Are you ready to fundamentally simplify & strengthen data exchange?Request Now
Problems related to poor data quality are common to organisations across the globe. A 2016 estimate by IBM put the cost of bad data in the US alone, at $3.1 trillion annually. These costs reflect the “Rule of 10” developed by Thomas Redman, which states that “It costs ten times as much to complete a unit of simple work when the data are flawed in any way as it does when they’re perfect”. This poses real challenges for financial regulators who are dependent on data which is fit for purpose. The particular difficulty faced by regulators is that the data received from regulated entities is variable in quality. The ability to validate and ensure quality at source would be hugely valuable. In some cases, regulators have been known to spend up to four months checking, validating and correcting data. Meanwhile, many returns from regulated entities are filed quarterly and some are monthly. In this extreme case it leaves little or no time for analysis of the data.
Vizor has developed a solution to help regulators deal with this issue. The solution has been developed as a result of the company’s extensive experience working with regulators across the globe and places the onus for the supply of good quality data firmly on the supervised institutions.
The solution automates the checking and validation process at the point of receipt. Where data is found not to meet the required standard, the filing is returned to the institution concerned for correction. Within 18 months of implementation of the Vizor solution, the vast majority of data being collected by regulators is both on time and of the required quality.
This has the power to put the regulators concerned up to 16 weeks ahead of where they might have been in terms of the process, and enables the redeployment of staff to higher value activities. These activities can include regulatory analysis and testing for solvency, capital adequacy, liquidity and so on.
Poor data quality is an issue for organisations across all sectors worldwide. In 2016, IBM estimated the cost of bad data in the US alone at a staggering $3.1 trillion annually. These costs mainly relate to the time the organisations spend on checking and correcting data received. Internationally renowned data expert Thomas Redman developed what has become known as the “rule of 10”. “It costs ten times as much to complete a unit of simple work when the data are flawed in any way as it does when they’re perfect”, the rule states. This is particularly the case when the organisations involved strive for data to be 100% fit for purpose at the point of receipt. This applies to sectors like healthcare, food processing, energy utilities, and financial regulators. There is little margin for error or delays in terms of data quality in such cases.
For data to be useful, it must be trustworthy. Data is complex. Very often the information can be correct, but the format is wrong. The right data can be input in the wrong field. Simple arithmetic errors can occur. However, without the systems in place to ensure quality and accuracy at the point of receipt, it can be difficult to trust data from external sources.
This places a particular burden on financial regulators who rely on vast amounts of data supplied by supervised entities in order to carry out their role and function.
Vizor is helping regulators around the world deal with this burden. The Vizor solution has been developed as a result of the company’s extensive experience working with regulators across the globe, including the UK, Canada, Saudi Arabia, and increasingly in the developing world. In addition, the Vizor team is made up of experienced ex-financial regulators and successful IT industry veterans who share vast expertise in the provision enterprise-class software to the supervisory sector.
The Vizor solution automates the checking and validation process at the point of receipt. Where data is found not to meet the required standard the filing is returned to the institution concerned for correction. Implementation of the Vizor solution sees the quality of filings improve quite dramatically over time as the regulated institutions take responsibility for ensuring the data filed is right first time.
The way in which the issue of poor quality data manifests itself poses real challenges for regulators. In the current situation, the process on receipt of data is to check and verify it for errors and then to correct it.
This leads to the regulator spending inordinate amounts of time checking and validating data thereby creating critical disruptions to the information supply chain.
In some cases, regulators have been known to spend up to 16 weeks chasing, checking and validating data.
For quarterly reporting schedules, this means that regulators may already be three weeks into the next reporting period by the time the last batch of returns have been validated and is ready for analysis.
This can lead to an imbalance in the time spent between collecting the data and time spent analysing it which in turn makes it very difficult for the regulator to form a timely view as to whether the institutions are carrying out their business in the manner expected. This places constraints on the ability of the regulators concerned to carry out their primary role and function of supervision and managing risk in the sector.
It also places an enormous cost burden on regulators. The “Rule of 10” mentioned earlier means that the regulators’ costs and workload in this area could be reduced by up to 90% if the institutions creating the data were to supply it to the required quality standard.
Even the most sophisticated systems will not in themselves fix the issue of bad data. Vizor recognises this and this is where the solution differs from others. Vizor technology enables and supports the behavioural changes needed to improve data quality. The solution also advocates and encourages an approach to tackle the data quality issue at source.
The onus for the supply of good quality data is placed firmly on the supervised institutions
The Vizor data collection platform also makes it easier for institutions to file returns in the format required by regulators. This is achieved through the provision of a number of options accessed through a web-based portal for institutions to file returns. The institutions submit the data and the application of rules engines ensures a high degree of quality from the very outset.
In addition, help screens and other aids assist the institutions and their staff to understand precisely what is required of them.
Over time, the institutions can graduate from a more manual data-entry based approach to file upload and machine-to-machine connectivity.
The Vizor Software solution is compatible with many formats including Excel, XML, and XBRL. This enables regulators to accept returns from all supervised entities without the need for expensive and time-consuming conversion operations or potentially error-ridden re-keying of data.
Experience has shown that within a year to 18 months of implementation of the Vizor solution the vast majority of data being collected by regulators is both on time and of the required quality.
This has a transformative effect following implementation at central banks and financial regulators. In essence, it can put them 16 weeks ahead of where they would be normally. Instead of being in a position where the previous quarter’s returns are still being checked and validated when they start collecting the current quarter’s, they are now able to commence analysis immediately.
Immediately upon receipt of the data the regulator is able to compare it to returns from the previous quarter. The Vizor rules engine triggers alerts for anomalies, inconsistencies, or potential regulatory breaches.
Trends or events which might point to risky behaviour or other issues worthy of attention are captured at the point of collection rather than some months later.
Central bank staff can be redeployed away from data checking, validation and correction to more high-value tasks such as regulatory analysis and testing for solvency, capital adequacy, liquidity and so on.
The Vizor solution flags potential problems while the experts in the regulator are able to use their skills and experience to drill down deeper into the data.
This also allows for a greater level of risk-based supervision. Once the data collected is consistently of sufficient quality, much greater focus can be given to systemically important and other large institutions.
The higher quality data collected from institutions can be sent automatically to the Vizor data warehouse solution which in turn allows for high-quality business intelligence analytics to be performed on historic and current data as it becomes available.
Another important benefit is the empowerment of regulator employees. They are freed to do the jobs they are trained and qualified for, the supervision of financial institutions. This aids staff recruitment and retention, thereby further contributing to pool of talent and expertise available to regulators. The net result is better regulation and a safer financial system.