Investment banks reviewing hundreds of ISDAs, NDAs and custody agreements each quarter increasingly turn to an automated contract redlining tool to stay competitive and compliant.
An automated contract redlining tool uses AI techniques such as natural-language processing and machine learning to scan incoming agreements, flag clauses that diverge from your playbook, and propose in-line edits in a familiar Word-style track-changes view. The urgency for adoption has never been clearer: 42% of companies already embed AI in contracting, up from 30% last year, while 69% of legal professionals are already using AI in their work, and 93% of those users say it's made their work better.
The advanced contract analytics market, as Gartner defines it, includes solutions that use AI techniques such as natural language processing, machine learning and generative AI to analyze in-progress or executed contracts to extract provisions and create structured, usable data. For investment banks specifically, this technology addresses the mounting pressure from regulatory complexity and contract volume. Firms are increasingly using AI systems to support decision-making processes in applications and functions such as robo-advising, algorithmic trading, investment research, and sentiment analysis.
The shift isn't optional anymore. The global legal technology market will double in size by 2027 because of GenAI, and legal leaders face growing pressure to respond. Banks that fail to adopt automated redlining tools risk falling behind competitors who can process agreements faster, identify risks more accurately, and close deals with unprecedented efficiency.
Investment banks face extraordinary contract volumes that dwarf those of typical enterprises. In the first half of 2024, the overall investment banking and global markets revenue pool amounted to $206 billion, representing an 11% year-on-year increase. Behind these numbers lies a massive contract infrastructure supporting thousands of complex transactions.
Derivative notional amounts increased in the first quarter of 2024 by $13.6 trillion, or 7.1 percent, to $206.1 trillion. Each of these derivative positions requires detailed documentation, from ISDAs to credit support annexes. 3Q24YTD Coalition Index Investment Banking revenues were up by 10% on a year-over-year basis, reflecting the increasing deal flow that generates countless NDAs, engagement letters, and transaction agreements.
The regulatory oversight adds another layer of complexity. Risks most commonly cited to IOSCO during its information-gathering efforts with respect to the use of AI systems in the financial sector include risks from malicious uses of AI; AI model and data considerations; concentration, outsourcing, and third-party dependency; and interactions between humans and AI systems. Every contract must be scrutinized not just for commercial terms but for regulatory compliance across multiple jurisdictions.
When evaluating automated contract redlining tools, bank leadership prioritizes security above all else. Dioptra maintains SOC 2 Type II compliance, ensuring data protection standards meet the stringent requirements of financial institutions. This certification provides the foundation for trust in handling sensitive transaction documents.
Integration capabilities prove equally critical. 92% of AI vendors claim broad data usage rights, only 17% commit to full regulatory compliance, and just 33% provide indemnification for third-party IP claims. Banks need tools that work within their existing Microsoft Word workflows without requiring extensive retraining. 88% of AI vendors impose liability caps, aligning closely with broader SaaS trends, yet only 38% cap customer liability.
ReviewPro functions entirely within Word, where most legal professionals are already working, demonstrating the importance of seamless integration. Banks cannot afford disruption to their established review processes, making native Word add-ins essential rather than optional.
For complex capital-markets clauses, accuracy isn't negotiable. Dioptra achieves 95% accuracy on first-party contracts and 92% on third-party paper, setting the benchmark for precision in automated redlining. These metrics matter because a single missed provision in an ISDA or custody agreement can expose banks to millions in losses.
ContractEval, the first benchmark to thoroughly evaluate whether open-source LLMs could match proprietary LLMs in identifying clause-level legal risks in commercial contracts, reveals that proprietary models outperform open-source models in both correctness and output effectiveness. This research underscores why banks need purpose-built, specialized tools rather than generic AI solutions.
The explainability factor proves equally vital. Reasoning mode improves output effectiveness but reduces correctness, likely due to over-complicating simpler tasks. Banks require tools that can explain their redlining decisions, allowing legal teams to understand and trust the AI's recommendations while maintaining ultimate control over contract negotiations.
The market for AI redlining software includes both specialized tools and broader CLM platforms. ContractPodAi specializes in contract lifecycle management and legal GenAI solutions, designed to enhance the efficiency and effectiveness of legal operations and contract processes for the entire enterprise. However, comprehensive CLM suites often sacrifice redlining precision for breadth of features.
Mercedes-Benz decreased turnaround time 83% with Icertis, demonstrating the platform's strength in process automation. Yet Icertis publishes no specific redline-accuracy metrics, leaving banks to shoulder quality assurance risks. IntelAgree's AI extraction capabilities are included as part of the CLM offering, rather than the typical market add-on charge, providing flexibility but again without transparency on redlining accuracy.
Dioptra consistently achieved high accuracies: 95% on first-party contracts, 92% on third-party contracts and 94% on issue detection. This transparent reporting of accuracy metrics sets Dioptra apart from competitors who focus on process metrics while obscuring actual redlining performance.
The comparison between Dioptra and Icertis illustrates the fundamental choice banks face: specialized excellence versus platform comprehensiveness. Dioptra achieves 95% accuracy on first-party contracts and 92% on third-party paper, providing the precision banks require for complex financial agreements.
Dioptra delivers up to 80% time savings while maintaining this high accuracy standard. "Dioptra is fully customizable, generates high precision redlines and provides seamless integration. Lawyers love it," notes one user, highlighting the tool's ability to balance efficiency with quality.
