The Total Economic Impact™ Of Silent Eight Customer Screening Suite

Improved Investigation Efficacy

Evidence and data. The interviewee said Silent Eight lowered match rates, automated alert adjudication, and reduced manual work while allowing their organization to screen conservatively and providing an audit trail for human oversight. This helped Silent Eight improve investigation efficacy. Interview evidence also indicated that Silent Eight investigated and adjudicated alerts within predefined risk and policy boundaries through functionalities specific to name screening. The interviewee observed the following changes driving investigation efficacy:

• Improved efficiency with automated screening and adjudication. The interviewee said that the prior homegrown solution produced match rates of about 15%, which drove high alert volumes and manual workload. With Silent Eight, the match rate dropped to 7% or 8%. Silent Eight then automatically adjudicated between 40% to 70% of matched alerts depending on data quality and client policies. This removed a large share of alerts before human review was required.

• Advanced matching and learning capabilities. The interviewee described functionalities that differentiated Silent Eight, noting Silent Eight offered “more elastic and the more flexible name matching capability that supports transliteration” and that its adjudication capabilities “learn from previous decisions and so that has helped to simulate, mimic, and automate the investigative steps and process that analyst would also go through.”

• Improved effectiveness while maintaining conservative risk appetite. The interviewee explained that their organization deliberately applied conservative screening thresholds to ensure potential risk was not missed, while relying on automation to resolve false positive alerts without manual review. As the interviewee stated, “We cast a very wide net [with Iris], make sure that we try to capture everything that we need to capture from our risk appetite perspective but then use basically secondary information to dispose of what was caught as part of the process.”
  The interviewee explained that current adjudication levels reflected a policy choice rather than technological constraints, “The firm has chosen to be very conservative from a risk appetite standpoint, so to catch more and then adjudicate later rather than running the risk of missing something,” while noting that higher adjudication levels are technically achievable: “I’m very confident that we can get to a much higher level of adjudication of 80% to 90%. This is just a question of the business and regulatory flexibility to come along.”

• Explainable and intuitive analyst case review experience. The interviewee described how the solution facilitates a better analyst experience: “Silent Eight comes with a very high degree of transparency and easy to understand setup so people can understand and then completely explain the decision. ... The information is presented in a nice, easy-to-use way inside the case management system. After getting used to the environment, it’s very fast for them to authenticate the alert, between a minute and 5 minutes max depending on the complexity.”

• Elevated analyst focus on complex investigations. By automatically adjudicating low-risk alerts with machine learning, Silent Eight shifted analyst effort toward alerts that require deeper human judgement. The interviewee explained: “[With] the adjudication capabilities in Iris and the ability to learn from previous decisions ... that has helped simulate, mimic, and automate the investigative steps and process that analyst would also go through. L1 and L2 teams are now merged as we pretty much eliminate L1 [tasks] entirely.”

Modeling and assumptions. Based on the interview, Forrester assumes the following:

• The organization screens a portion of the total customer base per month, growing from 920,000 per month in Year 1 to 2 million per month in Year 2 and 2.5 million per month in Year 3.

• The match rate of the homegrown solution was 15%.

• With Silent Eight, the organization observes a match rate of 8% in initial screening. Of this percentage, between 40% to 60% are automatically adjudicated. This produces an effective match rate of around 4%.

• The remaining are flagged for human review, each requiring 2 minutes of an analyst’s active attention.

• Before Silent Eight deployment, the average fully burdened hourly rate for an analyst was $19. This accounts for additional costs an employer incurs in additional to base salary (benefits, taxes, equipment etc.) and is representative of the markets these analysts operate in.

• With the Silent Eight deployment, the organization merges L1 and L2 analyst teams and allocates them to higher-value work, resulting in a slightly raised fully burdened hourly rate. After Silent Eight deployment, the average fully burdened hourly rate for an analyst is $21.

• A productivity recapture rate of 100% is applied as the employees have become more productive with automation, having avoided manual effort that they would otherwise have needed without Silent Eight.

Risks. Factors that may impact the value of this benefit include:

• Tools previously used and their performance.

• Labor cost of analysts.

• Match rates. This varies depending on risk appetites, language complexity, and market-specific characteristics.

• Automated adjudication rate. This varies with data quality. Risk appetite and policies also determine how conservatively or aggressively organizations rely on automated adjudication.

