in potential additional annual retail-banking profit from AI by 2030. BCG identifies agents as a major accelerator.
BCG · November 2025 · Forecast ↗ThinkStack for banking
Get from application to informed decision faster.
Bring customer records, financial analysis, and policy context together for onboarding, credit reviews, and investigations. ThinkStack agents prepare the evidence and draft the reporting, giving your specialists a clear starting point for the decisions ahead.
Agentic AI in perspective
The business impact taking shape in banking
From industry-wide potential to gains in specific banking workflows, published research shows where AI can change the economics of the work.
underwriting staff productivity at a European bank after redesigning its credit process with agentic AI. Expressed from BCG’s reported 50% uplift.
BCG · June 2026 · Reported case ↗lower cost to serve in banks that redesigned a frontline domain end to end around agentic AI, reported from McKinsey’s work.
McKinsey · December 2025 · Reported experience ↗Industry research and reported banking examples, not ThinkTrends customer results. Forecasts and individual outcomes are not guarantees of future performance.
The connected workflow
Equip your experts with modern data workflows
ThinkTrends governs and monitors agent access to tools through the Model Context Protocol (MCP). Combine retrieval-augmented generation (RAG), multi-agent orchestration, and runtime policies to reduce manual handoffs, accelerate reviews, and give your experts more time for decisions that need their judgment.
01 · Connect the relevant information
Customer & case filesForms, records, supporting documents
Banking dataConnected tables, extracts, feeds
Policies & publicationsInternal guidance, selected external sources
Enterprise toolsMCP servers, APIs, and OAuth connections
ThinkStack
Agents, tools, and workflow orchestration
MCP-enabled toolsConnect existing MCP servers or build and host custom tools.Grounded retrieval · RAGRetrieve relevant knowledge with source attribution and access policies.Managed agent harnessesBind models, instructions, skills, and tools in a managed runtime.Multi-agent orchestrationChain agents and branch workflows around defined inputs and outputs.Runtime guardrailsConfigure PII redaction, topic restrictions, and prompt-attack filtering.Traces & evaluationsInspect tool calls and score outputs against domain-specific rubrics.
Configured sources · Defined permissions · Specialist review
02 · Deliver outputs your specialists can use
OnboardingReview packetsCredit analysisEvidence summariesInvestigationsCase briefsRegulatory changeImpact assessmentsReportingReviewable draftsAgent qualityEvaluation results
Where to start
Multiple workflows. A shared platform.
Combine the capabilities around your process, your sources, and your review requirements. These examples show what a configured banking workflow could deliver.
01Customer onboarding & KYC reviewTurn document-heavy intake into a structured packet for your onboarding specialists.
- Start with
- Application forms, identity documents, customer records, and your onboarding checklist.
- The agent workflow
- Use extraction agents to structure documents, apply validation rules, and use configured MCP tools to retrieve related records. Organize missing or uncertain items for specialist review.
- What your team receives
- A structured onboarding packet with source references and an exception list.
- Specialist judgment
- Your team resolves identity and record-matching exceptions and makes the onboarding decision.
- Measure the value
- Preparation time per packet, missing-information rework, and reviewer correction rate.
02Credit analysis preparationBring borrower evidence and financial analysis together before the credit review.
- Start with
- Financial statements, application data, connected portfolio tables, and internal credit guidance.
- The agent workflow
- Extract figures, run configured SQL or Python analyses, retrieve policy context, and prepare a cited narrative for the analyst.
- What your team receives
- An analysis brief with tables, source references, and questions for the credit team.
- Specialist judgment
- Credit specialists validate assumptions, assess the evidence, and own lending decisions.
- Measure the value
- Time to prepare a review brief, reconciliation effort, and corrections made by analysts.
03Fraud & AML investigation supportHelp investigators assemble the context behind an existing alert or case.
- Start with
- Alerts from your existing systems, permitted transaction data, case notes, and investigation procedures.
- The agent workflow
- Use configured MCP tools to retrieve case context, analyze relevant records, and draft a case narrative. Apply PII guardrails and retain execution traces for the review.
- What your team receives
- A reviewable case brief linking the narrative to the underlying records and analysis.
- Specialist judgment
- Investigators assess the case and decide on disposition, escalation, and any filing.
- Measure the value
- Evidence-gathering time, review effort per case, and completeness of case documentation.
04Regulatory change assessmentConnect a new publication to the policies and procedures your team needs to examine.
- Start with
- Selected regulatory publications, internal policies, procedures, and knowledge bases.
- The agent workflow
- Use retrieval-augmented generation (RAG) to work from relevant policy passages, compare the material, and propose source-grounded revisions for subject matter review.
- What your team receives
- An impact assessment and source-grounded policy change suggestions.
- Specialist judgment
- Compliance and legal specialists determine applicability and approve interpretations and revisions.
- Measure the value
- Time to assemble an assessment, citation coverage, and reviewer rework.
05Regulatory & management reportingCoordinate data preparation, analysis, and drafting around a defined reporting cycle.
- Start with
- Reporting datasets, supporting documents, prior reports, and approved reference material.
- The agent workflow
- Orchestrate extraction, analysis, and document agents in a defined flow. Validate inputs, calculate figures, and propose narrative edits with source citations.
- What your team receives
- A reporting draft supported by analysis, source material, and a record of proposed edits.
