AI-enabled assurance for banks
SeeEverything runs the whole QA operation for banks, from sampling and review to frontline remediation and coaching. Your reviewers, your AI, or both can do the checks. Leaders get the insights to keep improving, and the board gets real-time, evidence-backed views of KYC, conduct risk and customer outcomes.
Trusted by tier-one banks for over a decade. 100% customer satisfaction and recommendation rate.
The problem
A small monthly sample leaves most of the risk unseen.
Issues get logged, but rarely reach the person who can fix them.
Boards and regulators want evidence that the behaviour changed or the issue was fixed.
One system
SeeEverything follows every finding through to a fix, then shows the evidence that the change held.
SeeEverything digitises your existing QA frameworks, and AI-assisted checks handle the routine work so reviewers cover far more cases. Reviewers keep the judgement.
Root-cause analysis shows where each fix belongs: coaching for people, a redesign for process, or insight fed back into product. Coaching is triggered for the right person and prefilled from the transcript.
Cadence gives frontline leaders a consistent operating rhythm: daily huddles and weekly team meetings with a set agenda, so key messages land, actions are followed up and repeat issues fall.
The next review cycle confirms the change held.
Every kind of QA
Many QA tools cover one channel, usually recorded calls. SeeEverything runs every QA framework a bank has, across every business unit and channel, in one platform with one audit trail.
Works with the AI you already have
Detection tools find issues. SeeEverything makes sure something happens about them, because only after action is taken can results be turned into intelligence.
AI, data-driven or human
Specialised, but fragmented on their own
One hub coordinating QA, leaders and staff
Action turned into intelligence
One evidence-backed view for the board and regulator
The loop closes. Trends from Grow feed back into Detect as QA deep dives, framework updates and targeted initiatives.
AI and human review
Every bank wants to review every case, not a small sample. AI removes the cost barrier by checking every case. Your reviewers remove the trust barrier: they set the frameworks, calibrate the AI and confirm, adjust or override its answers, with every decision on the audit trail. Move up as trust grows, without changing platform.
Sample files are ingested, cases allocated to reviewers or picked from a shared queue, and reviewers complete every check.
Best for new frameworks and judgement-heavy casesData in the sample file answers some questions at import, and reviewers complete the rest.
Best for high-volume reviews with structured dataEvery question is answered as the sample file is imported, and reviewers confirm, adjust or override.
Best for mature, rules-based checksYour own AI agents complete QA through a secure integration, with the same reviewer oversight.
Full coverage of interactionsBest for banks with their own AI investmentsIf an AI model is withdrawn, paused or fails a model-risk review, QA carries on at a lower level of automation, with the same frameworks, data and audit trail.
Banks use SeeEverything as their system of record in regulator-in-the-room sessions.
Change AI models as the market moves, without losing your frameworks, data or audit trail.
How it works
Eight steps in one platform. Most AI QA tools stop at step 3. SeeEverything follows every finding through to a changed behaviour.
Your QA operation, ready to run
Your existing QA forms, checklists and policies go in as they are, fully deployed in under 90 days.
Ingest sample files, allocate work to reviewers, or let them pick from a shared queue.
From finding to changed behaviour
The platform surfaces the risk and your reviewers make the call, at any level of automation.
Every finding gets an owner and a frontline dashboard. QA validates each action before it closes.
Coaching closes skill gaps, and root-cause fixes go to the process and product owners.
Cadence routines and leader dashboards give clear visibility and accountability.
Solve issues across the whole business
Executives, risk teams and team leads see one picture of conduct, capability and customer outcomes.
When an issue shows up across teams, launch QA deep dives, focused coaching and knowledge updates at scale, then track whether the trend moves.
Your data stays yours. Client data is never used to train AI models.
Customer stories
How a large regional bank lifted QA productivity and cut errors, without adding headcount.
“SeeEverything helped significantly increase the efficiency and effectiveness of our QA teams.”
Value calculator
Enter your headcount and average cost per person to see how much capacity SeeEverything could release across your teams.
| Team | Headcount | Average annual cost per person | Capacity released |
|---|---|---|---|
| QA reviewersUp to 60% of time released · automated and AI-assisted checks | FTE | ||
| Frontline and operations staffUp to 5% of time released · one system in place of spreadsheets and emails | FTE | ||
| Team leaders and managersUp to 15% of time released · one system, plus faster coaching | FTE |
Capacity released = headcount × average annual cost × share of time released.
QA reviewers, 60%: automated and AI-assisted checks take on routine review work.
Frontline and operations, 5%: staff whose work is reviewed spend less time on QA admin, because SeeEverything replaces spreadsheets and emails.
Leaders, 15%: the same system efficiency, plus faster coaching, with notes prefilled from transcripts.
Default costs are estimates: salary plus employer taxes, pension and benefits. Time released is based on SeeEverything client averages. Actual results vary.
