Data Management Efficiencies

Evidence and data. The interviewees shared that their organizations were able to manage data much more efficiently with Quantexa.

• The head of technology and innovation at the telecommunications operator said: “We had all this data, but it was very difficult for us to do entity resolution. We had lots of copies of customers called by different names. Quantexa helped us to have quality data.”
• The global head of financial crime detection at a financial services organization said: “Previously, we had to treat records in duplicate fashion and identify those records. Now, we have seen a 50% reduction in processing times; half the work is now done by machines.”
• The AML transaction monitoring lead at a financial services organization said: “We are finding issues that we could not find before. We have been able to significantly reduce data inefficiencies. … Entity resolution has been very beneficial. We now get UBO (ultimate beneficial ownership) details. We can understand the networks and get all contact data in one place so we can understand who a shareholder is and what the network looks like. By combining transaction monitoring and screening, we can get one opinion about one customer. We get the full view.” The interviewee said graph analytics capability enables complex relationships to be represented to support better and faster decision-making.

Modeling and assumptions. In order to quantify this benefit, Forrester assumes the following about the composite organization:

• Prior to its Quantexa investment, the composite organization required 100 FTEs to spend 20% of their time managing the data. These FTEs included various roles including database managers, data scientists, data analysts, and IT engineers.
• With Quantexa, the effort the composite requires to manage data reduces by 15% in Year 1 and also in Year 2 because the number of duplicate records is reduced by the same amount. In Year 3, this reduction is 20% as the composite’s data processes improve and it adds additional use cases.
• The fully loaded annual salary of a core data FTE is $200,000.
• The composite has 400 advanced users of data systems in Year 1, 500 in Year 2, and 700 in Year 3.
• With Quantexa, each advanced user saves 4 hours per week because they no longer need to access multiple data sources and systems or consolidate the data from these different sources, and because the duplicates are eliminated, so they no longer have to spend time correcting errors from inaccurate data.
• The average fully loaded annual salary of an advanced data user is $150,000.
• Forrester applied a 50% productivity conversion factor because although employees may save time, it’s assumed that only half of that is put back into productive use.

Risks. The impact of this benefit can vary by organization depending on:

• The quality of the data and number of duplicates.
• The number of advanced data users, which may vary depending on the company and the industry.
• The salary rates of core data FTEs and advanced data users.

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 $7.9 million.

Operational Efficiencies

Evidence and data. Interviewees said improving operational efficiencies was one of the most significant areas of benefit for their organizations.

• The AML transaction monitoring lead at a financial services organization shared: “Previously, when we used rule-based systems, 99% of alerts were false positive. So, an alert is created, but there’s nothing there and a lot of time lost. Now, escalation to second line has gone from 1% of alerts to 30%.”
• The chief data officer at a financial services organization said: “We have a more precise view of our client population, which results in less time managing and cleaning data. So, we are operationally more efficient. We reduce false positives and enable more refined onboarding.”

Modeling and assumptions. In order to quantify this benefit, Forrester assumes the following about the composite organization:

• The composite organization serves 2 million business customers around the world, and they are categorized into three levels of risk: 1) 80% are low-risk, and their data is checked every five years; 2) 15% are medium-risk, and their data is checked every three years; and 3) 5% are high-risk, and their data is checked annually.
• Prior to its investment in Quantexa, the composite performed an average of 520,000 KYC checks each year. With Quantexa, this is reduced by 30% because there is a 15% to 20% reduction in duplicate records and because Quantexa provides alerts when records need to be checked instead of needing them to be updated with a regular, rules-based system, this further reduces the total number of checks required. Each review takes an average of an hour.
• Prior to its investment in Quantexa, the composite received 96,000 false-positive alerts annually, and each requires an hour to process. With Quantexa and after implementing the KYC use case, data quality and accessibility improves, so the number of alerts declines by 5% in Year 1. From Year 2, the addition of AML, fraud management, and financial crime use cases results in a 65% reduction in false-positive alerts. These time savings are negated to some degree because those remaining alerts require more time to investigate.
• The fully loaded hourly rate of an investigation analyst is $72.
• Forrester applied a 50% productivity conversion factor because although employees may save time, it’s assumed that only half of that is put back into productive use.

Risks. The impact of this benefit can vary by organization depending on:

• The initial ratio of low-, medium-, and high-risk customers, which may result in a fewer KYC reviews.
• The initial level of duplicate records and/or false-positive alerts.
• The time per KYC review and/or alert investigation.
• The salaries of relevant employees.

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 $14.8 million.

Reduced Risk/Improved Compliance

Evidence and data. Each interviewee said a key benefit for their organization was reduced risk and improved compliance. This was particularly the case for those organizations that implemented use cases such as KYC, AML, fraud, financial crime, and risk management, and the deputy director in the public sector said it was especially impactful for their organization.

It is also notable that interviewees said this benefit was not only driven by having better tools for investigative analysts, but also because a lot of time was freed up from the reduction in false positives, improved data accuracy, and a reduction in the number of data sources and tools they previously needed to access.

