetitive work. Vendors must tailor their responses to each organization’s specific due diligence requirements, multiplying the effort needed.
Policy and compliance interpretation
Another bottleneck in TPRM is the extensive time spent on policy and compliance interpretation. 41% of respondents reported spending more than 30 hours per month
analyzing third-party documents, including contracts, information security reports, and assessments. This highlights the significant workload associated with compliance interpretation, where teams must manually review and evaluate policies.
One expert shared insights into the complexities faced by global firms, noting that regulatory inconsistencies across different regions lead to redundant efforts and a lack of standardized processes — often exacerbated by the manual nature of compliance tasks.
Figure F: Collectively, how much time is typically spent by members of your team?
*Data may not add up to 100% due to rounding
THE ROLE OF GENAI IN TPRM
Automatically creating and updating workflows
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Analyzing third-party documents
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Automated filling of questionnaires and assessments
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Recognizing these challenges, innovations in GenAI help TPRM teams foster efficiency. Here’s how they offer support:
Automatically creating and updating workflows
GenAI significantly streamlines the creation and updating of TPRM workflows, tasks that have traditionally been labor-intensive. In conventional approaches, creating and updating TPRM workflows is a cumbersome process that requires extensive collaboration with IT, developers, or consultants. This multistep approach, from policy interpretation to process orchestration, often results in delays when responding to regulatory changes and best practice updates.
AI technologies like Certa AI streamline process management by directly translating policy updates into fully configured, actionable workflows. Users can input new policies in natural language, and the system automatically generates or updates workflows, ensuring timely compliance without the need for coding.
Survey data shows that the median organization typically spends 10-20 hours per month updating these workflows2 With AI, this time is drastically reduced, freeing teams to focus on more strategic risk management instead of administrative tasks.
Analyzing third-party documents
GenAI significantly reduces the time and complexity of analyzing critical thirdparty documents. Team members spend significant time analyzing documents like contracts, information security reports, and assessments. This manual process is prone to oversight and struggles with the complexity of unstructured data.
Traditional systems, which are limited to structured data formats such as APIs, spreadsheets, and formulaic data sheets, fail to efficiently handle the variability and complexity of unstructured documents. In contrast, GenAI technologies have the capability to interpret diverse documents, regardless of variations in order and format.
The
median firm spends between 21 to 30 hours per month analyzing third-party documents.
GenAI tools can initially screen these reports and flag what teams need to review manually, reducing the time assessors spend reviewing documents and allowing teams to focus on strategic risk management and compliance issues.
How Certa AI can help:
Continuously assess and correlate information, systems, and data
Unlike traditional methods that don’t account for changes in third-party-provided documents, evidence, and other unstructured documents, Certa AI offers continuous assessment with real-time alerts. This proactive risk management ensures identifying potential threats early and validating data across various sources, including unstructured documents.
Automate remediation plans
Traditional manual remediation is reactive and slow, risking prolonged disruptions or compliance failures. Certa AI automatically generates and manages remediation plans based on issues identified during the analysis of third-party documents, enhancing responsiveness and minimizing compliance risks before they escalate.
Instantly analyze third-party population contracts documentation, and corporate systems
Traditional methods for analyzing third-party portfolios and related information are often slow and cumbersome, hindering responsiveness to new requirements. Certa AI rapidly assesses contracts and documentation, such as SOC2, against new requirements, proactively identifying compliance gaps and ensuring ongoing management to stay ahead of emerging risks.
Automatically Analyze, Enforce, and remediate KPIs/ SLAs
Manual tracking of key performance indicators (KPIs) and service level agreements (SLAs) against business continuity and disaster recovery (BCDR) plans and performance tests can miss critical issues, risking disruptions and non-compliance. Certa AI automatically analyzes and enforces KPIs/SLAs, proactively correcting deviations to maintain service level compliance, ensure business continuity, and enhance operational efficiency. It also identifies areas for improvement in vendor performance, optimizing relationships and holding teams accountable.
