Kram Control Manager

IFC / ICOFR / SOX control testing and AI-assisted control assurance.

Kram Control Manager brings structure to control testing — from RACM and evidence requests to sampling, tester-reviewer workflows, deficiency tracking and management reporting.

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The Problem

Control testing without a system is expensive and unreliable

📊
Testing managed through spreadsheets

Control testing trackers built in Excel become unmanageable across cycles, controls and testers. Version confusion is constant.

📧
Follow-up-heavy evidence collection

Testers chase control owners over email for population data and evidence. Delays accumulate and testing timelines slip.

📉
Incomplete population data

Population submissions are incomplete, inconsistent or unverified. Sampling logic is applied without validating the base data.

🎲
Inconsistent sampling logic

Sample size decisions vary across testers and cycles. There is no standard approach to frequency-based or risk-based sampling.

🔍
Weak reviewer visibility

Reviewers struggle to track which controls have been tested, which have exceptions and which deficiencies are open.

⏱️
Time-consuming management reporting

Testing status summaries, deficiency reports and management dashboards are prepared manually at the end of every cycle.

Core Workflow

End-to-end control testing in one structured system

01
RACM / Control Repository

Define or import your control library with objectives, frequency, risk linkage and ownership.

02
Year-wise Rollover

Roll over controls to a new testing cycle. Update ownership and testing scope as needed.

03
Assign Roles

Assign control owners, testers and reviewers to each control or control group.

04
Request Population and Evidence

Send structured requests to control owners for population data and supporting evidence.

05
Accept and Sample

Testing team accepts population data and generates samples based on frequency and risk logic.

06
Upload and Test

Control owners upload evidence. Testers perform testing and document observations.

07
Review

Reviewers work through their queue, review testing documentation and approve or return.

08
Log Exceptions and Deficiencies

Exceptions are escalated to deficiencies. Severity is assessed and remediation owners are assigned.

09
Management Dashboard

Real-time view of testing status, open deficiencies and control coverage across the cycle.

Product Versions

Control Manager grows with your maturity

Start with structured testing workflow. Add AI assistance when ready. Build towards portfolio-level control assurance intelligence over time.

Version 1Available

Control Testing Workflow

Structured end-to-end control testing workflow covering RACM, evidence requests, sampling, testing, review and deficiency management.

Capabilities
RACM / control repository
Year-wise control rollover
Process and control listing with counts
Control owner, tester and reviewer assignment
Population request workflow
Evidence request workflow
Data acceptance by testing team
Rule-based sampling using control frequency
Owner evidence upload
Tester testing workflow
Reviewer queue
Exception and deficiency logging
Management dashboard and reporting
Version 2Pilot

AI-Assisted Control Testing

AI assists testers and reviewers throughout the testing cycle — from control design review to evidence adequacy checks and deficiency drafting.

Capabilities
AI-assisted control design review
AI review of control descriptions for clarity and testability
AI suggestion of sample size based on frequency, risk and IFC logic
AI review of population data for completeness and unusual items
AI preliminary evidence adequacy check
AI flagging of missing or weak evidence
AI-assisted tester observation drafting
AI-assisted exception wording
AI-suggested deficiency severity
AI-generated testing status summaries
Version 3Roadmap

AI-Powered Control Assurance Intelligence

AI moves from assisting individual testing steps to providing portfolio-level control intelligence, pattern recognition and management reporting.

Capabilities
AI identification of control design gaps
AI comparison of similar controls across processes or departments
AI duplicate and redundant control identification
AI control rationalisation suggestions
AI mapping of controls to risks, assertions and financial statement areas
AI identification of high-risk controls for focused testing
AI analysis of recurring deficiency themes
AI remediation recommendation drafting
AI management summary generation
AI audit committee-ready reporting support

See Control Manager in action

Request a demo and see how Kram Control Manager can support your IFC / ICOFR / SOX testing programme.

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