• The deputy director in the public sector said: “We were able to build a cross-bank network in which banks not only have access to their own customer data, but also others. So, if you have all of it, you are much better able to identify fraud and other issues. We have been able to prevent and recover £16 million.”
• The managing director at a financial services organization explained: “The power is in the resolved entity data. We reduce risk of identified transactions and can find patterns of activity that were previously undetectable, so we are reducing our overall risk. We found 10 times the number of cases just in the pilot. It’s like a CT scan vs. an X-ray.”
• The chief data officer at a financial services organization explained: “With Quantexa, I can start looking at a 360-degree view of a relationship and the behaviors around it, and I can start doing trend analysis because it’s not only an absolute behavior; it’s a change of behavior because our regulators around the world expect us to understand the sources and uses of funds. Regulators expect that when you open an account … we understand where the money comes from, we understand the nature of your business, and we are able to monitor how you’re using our firm and highlight suspicious activity. If it rises to the level of an incident, we report that to our regulators.”

Modeling and assumptions. In order to quantify this benefit, Forrester assumes the following about the composite organization:

• With Quantexa, the composite avoids many matters requiring attention (MRAs) and matters requiring immediate attention (MRIAs), which are issues that financial regulators require that a financial services organization addresses; they take time and resources to remediate. It avoids 10 such events in Year 1 and 20 in years 2 and 3 as additional use cases are added (notably AML, fraud, and financial crime).
• Remediating each of these tasks requires an average of 80 hours of effort from a compliance officer or similar role.
• The average annual salary of a compliance officer is $200,000.
• The composite identifies and avoids 25 additional fraud cases in Year 1, and this number grows to 100 in years 2 and 3 as additional use cases are implemented.
• With Quantexa, the composite avoids 100 hours of remediation effort per fraud case, and for each fraud case avoided, the composite does not need to pay reimbursement fees of $100,000.
• With Quantexa, the composite reduces its regulatory fees, including those related to fraudulent activity. In Year 1 it avoids paying fees of $500,000, and this increases to savings of $2 million in years 2 and 3.

Risks. The impact of this benefit may vary by organization depending on:

• The organization’s preexisting risk posture.
• The number of fraud cases discovered, which may lead to a lower average reimbursement rate and/or could require less remediation effort.
• The amount of remediation effort saved by avoiding MRAs and MRIAs.
• The relevant salary rates.

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 $19 million.

Incremental Profit From Improved Customer Intelligence

Evidence and data. The interviewee from the private sector said its organization planned to implement a customer intelligence use case. The head of technology and innovation at a telecommunications operator said this was their organization’s principle and initial use case while interviewees from financial services organizations said this use case tended to follow data-focused fraud and KYC-related use cases.

• The head of technology and innovation at the telecommunications operator said their organization implemented Quantexa to provide it with a better view of its business customers. It started with small and medium-sized enterprises by enabling sales representatives to easily see a full picture of the organization’s customer in terms of the products and services they use across multiple lines of business in a single view. Representatives previously had to access 15 sources of data. Not only did Quantexa save them a lot of time, but it also enabled them to identify quality opportunities and propose better solutions.

  The same interviewee said: “Through better upsell, cross-sell, and new-customer acquisition, we expect a revenue increase of 3% to 5%.”

  The organization also plans to build out its customer intelligence capability not only in key regions, but also in other segments including enterprise customers.

• The chief data officer at a financial services organization told Forrester: “Customer intelligence is on the roadmap as a use case. It’s also about being more efficient so that you can serve customers better and find new opportunities faster.”
• The managing director at a global financial services organization said: “We can bring all the customer data into a single view. In terms of additional upside, we can expect a revenue increase of 3% to 5% in those segments where this is implemented.”

Modeling and assumptions. In order to quantify this benefit, Forrester assumes the following about the composite organization:

• The composite implements its customer intelligence use case in Year 2, and it goes live at the beginning of Year 3.
• The composite derives 20% of its revenue from institutional banking.
• The composite implements its customer intelligence use case in 25% of its global footprint. Therefore, in Year 3, this benefit impacts $2.5 billion in revenues.
• The composite’s revenue uplift is 3%.
• The composite’s operating profit margin is 10%.

Risks. The impact of this benefit may vary by organization depending on:

• The proportion of revenue impacted, which could be lower if, for example, the portion of revenue in this segment is lower.
• Whether or not the organization’s prior setup was already efficient and effective.
• The organization’s operating profit margin.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $4.8 million.

Cost Savings From Retiring Legacy Solutions

Evidence and data. Many interviewees shared that their organization has been able to simplify its technology stack and reduce costs by retiring legacy solutions. These eliminated costs include fees for vendor software, but also the related costs of maintaining the applications. In some cases, costs also included custom, internally built solutions that can be costly to maintain and upgrade.