Automated filling of questionnaires and assessments
Expanding the use of GenAI further, tools now also automate routine TPRM tasks. This includes the filling of due diligence questionnaires and assessments, significantly reducing the manual effort required and enhancing data accuracy.
How Certa AI can help:
Streamlining due diligence with Certa AI: Data AI empowers vendors by reducing the time and effort to complete questionnaires. Third-party stakeholders provide policies, certifications and other documents, and Certa AI automatically generates initial answers — reducing the manual input required.
Intelligent Pre-Fill automatically precompletes assessments using existing and historical evidence, freeing up valuable time for IT and information security teams.
Third Party Risk Management in action: Case Study
Faced with lengthy onboarding times and inefficient vendor management, Quantcast, a leader in advertising technology, used Certa’s platform to revolutionize its processes. The implementation reduced onboarding times by threefold, achieving seven-day onboarding for high-risk vendors and five for low-risk ones. It also streamlined the management of over 200 contract renewals and facilitated more than 1,000 notifications across 300 vendors. This allowed for more effective risk categorization and targeted mitigation strategies. Additionally, Certa AI’s tool freed up valuable resources, providing Quantcast with a comprehensive view of all vendor relationships and improving decision-making and operational efficiency.
CHALLENGES AND BARRIERS TO AI ADOPTION
Data security concerns
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Resource and budget constraints
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Data security concerns
Data security is the primary concern for 60% of firms when adopting AI-driven solutions. The technology is still fairly new, and widespread perceptions of its potential risks exist, particularly following data breaches involving AI platforms. Additionally, there is a perceived lack of proven security, especially concerning the handling of sensitive information and third-party risks.
Figure G: What do you think are the biggest barriers to adopting such AI-driven solutions?
Concerns over data security
Cost of implementation
Lack of awareness of available solutions
Lack of skilled personnel to operate AI tools
Resistance to change within the organization
OTHER:
AI is not integrated into Risk framework and appetite
Budget Constraints
Concern with data accuracy from AI use
Concerns about accuracy of results
Lack of consistency in the offering, unproven track record, reliability of provider
Lack of knowledge to ensure AI tools are producing valid outcomes
No proven need
Not yet convoked there is a proper AI tool rather a lot of rebranding and usage of the letters from average vendors Resource
by AI
One interviewee highlighted concerns over AI’s self-modifying capabilities and the potential unintended consequences of its use, which are poorly understood. This predictability raises concerns about possible security vulnerabilities that AI might introduce.
Experts compared the transition to newer technologies like AI to earlier technologies such as cloud computing, which initially also caused widespread concern and confusion. As organizations and regulatory bodies learn to ask the right questions about AI, they can better establish a foundational understanding to help mitigate these risks.
Concretely, regulatory bodies are beginning to draft AI rules. In 2024, the world’s first comprehensive AI law, the European Union’s AI Act, came into effect. The act mandates that companies dealing with AI must meet stringent requirements in risk management, data governance, information transparency, and human oversight3. Other jurisdictions, such as Singapore, have implemented regulatory frameworks, such as the Model AI Governance Framework for GenAI4.
As clearer regulations and standards are developed, many of the perceived barriers to AI adoption will likely diminish, enabling organizations to implement AI more securely.
Certa’s Approach to responsible AI
Certa AI is committed to developing and using AI responsibly, prioritizing fairness, transparency, and accountability. We uphold data privacy, mitigate bias, and maintain human oversight, aligning AI with ethical and legal standards. Our approach includes ethical impact assessments, user empowerment for data control, ongoing external engagement, and continuous evaluation. By ensuring safety, explainability, and inclusivity, we create AI solutions that benefit individuals, businesses, and society.
The Pillars of Responsible AI in Enterprise
Fairness
Guard against biases in data
Inclusiveness
Ensure that AI is accessible and sensitive to all populations
Reliability
Verify that results are accurate for the selected use case
Privacy & Safety
Guarantee that data used during pre-empting or training can’t be leaked
Transparency Information is from verifiable sources and auditable
Accountability Legal, regulatory, compliance, along with fairness, safety
Resource and budget constraints
47% of respondents view the high costs of implementing AI-driven solutions as a significant barrier to adoption. When asked about the biggest challenges faced in managing third-party risks, 53% cite a lack of time and resources, and 50% struggle with inadequate technology and tools.