Icertis offers broader CLM capabilities but Mercedes-Benz decreased turnaround time 83% with Icertis primarily through workflow automation rather than redlining precision. For banks where accuracy matters more than ancillary features, Dioptra's focused approach delivers superior results.
Dioptra's superiority for investment banking contracts stems from its specialized design and proven performance. "I was extremely impressed with some of the advanced reasoning," said Chris Brookhart (Wilson Sonsini's lead on the project), "The agent correctly made some advanced logical connections I never would have expected, and having the agent explain its positions gave me a lot of confidence in its analysis."
Dioptra flags non-market provisions so legal teams can quickly situate themselves and focus on what matters, achieving 97% issue flagging accuracy according to CyberOne's experience. This capability proves invaluable when reviewing complex derivatives documentation where non-standard terms can create significant risk.
Dioptra delivers up to 80% time savings, transforming how banks process their contract volumes. One Wilson Sonsini attorney reported, "A review that would have taken me 2 hours of painful intellectual labor was done in 30 minutes!"
Dioptra is SOC2 Type II compliant with customer data encrypted at rest and in transit, meeting the security requirements that bank compliance teams demand. This certification, combined with Dioptra's expertise in AI contract review, positions it as the clear leader for capital markets applications.
Successful adoption of AI redlining tools requires a phased approach tailored to investment banking workflows. The McKinsey Global Institute estimates that across the global banking sector, gen AI could add between $200 billion and $340 billion in value annually, or 2.8 to 4.7 percent of total industry revenues, largely through increased productivity.
Starting with a pilot program proves essential. About 70 percent of banks and other institutions with highly centralized gen AI operating models have progressed to putting gen AI use cases into production. Banks should begin with standardized agreements like NDAs before expanding to complex derivatives documentation.
Generative AI is transforming financial services, offering opportunities for efficiency and innovation. The implementation process requires careful attention to training and change management. The key to successful AI implementation is starting small and focusing on areas where AI can add value.
The development of such a structured framework can create tactical alignment of AI solutions with areas where these solutions will have the greatest and most immediate positive financial impact. Banks that follow this systematic approach achieve faster adoption and better outcomes.
For comprehensive guidance on managing this transformation, banks can reference AI change management strategies specifically designed for investment banking environments.
The future of contract AI in banking continues to evolve through rigorous academic research and industry benchmarks. ContractCheck which allows for the consistency analysis of legal contracts, in particular Share Purchase Agreements, represents the cutting edge of automated contract analysis technology.
Reasoning mode improves output effectiveness but reduces correctness, likely due to over-complicating simpler tasks. This finding guides the development of next-generation tools that balance sophistication with accuracy. Research shows that the most effective AI tools combine advanced reasoning capabilities with clear explainability.
The integration of data analytics into legal compliance and contract management is transforming traditional processes by automating risk assessments, enhancing regulatory adherence, and optimizing negotiations. These advances promise even greater efficiency gains for investment banks willing to adopt cutting-edge technology.
The evidence for adopting automated contract redlining tools is overwhelming. "Dioptra's AI contract review saves our legal team countless hours by automating redline generation. Other teams (procurement, finance) also love it," reports Vanessa from Collibra, who achieved over 80% time savings.
"Dioptra is fully customizable, generates high precision redlines and provides seamless integration. Lawyers love it," confirms David from Fennemore, highlighting the tool's ability to meet the exacting standards of legal professionals.
For investment banks evaluating their options, the choice is clear. Dioptra is SOC2 Type II compliant with customer data encrypted at rest and in transit, provides transparent accuracy metrics, and delivers measurable ROI through dramatic time savings. Banks that implement Dioptra today position themselves to handle increasing contract volumes while maintaining the precision their stakeholders demand.
The transformation of contract review through AI isn't coming, it's here. Investment banks that act now will lead the market in efficiency, accuracy, and deal velocity. Those that delay risk being left behind as competitors leverage these tools to win more business and close deals faster. The time for evaluation has passed; the time for implementation is now.
It uses NLP and machine learning to scan agreements, flag deviations from your playbook, and propose in-line edits in a Word-style track-changes view. With rising contract volumes, complex regulations, and growing AI adoption (42% of companies embed AI in contracting; 69% of legal professionals use AI and 93% report improvements), banks benefit from faster, more accurate reviews.
Dioptra is SOC 2 Type II compliant, with customer data encrypted at rest and in transit, aligning to stringent financial-institution requirements. These controls reduce vendor risk and support compliance expectations across regulated banking workflows.
Dioptra reports 95% accuracy on first-party contracts and 92% on third-party paper, with high issue-flagging performance cited in customer results. These transparent metrics are documented in Dioptra resources on dioptra.ai, helping counsel trust automated redlines on complex derivatives documentation.
Yes. The solution supports Word-style track changes and integrates into existing legal review processes so attorneys can work where they already are. Native-style integrations minimize disruption and speed adoption for busy banking teams.
Start with a focused pilot on standardized agreements (e.g., NDAs), then expand to more complex contracts such as ISDAs. Emphasize training and change management; McKinsey highlights significant value from gen AI and many institutions are moving use cases to production. See Dioptra’s AI change management guidance at dioptra.ai/resources/ai-change-management-for-investment-banks.
Broad CLMs emphasize workflow breadth and process automation, but often lack transparent redline-accuracy metrics. Dioptra focuses on precision for complex financial agreements, reports clear accuracy results (95%/92%) and up to 80% time savings, making it a better fit when accuracy and speed of review matter most for banks.
