For years businesses have manually dealt with millions of pages of documents, emails and various other forms of unstructured content to get work done. Companies have tried numerous process automation technologies to ease the burden, only to come up short because they couldn’t adequately deal with all the unstructured data. Only now, with the maturation of a branch of artificial intelligence technology called Deep Learning, is it becoming possible to deliver true process automation technology.
A prime example is in the financial services industry. Financial services companies operate in an ecosystem of partners, suppliers, customers and regulators that relies on the timely exchange of accurate information, most of it unstructured. Prior to the introduction of Deep Learning, which makes it possible to automate processes that deal with unstructured data, these firms attempted to use keywords and optical character recognition (OCR) technology to automate document-based processes and decision-making. While this was a step in the right direction, companies had to precisely structure queries and rules to get the desired result; any variation from what the computer expected would thwart the effort.
Deep Learning takes an entirely different approach. Instead of giving the computer instructions, users provide the computer with examples of what they’re trying to accomplish. From that, Deep Learning algorithms work backwards to create models to achieve the desired goal.
Intelligent Process Automation (IPA) takes the technology a step further by applying it to processes that normally require human decision-making or input. In a financial services environment, those processes include customer onboarding, commercial underwriting, trade order confirmation, financial document analysis and much more.
When implemented correctly, the results can be nothing short of astounding. It’s not uncommon to see reductions in process cycle times of 85%, a 4x increase in process capacity and an 80% reduction in required human resources. Not only does Intelligent Process Automation enable financial services firms to improve efficiencies and become more profitable, but it is also allows employees to move away from mundane tasks and work on higher-value projects.
Following are some examples of the most common use cases in financial services that benefit from intelligent process automation.
Customer Onboarding
Whenever a bank or financial services company gets a new customer, it requires reams of documentation to get the customer set up correctly in its systems. The bank will have its own forms, but may also require tax returns, statements from other institutions, and the like. It may also have to reach out to other institutions to pull credit reports or transfer funds, for example.
Consider just one data point: the customer’s nine-digit Social Security number. Some forms may render the number with dashes, located in the upper right of the page. Others may use only the nine digits, without dashes, and put it at the bottom of the page. Previous generations of document recognition technologies would have trouble identifying each of these as a Social Security number without being expressly told where to find it and what it looks like on each type of form. IPA tools for financial services, however, are trained to recognize the Social Security number no matter what form it may take and where it’s located. The same applies to all sorts of other information: customer name, address, account numbers—you name it.
With that kind of capability, financial services firms can largely automate the customer onboarding process, perhaps requiring only a supervisor to check for accuracy as a final step.
Financial Document Analysis
Another example of how financial firms use artificial intelligence automation is with document analysis.
Perhaps a company needs to examine Securities and Exchange Commission documents or other public company filings. Again, these documents may contain similar information – dollar amounts, for example – but present them in slightly different formats. Some have dollar signs, others don’t; some have two decimal places, others none. The same goes for tax ID numbers and a whole host of other criteria.
Intelligent process automation tools can recognize these differences and present data from multiple forms in a normalized fashion, so it can be input into the bank’s own digital systems and properly analyzed.
One application for this technology that virtually all financial institutions are now dealing with has to do with International Swaps and Derivatives Association (ISDA) standards that are being phased out and replaced. Many companies have customer contracts based on the ISDA standards that now must be updated, which can be a time-consuming process.
To date, most companies deal with this through a “4-eye approval” process for reviewing and cross-checking data inputs made when amending ISDA documentation. Inputs are added by one subject matter expert (SME), then manually inspected and approved by a second SME.
IPA solutions can automate the process, eliminating the need for manual validation and data review.
Commercial Loan Underwriting
Banks with detailed processes for appraising and approving mortgages, including data extraction and image recognition, can use intelligent automation tools to automate the process of extracting relevant unstructured data from onboarding documents, as well as to analyze images. IPA can be used to transform the mortgage approval process, allowing it to become far more efficient and consistent.
Trade Processing Automation
Investment firms receiving trade processing documentation via email and PDF formats can use artificial intelligence automation tools to extract relevant unstructured data from these trade documents and compile it into a normalized format that can then be integrated with the firm’s digital management system. IPA enables companies to eliminate untold hours of manual data processing.
IPA Brings a New Era to Financial Services
Artificial intelligence and automation technologies are bringing new capabilities to all sorts of vertical industries, and financial services automation is certainly no exception.
To learn more about how IPA helps automate processes that include unstructured content, download this free analyst report from the Everest Group, Intelligent Document Processing for Unstructured Documents.