Budget limitations prevent organizations from acquiring essential resources, such as sophisticated tools and skilled personnel. Experts noted that this often leads TPRM teams to devise creative but temporary solutions to cope with escalating demands. While these stopgap measures may address immediate needs, they are unsustainable for long-term operational stability.
One expert predicted that budget constraints and inadequate resource allocation could lead to significant issues
such as audit failures or control breakdowns, which could eventually lead to hefty regulatory fines or, paradoxically, require emergency budget increases to address regulatory pressures or operational failures.
While initial costs are a consideration, GenAIdriven tools offer a practical approach to streamlining TPRM — by automating routine tasks, helping organizations manage resources more efficiently, reducing the risk of costly errors, and improving compliance practices. With 37% of respondents citing a lack of awareness of available solutions and 34% a shortage of skilled personnel to operate AI tools, there’s a clear need to invest in training and development. Such initiatives would effectively equip teams to leverage GenAI, balancing its long-term value against upfront investment.
Other (please specify)
OTHER:
Historically, board acceptance and real support
Lack of understanding of this priority by Management
Lack of up to date intelligence
Low bargaining power
Some regulatory bodies ask virtually the same thing, so you literally repeat the same thing for the next.
The constant changes in requirements impacting Third parties. Changes in risk requirements also impacts configuration on the TRPM tool that we use.
Transparency of functional vendor owners Unstructured data
Validated financial information
Vendors disclosing relevant details on their product/service
Figure H:
BENEFITS AND ROI
Efficiency and productivity gains
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Better resource allocation
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Enhancing strategic flexibility
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Efficiency and productivity gains
Users of AI-based solutions for TPRM report significant and measurable benefits. A substantial 39% of respondents reported a 21-30% improvement in efficiency from adopting AI, while another 26% noted an 1120% increase.
These efficiency gains are not just numbers; they translate into tangible benefits such as cost savings, more dynamic risk management strategies, and enhanced compliance. This demonstrates how AI can bolster operational capabilities by allowing teams to allocate their focus toward strategic activities rather than remaining bogged down in manual tasks.
Despite these gains, it’s noteworthy that 30% reported less than a 10% efficiency improvement. This modest increase points to a significant challenge: the lack of skilled personnel to effectively operate AI tools. There is a clear need for well-designed training programs that help teams adapt to new technology, as well as an allocation for proper training and support to fully leverage AI’s capabilities. Additionally, choosing technology that is easy to use and has intuitive interfaces can make this transition smoother.
Better resource allocation
With even a 10% increase in bandwidth, 66% of respondents indicated they would allocate the extra resources to focus on higher-level strategic initiatives. Additionally, 44% said they would conduct more in-depth due diligence on third parties, and 31% said they would improve the accuracy of due diligence assessments.
Figure J:
If your team suddenly had 10% more bandwidth starting next week, how would you use the extra resources? (Select all that apply)
Expert opinions confirm that manual processes, such as vendor responses and documentation reviews, create significant bottlenecks. These inefficiencies highlight the need for a strategic shift from performing manual tasks to engaging in higher-level planning and decision-making. This shift significantly impacts the organization's direction and enhances overall efficiency.
One expert noted the current operational realities: due to pressing demands and an increase in workload without a corresponding increase in headcount, teams often must prioritize operational capacity over strategic planning. Although strategic initiatives are recognized for their value, immediate operational needs frequently take precedence.
GenAI-driven tools have the capacity to free up resources by automating repetitive tasks, enabling teams to concentrate on key operations, enhancing efficiency, and improving the overall agility and responsiveness of risk management functions — which ultimately benefit return on investment (ROI).
specify)
66% of respondents would use a 10% increase in bandwidth to focus on higher-level strategic initiatives.
Enhancing strategic flexibility
Over the next 1-2 years, 62% of respondents are likely or very likely to implement more GenAI solutions, with only 15% indicating they are unlikely or very unlikely to adopt. This indicates a clear interest in GenAI, recognizing its potential to enhance TPRM processes.
