Banking & Financial Services

Banks & financial services companies capture customer's information through multiple channels (online, paper forms, mobile platforms, 3rd party platforms. etc.). The customer capture processes often include identity verification, background checks, financial fraud and AML (Anti-Money Laundering) checks, etc. Naturally, to be successful, this process requires data to be captured and queried from different internal and external systems.

Transfer Handwritten Forms to Computer Text with Computer Vision

Today, our technology extends the reach of automation beyond the limits of scanning with optical character recognition (OCR). Imagine a world where your hard copy documents completed by customers in their own handwriting has the information on the handwritten form automatically typed into your banking systems.  The Ntansa AI-enabled Computer Vision technology makes this a reality today.  Banks are able to increase speed and accuracy of data entry from paper handwritten forms to automate full end to end customer onboarding and related workflows.

Modernize Your Data Entry and Management Processes

The data access and population processes require operational staff to execute repetitive tasks. This is where Ntansa intelligent automation solutions are capable of modernizing and performing these tasks, similar to the way a human would. The intelligent automation bot accesses and populates information into multiple systems and follows a rules based workflow in doing so. Over time, by leveraging machine learning, the intelligent automation process is trained to read various forms of documents regardless of the format they are presented in.

In addition, intelligent automation can integrate banking systems together at the screen/UI level without the need to develop costly low-level systems integration, use API or other system integrations.

Similarly to any well designed and executed digital transformation program, it is recommended that intelligent automation be delivered in an agile or phased approach, with initial implementations focused on rules-based tasks and gradually developing more complex and AI-based automation through each stage of our deployment methodology.

The vast majority of mortgage loan processes involve multi-channel loan origination systems, G/L systems, document management and imaging systems, third-party service provider data integrations, etc. The repetitive and closely regulated sector of the mortgage industry.

Mortgage Industry Change and Regulatory Compliance

The mortgage origination process often differs based on a number of factors, including the size of the lender and by the state of the secondary market’s regulatory environment. For example, before the financial crisis of 2008, the global secondary markets were dominated by private banks. Today the same secondary market is dominated by government-sponsored entities and that puts the onus on banks to operate in under very different regulatory requirements. Over time, it’s entirely possible that markets may be relaxed again and compliance procedures may be adjusted once again.  In Africa, many economies are undergoing corrections and adjustments on banking requirements which has resulted in the collapse, consolidation, or forced closure of many smaller banks.

In light of these are other similar challenges, CIO rarely agree to make investments in technology where the ROI is span over multiple years before the business is able to reap the returns. This is where intelligent automation can address many “low hanging fruit” opportunities.

Some Examples:

1. Using intelligent automation to quickly enable 3rd party data integrations (e.g. asset and employment verifications, tax returns, credit reports, appraisals, etc.)
2. Intelligent automation can support call center staff with case management by pulling and posting data with minimal to zero manual intervention
3. Using intelligent automation as a substitute for traditional time-consuming backend SDK/API for systems integration where real-time integrations is not required. For example, capturing loan application details using various channels and running an automated batch process in the backend to pull and post data into various systems

Increased consumer demand and expectations due to the mass entrance of fintechs and mobile technologies have created the need for banks to offer flexible, smart and innovative card solutions to their customers. Citigroup CEO, Michael Corbat warned in November 2019, that if banks don’t take on the serious work of offering innovative and lifestyle solutions to their customers, they risk becoming ‘dumb utilities’ to the likes of Google and other tech firms entering the financial markets.

However, the data and customer relationships bank have will continue to be their greatest asset and that paired with technologies like artificial intelligence, machine learning and intelligent automation, banks are themselves able to create fintech like solutions to meet customer expectations.

Some Examples:

1. Pull in credit card applications from multiple channels, including handwritten documents, and process them into the Bank’s core systems.
2. Manage the end to end lost/stolen card case process. Intelligent automation can support call center agents with pulling and posting data from various systems of records to ensure cases are managed quickly. For example, a debit card data breach issue; most banks will have their staff key in the data into their systems of record. If the total data entry process requires 100 hours at $17 an hour ($13 plus benefits). The total of $1,700 would just be a hard tangible cost. The opportunity cost of what that same employee could accomplish over those 100 hours when freed up by intelligent automation software is where banking and financial services leaders are winning.
3. As a rule of thumb, intelligent automation can do the same amount of work as approximately 6 people.

The Centralized Online Real-Time Exchange (Core) banking system is the backbone of banking operations. However, not all core banking systems have kept up with the pace of technology nor have they made it easy for banks to innovate and transform themselves to better meet customer needs. Many Financial institutions run core banking software they built or have been customized to their operations.  These banking institutions are often sequestered by technology debt which makes changes, upgrades and integrations time consuming and not cost effective.  In these situations and countless others, intelligent automation provides a proven means to both innovate and boot productivity.

Some Examples:

1. Customer information updates, address changes, job, and lifestyle, etc
2. Account reconciliations
3. Cheque validation processes
4. Overdraft protection integrating with 3rd party systems and Bank’s internal procedures

Audits are a fact of the banking industry and an ongoing part of any successful risk and compliance function. Although many banks have made investments into their IT operations to automate some of the business processes involved with BPO or similar older technology, the reality remains that many of the IT investments made are unable to keep up with the pace and nature of change related to risk and compliance.

The power of intelligent automation is the speed of implementation and the agility of updates which empower banks to react quickly to changes.

Some Examples:

1. AML & fraud checks using the internal bank processes and 3rd party data integrations
2. Risk reporting and analysis
3. Data quality and validation
4. Internal controls testing and assessment