- Specialist judgment
- Report owners check the figures and narrative and control final approval and submission.
- Measure the value
- Preparation hours per cycle, reconciliation effort, and revision rounds.
06Agent quality & model-change evaluationGive domain experts a repeatable way to judge agent behavior as configurations change.
- Start with
- Selected agent runs, test cases, expected outputs, and a rubric defined by your reviewers.
- The agent workflow
- Build graded datasets, compare response scores, inspect failing traces, and calibrate the evaluator against human judgments.
- What your team receives
- Per-case scores, trace evidence, and an evaluation comparison for the proposed change.
- Specialist judgment
- Your team defines acceptable performance and decides whether a change is ready to use.
- Measure the value
- Reviewer–evaluator agreement, regression failures, and time spent diagnosing errors.
Regulatory reporting · workflow example
From source material to specialist review
For a recurring report, combine extraction, analysis, knowledge retrieval, and document suggestions in a coordinated flow. Specialists can review the evidence and proposed wording before the report moves into your submission process.
Explore document workflows- 01
Collect & validate
Extract reporting inputs from documents and feeds. Apply validation rules and send low-confidence records for review.
- 02
Analyze & assemble
Run SQL or Python analysis, retrieve relevant policy passages, and assemble the figures and evidence for a draft.
- 03
Suggest & review
Prepare source-grounded wording as tracked suggestions. Reviewers accept, reject, or revise the changes.
- 04
Inspect & improve
Inspect the execution trace and evaluate sample outputs against your team’s rubric before changing the workflow.
Connectivity, governance & assurance
Enterprise controls for agentic banking.
Give domain experts the reach of connected agents and give review teams a clear view of the controls behind the work.
MCP with managed credentials
Connect tools through registered MCP servers. Reference stored secrets or OAuth connections, and test the handshake before making a tool available.
Explore hosted MCP servers ↗Guardrails that run with the agent
Configure PII masking or blocking, custom identifier patterns, denied topics, and prompt-attack filtering. Set inbound and outbound rules independently, with response-grounding checks on output.
Explore Policy & Guardrails ↗Evidence for every review
Inspect retrievals, tool calls, and guardrail decisions in execution traces. Use domain rubrics and human-calibrated evaluators to compare outputs when prompts, models, or tools change.
Explore Observability & Tracing ↗SOC 2 Type II & ISO 9001:2015
ThinkTrends has a SOC 2 Type II report and is ISO 9001:2015 certified for quality management. Discuss the applicable scope and supporting documentation with our team as part of your vendor assessment.
Discuss assurance documentation ↗What’s possible
Reimagine the workflow. Expand what your team can do.
Up to20×
potential productivity in supervised agentic banking workflows
McKinsey forecasts productivity gains of up to 20 times in supervised digital-factory workflows, where people oversee coordinated AI agents. The opportunity comes from redesigning the work end to end.
Coordinate the whole process
Connect information gathering, analysis, drafting, and handoffs in a defined multi-agent workflow.
Focus expertise on exceptions
Give specialists the context to review uncertain cases and retain control of consequential decisions.
Prove value in your environment
Baseline one workflow, measure quality and effort, and expand only when the results support it.
A forecast, not a measured banking result: McKinsey’s September 2026 report states that no bank had yet achieved a twentyfold productivity increase from agentic AI. This is not a ThinkTrends performance claim.
McKinsey · The decade to redefine UK banking · September 2026 ↗Supporting your evaluation
Bring your review team into the conversation
Share the MCP, runtime, and governance detail with your technical reviewers, and bring assurance documentation into the compliance and procurement discussion.
Risk & compliance
Review how policies and guardrails are applied, and how agent activity can be inspected.
Policy & Guardrails Observability & TracingSecurity & architecture
Explore runtime isolation and secrets management as inputs to your technical assessment.
Agent Runtime Environments Secrets ManagerLegal & procurement
Discuss data handling, ownership, and contract requirements with our team.
Discuss legal requirementsCommon questions
Frequently Asked Questions
What does ThinkTrends offer for banks and financial services firms?
ThinkTrends offers agentic AI for financial crime and compliance: KYC onboarding review, alert investigation, transaction checks and regulatory report drafting. Every finding shows its evidence, a named person makes every decision, and every step is ready for examiners.
How is ThinkTrends different from ChatGPT Enterprise or Microsoft Copilot for financial services?
General-purpose assistants are not built for model risk management or examiner scrutiny. ThinkTrends runs documented, validated agents connected to your case and transaction systems, records the inputs, version and reviewer behind every decision and runs in your own environment.
Does a ThinkTrends agent close or escalate alerts on its own?
No. Agents investigate and recommend. An analyst decides each alert, and the reason is recorded with the evidence.
How does ThinkTrends fit model risk management?
Each agent is documented, validated and approved through your model risk process, then monitored for drift and overrides in production.
Can examiners see how a ThinkTrends decision was made?
Yes. Every decision keeps its inputs, the records it used, the agent version and the people who reviewed and approved it.
Where does ThinkTrends run for financial institutions?
In your cloud or data center, with production, challenger and research environments kept separate.
Is our data used to train AI models?
No. ThinkTrends uses customer data only to do the work, inside your own environment. Your data is never used to train, tune or evaluate a model.