Andreas Burner, CTO and Head of Product Management at SmartStream
Data may be today’s gold, but for some firms it is still a burden rather than a blessing. Andreas Burner, CTO of SmartStream, believes that intelligent automation transforms data from an encumbrance into a valuable strategic asset.
Data has become the lifeblood of the financial industry and capitalising on it is critical if firms want to win the battle for market share. Yet for some companies, what should be a treasure trove undermines their competitiveness rather than contributes to it.
So why has data become such a double-edged sword?
Information now flows around in vast quantities and dealing with the sheer volume of it has become a challenging task. Data circulates in many different formats, including unstructured ones such as PDFs, making it difficult for institutions to ingest it into their systems and process effectively. A lack of standardisation in the way financial information is communicated adds further complexity – consider, for example, the varied methodologies used by individual data vendors to identify financial instruments.
Low quality data is another pain point. Businesses are constantly hindered by inaccurately captured, incomplete, out-of-date, inconsistent, duplicated or redundant information. This is not just troublesome to deal with but significantly affects firms’ earnings. A recent Gartner survey found that it costs organisations an average of $12.9 million per year, while earlier research (MIT Sloan Management Review) put the bill at 15% to 25% of revenue for most companies.
This also creates other side effects. It prevents businesses from understanding market trends and customer preferences, denying them the opportunity to offer new products and services. It also hampers regulatory compliance, while negative customer experiences resulting from incorrect information are likely to engender mistrust towards an organisation and damage its reputation. Furthermore, operational efficiency is affected – tackling shoddy or missing data involves huge amounts of wasted staff time.
In addition, inaccurate data impacts decision-making, resulting in flawed insights and bad strategic choices. There are huge implications for risk management, too: risk models built on faulty data, for instance, can lead to financial institutions losing millions of dollars.
Air, SmartStream’s cloud-native, SaaS, data automation and intelligence platform, has been designed to address these challenges. It provides financial institutions with a low cost, scalable and secure environment in which they can manage their data effectively. It offers firms the potential to lower operating overheads, alleviate their technology burden, reduce risk, improve accuracy and enhance customer trust, enabling them to increase competitiveness, and to become more resilient and adaptable in the face of future change.
The platform, which is built on the latest technologies, harnesses AI and machine learning to process data from multiple sources. It ingests information in a variety of formats, including unstructured ones such as PDFs, and deploys AI-based techniques to enrich, cleanse, aggregate and match inflowing details. A co-pilot feature assists users to manage any resulting exceptions.
Importantly, Air takes a very different approach to traditional systems, which depend heavily on the quality of the data they receive. Once information has been fed in – which can be done quickly and easily by business users, allowing self-service – Air employs AI-based techniques to address flaws rapidly, preventing faulty data from entering other applications and causing exceptions downstream.
Using intelligent automation to redress data inadequacies represents an attractive alternative to current practices. At present, firms expend vast amounts of effort carrying out manual validation, correcting errors and searching for accurate information. The bill for these activities has become immense – experts estimate that handling data quality issues costs companies between 10% and 30% of revenue – meaning that finding a more cost-effective way of working is now imperative.
Air utilises AI-driven algorithms to reconcile any data structure, permitting rapid pinpointing of exceptions and removing the need for laborious manual file comparisons. Air makes use of Affinity, SmartStream’s observational machine learning technology – which learns from the way human reconcilers correlate records – to further enhance matching.
Advanced reporting provides detailed, real-time management information, allowing managers to promptly assess operational health, rebalance workloads and address inefficiencies. Sophisticated analytical tools also empower firms to achieve valuable business insights, enabling them to unlock the hidden potential of the data they hold.
Two powerful modules, Air Data and Air Cash, automate activities that would otherwise require significant time and manual effort. Air Data automates time-consuming cross-checking between different systems, while Air Cash is designed to handle a wide range of cash reconciliations, from simple to highly complex cases, with speed and ease.
In addition, the solution is highly scalable, fast, cost-effective to operate, and capable of adjusting rapidly to fluctuations in business volumes. It also offers an extremely secure environment in which to operate.
In conclusion, financial institutions are often unable to exploit their data effectively, and so fail to extract the operational and commercial understanding needed to improve efficiency, control costs and raise profitability. To fight back, firms must take a new and more pre-emptive approach to managing their data, seeking out innovative, low-cost ways of improving its quality.
Sophisticated AI-based technology can be particularly helpful in this respect, enabling firms to clean up, enrich, aggregate and match information before it enters downstream applications and creates exceptions. Importantly, the management information and business insights yielded by intelligent automation has the potential to transform institutions’ data into a valuable strategic asset at a far earlier stage than is currently possible, offering firms a vital lifeline in their efforts to lower overheads, boost efficiency and raise competitiveness.
Change in data management practices is also essential if the industry is to prepare for the future through digital transformation exercises and, more specifically, by taking advantage of technological advances in AI and machine learning. The effectiveness of AI-based tools rests squarely on the data they have access to and, if the information they have available to work with is flawed, their value is impacted. Given that AI-driven technology surely represents the future for the finance industry, it makes more sense than ever for the sector to put its house in order and improve the accuracy of its data.