• The global head of financial crime detection at a financial services organization said: “We will be able to replace many — perhaps 40 or more — database instances that we no longer want to replicate the data. This will enable us to reduce the amount of infrastructure and human resources and also monetize data assets.”
• The AML transaction monitoring lead in financial services told Forrester: “We will be able to decommission three legacy systems: one from a vendor and two that were custom-built. That will be $2 million in savings altogether, and that includes licensing and the cost of maintaining those systems in-house.”

Modeling and assumptions. In order to quantify this benefit, Forrester assumes the following about the composite organization:

• With Quantexa, the composite is able to save $1 million in legacy solution costs in Year 1.
• In Year 2 and as additional use cases are implemented, the composite decommissions additional legacy technology including a point solution transactions monitoring tool. This increased the cost savings to $1.5 million.
• In Year 3, following the implementation of the customer intelligence use case, the composite decommissions additional databases. As a result, the total legacy technology cost savings increased to $2 million.
• The composite also sees an additional 10% in cost savings each year from no longer needing to maintain, upgrade, and support these legacy systems.

Risks. The impact of this benefit may vary by organization depending on:

• The organization’s previous spending on legacy systems.
• Internal delays and challenges to decommissioning legacy systems.
• Delays in legacy technology decommissioning because of multiyear contracts or other dependencies.

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 $3.6 million.

Unquantified Benefits

Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:

• Flexible and simplified architecture. Interviewees said the Quantexa Decision Intelligence platform provides the data foundation for a wide range of use cases and that this not only reduces complexity, but also brings efficiency by enabling multiple use cases to leverage the same data platform. By adopting this approach, interviewees said their organizations can streamline their operations, avoid redundant data silos, and enhance their overall decision-making capabilities. This flexible architecture can empower organizations to prioritize and implement use cases according to their specific needs.
• Strategic relationship to fight financial crimes. Interviewees said that by cross-sharing data with other entities and industries, their organizations can help fight financial crimes such as fraud, scams, and money laundering, which can result in more robust and comprehensive defenses against these illicit activities. Interviewees’ organizations are also able to effectively combat these threats on a much larger scale and pool their resources and knowledge for a collective defense.
• Improved ability to investigate complex AML, fraud, and financial crime cases. Interviewees said that with Quantexa, their organizations are better equipped to effectively tackle and resolve complex investigations. They said they now have a better view of customers and their surrounding networks and that they no longer need to access multiple data sources. Furthermore, they avoid much of the time previously spent looking into false positives, which frees them up for more valuable investigative tasks.
• Enabling AI success. Interviewees said improved data quality is an important foundation for the application of AI. If machines learn from inaccurate or inconsistent data, their output will be suboptimal. Conversely, good quality data means they will provide higher quality output.
• Improved relationship with regulators. Interviewees from organizations in highly regulated industries — especially financial services — said their firms have been able to improve their compliance postures. As a result, their relationships with regulators is stronger. The global head of financial crime detection from a financial services company mentioned: “We have better relationships with regulators. We can show them innovation and continuous improvement. They like our forward-thinking approach.”

• Better customer onboarding and customer experience. Interviewees said that by having a complete and integrated view of their customers, they are better able to serve them. This is particularly the case for customer intelligence use cases in which sales representatives can quickly see all the different links with a customer across different lines of business to provide better service, identify opportunities more easily, and avoid misaligned sales communications. Furthermore, for KYC-related use cases, the implementation of Quantexa also streamlined customer onboarding and allowed organizations to avoid unnecessary requests for information or regular data updates.

  The chief data officer at a financial services organization said: “Another benefit is faster and more efficient onboarding because you have better KYC and automated systems. Certainly, it will also contribute to improved customer experience because you have a better view of the customer.”

• Improved employee experience. Interviewees said Quantexa significantly improved the employee experience for many within their organizations — particular those investigating fraud. By automating and streamlining manual and repetitive tasks, Quantexa effectively removes the burden of mundane and monotonous work from employees. Furthermore, employees no longer need to access multiple systems to find and collect data, which can be time-consuming. Inteviewees said that previously, fraud investigation analysts would find an average of only one case out of 100, but that this is reduced to perhaps one out of three as the number of false positives is significantly reduced.

Flexibility

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

• Ability to support multiple use cases from one platform. There are multiple ways in which a customer journey can develop. Typically, it will start with an initial use case as foundation, such as entity resolution or KYC, after which additional use cases such as fraud management, anti-money laundering and risk management can be added. While the head of technology and innovation at the telecommunications organization said customer intelligence was the initial use case for their company, each of the interviewees in financial services said this was a future focus for their organizations.

  Interviewees said these additional use cases are much easier and faster to implement because the data platform on which they sit has already been implemented and working as the foundation to enable data fabric for continuous decision intelligence. Only minimal adjustments or integrations are then necessary. Furthermore, no additional costs are incurred in needing to manage additional data platforms or sources and much of the data has already been cleaned and made more accurate. (Please refer to the graphic.)

• Expanding to additional business lines and/or regions. Several interviewees’ organizations initially implemented Quantexa in one region and had plans to expand to others. For example, the head of technology and innovation at the telecommunications operator said their organization started in one European country and planned to mirror the effort in other countries.

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Appendix A).