On July 19, 2011, Aité Group released a new report on Reconciliation Solutions which examines some of the key trends in the reconciliation market and analyzes the capabilities of leading reconciliation solution vendors.

Aité predicts that the demand for additional functionality will drive spending for reconciliation solutions on a global basis – reaching US$520 million annually by 2014. Another trend that Aité predicts is that although US and European markets have the highest reconciliation spending, Asia will be evolving at a higher growth rate than before over the coming years.

The report profiles and compares reconciliation solutions from the following major players: Broadridge, Caswil, Cosmos, Fiserv, Electra, Milestone, SmartStream, SunGard, SS&C, and Sterci.  To purchase the report, please click here

Where Caswil differentiates from these other players is its distinctive Agile Conversion technology, which is a powerful data transformation engine that converts, clean, merge and enrich data so that they are reconciliation-ready and reconciliation friendly. Good data is at the heart of higher-automatch rates in reconciliations. Clients who are looking for a customized reconciliation solution to suit their workflow, who have multiple complex data sources to integrate, and who deal frequently with changing requirements arising from complex OTC derivatives, for example, would find Caswil solutions specially suited to their needs.

To contact Caswil, please write to us at info@caswil.com

An agile conversion process should have the following principles:

1. Responsive: Changing business requirements is an inevitable reality. Agile conversion harnesses change into competitive advantage.
Challenge faced: Automation creation can hardly keep up with changing requirements, and organizations are not agile enough to respond to change.
2. Collaboration-friendly: Business people and developers working together to create automation need to be empowered with the right tool for collaboration.
Challenge faced: Communication breakdown between business people and IT leads to the danger of project not meeting requirements.
3. Short-development cycle: Working automation should be the primary measure of progress, removing the need for testing and validation cycles.
Challenge faced: The long development cycle from getting business requirements to development, testing, validation and implementation leads projects to go over budget, as soon as roadblocks appear or complexity increases.
4. Flexible: Flexibility and simplicity should not be traded off as complexity increases.
Challenge faced: As data conversions get more complex, automation scripts and process get more complicated and less flexible. This compromises the flexibility of the organization to react to change.
5. Transparent: Conversions should be transparent, allowing automation breaks to be repaired on-the-fly.
Challenge faced: Data conversions are often a black-box, and organizations tend to over-depend on the same key individuals to repair automation breaks because they are the ones who created the automation.

Creating automation and straight-through-processing does not have to be a complicated and expensive process. Agile conversion is an innovative alternative approach to integrate multiple data sources into a single platform. Getting financial data to be ready for reconciliation and analysis is now made simple and straightforward with Agile Converter.

In addition, there are tools used to integrate data sources and link data-exchange between disparate systems. These tools go by various names, such as: mapping tools, data converters, data adapters, data aggregation, trade interfaces, ETL tools (extract, load, transform) and application programme interfaces (API). They differ in varying degrees of functionality and usability, and they come with different features and strengths.

The truth is there are often many manual workaround steps to fill the gaps that these tools cannot fulfill. These manual workaround steps are precisely the weakest link that decreases the agility of data processing. The existing approaches in the industry come with the following challenges:

1) Responsiveness – Organizations are often not agile enough to respond to fast and changing requirements. Automation creation can hardly keep up with requirements. A reason is that pre-built automation solutions are often not flexible enough. Any desired change has to rely on rounds of vendor upgrades, which may not meet your organization’s needs afterall. Customized solutions may be more flexible, but have other challenges such as the lack of transparency.

2) Collaboration – Communication breakdown between business people and IT developers is a common problem. In recent interviews with CTOs and IT professionals, they say that getting business requirements right is the weakest link in the process of automation creation, not the creation and modification of automation itself. The danger is that, after all the time and costs incurred, the project do not meet requirements.

3) Development cycle – Very often, by the time automation is implemented, requirements have changed. The development cycle from getting business requirements to development, testing, validation and implementation takes too long and too much resources. This is especially so when getting requirements right needs several iterations of revision. The chart below depicts the time and cost involved in creating and fixing automation. Projects tend to go over budget, as soon as roadblocks appear or complexity increases.

4) Flexibility – As data conversions get more complex, automation scripts and process get more complicated and less flexible. There is a high tradeoff between complexity and simplicity. Making changes to automation is often not simple enough, hence compromising the flexibility of the organization to react to change. On a separate note, although spreadsheets and macros may be highly flexible, the tradeoff is that spreadsheets are neither robust nor systematic.

5) Transparency – Data conversions are often a black-box – be it proprietary solutions or pre-built vendor solutions. There is often a lack of transparency in the creation of automation and conversion. Organizations tend to over-depend on the same key individuals to repair automation breaks because they are the ones who created the automation.

All of these challenges lead to the general belief that straight-through-processing is a hard goal to attain. However, we believe that optimized automation can be achieved if we are prepared to adopt a new paradigm to be more responsive to changes. In other words, a more agile process needs to be considered to adapt automation on-the-fly.

Increased regulatory requirements are changing the ways financial institutions must act in order to protect the investor public, prompting serious considerations in technology, operations, and infrastructure. Investors demand greater accountability and real-time information on their exposures. However, the crux of the problem in producing transparent and efficient reporting lies in the fact that financial firms are coping with multiple systems, trying to aggregate data across different silos, different locations, and different formats.

The options for aggregating data remain either manual and localized efforts, or outsourced to external vendors, giving away control of this critical link in the processing chain. Asset and wealth managers begin to realize that spreadsheets, while flexible, come with an inherent level of risk, and have become increasingly prone to inquiry by auditors and subject to regulation. PriceWaterhouseCoopers estimated that between 30% and 90% of all spreadsheets has at least one major error.

Adding to the mix of challenges is that aggregation of financial data becomes substantially more complex to automate these days as more complex instruments are traded, with little or no standardization from deal to deal. Processing complex alternative instruments also mean having to process data relating to varying lock ups, notice periods and settlement schedules – parameters that are constantly changing, which cause frequent exceptions and automation breakdowns.

According to Denise Valentine, senior Analyst with Aite Group, “Technology vendors must develop the next generation of investment accounting systems – a generation which serves a heightened sense of operational efficiency and risk management, speedier information flow, open architecture and highly scalable technology that helps meet today’s demand for transparent ad-hoc reporting required by regulators and investors alike.”

Caswil responds to this need of aggregation, reporting and investment management with its adaptive conversion technology, Agile Converter. For firms who are considering moving away from spreadsheet dependency, this technology retains the flexibility of spreadsheets and macros, while adding robust automation and multi-leveled security. Instead of relying on manual processes, writing macros, or writing scripts and programs to aggregate and clean data, firms are able to create conversion interfaces with Caswil’s adaptive conversion tool, at their desktop or a web-interface, to transform data from multiple sources, multiple formats into their desired target format(s) to be loaded seamlessly into their target system(s). Easy-to-install, Caswil modules require minimal resources to implement automated workflows right away. Just by entering parameters, users are able to create complex data conversions and automation without any programming knowledge.

In a recent Wall Street & Technology article, Valentine was quoted to say that any technology solution that proposes to streamline report aggregation needs to do two things: work across silos and establish automated workflows. Caswil financial data automation solutions do just that, and take a step further: by harnessing change into a competitive advantage.

Read more about Caswil’s adaptive conversion technology here.