Within the next 1-2 years, 62% of respondents are likely to adopt more GenAI solutions.
K:
The enthusiasm for GenAI, while marked by gradual adoption rates, highlights a strategic shift towards more sophisticated, efficient systems. Most organizations are currently in exploratory phases, cautiously assessing the costs, security, and reliability to ensure that the technology aligns with their operational needs.
Experts suggest that the adoption of general tools akin to GenAI assistants, although still in the early stages, marks a shift towards automating more complex tasks — such as pre-populating questionnaires.
This measured pace is part of a broader trend that has moved from understanding AI’s potential to actively implementing solutions that can drive significant gains in efficiency and strategic risk management. The key factors influencing further adoption of GenAI include budget availability, organization ambition, confidence in the technology, senior management support, and appropriate guardrails for its strategic use.
As GenAI technology becomes increasingly integral to operations and adoption grows, it is poised to transform risk management practices across industries.
FUTURE READINESS WITH GENAI
Conclusion Page 30
Executive summary: Certa’s reaction
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Conclusion
Survey insights reveal a pressing need for better tools in TPRM, with GenAI set to optimize these processes. Amid budget constraints, the case for adopting AIdriven technologies becomes even more compelling as they create significant operational efficiencies and close productivity gaps. This extra bandwidth can allow firms to focus on higher-level strategic initiatives —precisely what the majority of respondents indicated they needed — which is critical for navigating the intricate dynamics of today’s global supply chains.
Executive summary: Certa’s reaction
In today’s increasingly complex and tumultuous business environment, thirdparty risk management (TPRM) has become a first-tier priority for organizations worldwide. As global supply chains expand, businesses face mounting regulatory pressures and operational risks, despite contending with stagnant risk management budgets. The need for greater efficiency and productivity in TPRM has never been more urgent.
At Certa, we recognize that traditional, manual approaches to TPRM are no longer sustainable. Our research, in collaboration with CeFPro, reveals that 81% of firms have seen an increase in third-party relationships over the last three years, yet 40% report stagnant or reduced budgets. Manual workflows remain a significant bottleneck, with 70% of organizations still relying on labor-intensive processes for document analysis and 56% conducting manual due diligence. The result is a productivity gap that threatens organizations’ ability to manage risk effectively.
68% of risk professionals are looking to implement automation tools, showing that the industry recognizes the need to close the productivity gap. However, traditional IT falls short when it comes to automating risk teams’ manual processes. Previous solutions were built to analyze structured data, like spreadsheets and databases, and not the unstructured data, like contracts, assessments, and compliance reports, that risk teams work with heavily in their day-today.
To bridge this gap, generative AI (GenAI) offers a transformative solution, enabling organizations to:
• Automate and streamline workflows by instantly translating regulatory changes into actionable processes.
• Pre-fill due diligence assessments to ease the burden on vendors and internal teams.
The results speak for themselves. Organizations that have adopted AI-driven TPRM solutions report median efficiency gains of 21-30%, and 66% of respondents indicate that they’d use efficiency gains to focus on more high-level, strategic initiatives, which are crucial to the long-term success of a business.
Barriers to AI adoption persist, with 60% of firms citing data security concerns and 47% pointing to implementation costs. Despite these challenges, 62% of firms plan to expand their use of GenAI in TPRM within the next two years, recognizing that the ability to automate, analyze, and innovate will define the future of risk management. Looking ahead, AI-driven TPRM will no longer be a competitive advantage—it will be a necessity.
Jag Lamba CEO & founder Certa
At Certa, we are committed to empowering organizations with cutting-edge AI solutions that simplify workflows, automate processes, and deliver full visibility. Designed to be modular and flexible, Certa scales as your business grows and adapts effortlessly to evolving regulations. Contact us today to explore how AI-driven TPRM can drive measurable value for your business.
Additional questions from survey
Figure L:
How many third-party relationships does your organization currently have? *Data may not add up to 100% due to rounding
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