• Growth and replacement context. This scenario models fast-growing environment, comparing net-new volumes that grow significantly overtime against a would-be scenario in which the organization maintains the status quo. In scenarios where organizations have already reached large, steady‑state screening volumes and are replacing an existing enterprise solution rather than scaling from lower volumes, the achievable productivity recapture rate may be lower than modeled (time savings entailing a partial productivity recapture).

Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.9 million.

Streamlined Screening Tool And Policy Management

Evidence and data. Silent Eight eliminated the need for the interviewee’s organization to maintain legacy screening tools. It also reduced the effort required to tune policies by replacing manual, reactive optimization with a system that learns from prior decisions.

• Eliminated legacy screening tool maintenance. Silent Eight replaced basic homegrown solutions that required ongoing manual upkeep and offered limited tuning flexibility. Consolidating screening and adjudication into Silent Eight removed the need to maintain separate legacy tools and infrastructure.

• Continuous performance improvements enabled with a feedback loop. The interviewee said that their organization’s prior homegrown solutions required frequent tuning, often twice per month, to manage high false-positive rates. With Silent Eight, policy tuning was needed far less often. The interviewee noted that a feedback loop in Silent Eight continuously learned from analyst decisions: “We could optimize the adjudication capabilities from the beginning. Iris’ ability to learn from previous decisions has helped to simulate and automate the investigative steps and process that analyst would also go through.”

• Lower internal effort to update screening logic. The interviewee explained that updates to risk appetite and policy settings are now faster and more targeted, typically completed in a few rounds within a single day when new lists or sources were introduced. With the prior tool, each tune required less time mainly because there were limited configuration options; with Silent Eight, their organization could make more meaningful adjustments with less ongoing effort.

Modeling and assumptions. Based on the interview, Forrester assumes the following:

• The legacy, homegrown solution required 50% of an IT FTE’s time to maintain, amounting to 1,040 hours based on a 2,080-hour work year. This efforted is eliminated as the solution is replaced by Silent Eight upon its go-live.

• With the legacy solution, the organization had to constantly adjust policies at about a biweekly cycle. With Silent Eight, policy tuning occurs only twice per year with more iterations per tuning cycle but fewer cycles overall.

• The productivity recapture rate is 50% to account for human tendency to direct only part of the time saved back to productive work.

Risks. Factors that may impact the value of this benefit include:

• Prior technology landscape.

• Regulatory environments that an organization operates in and requirements for policy adjustments.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $56,000.

Unquantified Benefits

The interviewee mentioned the following additional benefits that the organization experienced but was not able to quantify:

• Strengthened regulatory confidence. The interviewee expressed confidence in Silent Eight’s screening effectiveness and outcomes: “The screening solution is very solid, very robust. We have a very high comfort level of it catching the right things for us.”

• Improved transparency and explainability. The interviewee highlighted Silent Eight’s ability to support explainable decision-making: “One of the things that is I like a lot about the way silent data operates is the transparency. When you have machine learning and AI components inside your processes, you need to be able to explain it. Iris stands out in terms of transparency and the oversight it enables.”

• Improved client experience through fewer escalations. The interviewee said that their organization’s more robust name screening capabilities reduced client friction: “When you have fewer false positives, you reach out less often — to block transactions or to raise them with regulators. When you raise something, you know that it is worth it.”

• Increased continuous improvement through cross-client learnings. The interviewee welcomed updates about platform enhancements and policy optimization, noting, “When [Silent Eight learns] something from their client base, they come back to us and say, ‘Here’s an opportunity.’”

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement CSS and later realize additional uses and business opportunities, including:

• Strategic flexibility and future-proofing. The interviewee described Silent Eight as a long-term platform choice: “We made Silent Eight the strategic screening and alert adjudication solution for our strategic stack. ... It works with any source and vendor on the list side and the reference data side.”

• Scale without proportional cost increase. Silent Eight enabled the interviewee’s organization to handle materially higher screening volumes and expand coverage without linear growth in operational effort or cost. The interviewee indicated that scaling under the legacy would have significantly increased false‑negative risk and operational burden, making expansion substantially more difficult to manage. Looking ahead, the interviewee shared plans to scale deployment to additional use cases, markets, and clients: “We want to scale [use of Silent Eight] far and wide. In the next phase, we go into PEP. Our aim is to go from serving one market to 20 markets.”

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).