Transaction Banks Add Value With Data

Fintech and automation are critical to growing transaction-banking services in the era of Big Data.

Faced with more-demanding corporate clients in a multibank environment, transaction banks have invested millions of dollars in creating a seamless technological experience by integrating their banking platforms with those of their corporate and institutional clients.

Treasurers want real-time visibility and control over their cash and liquidity, to minimize external borrowings, effectively manage working capital and maximize returns, according to Chet Kamat, CEO of Oracle Financial Services Software. “It is critical to have systems that not only effectively manage and monitor transaction-based liquidity but also help corporates project their positions based on future cash flows,” he says. “Treasurers are looking for an integrated system that makes it simple to monitor positions across multiple geographies, with multiple banks, and that eases reconciliation between bank systems and corporate systems.”

To achieve this, corporates will look for the right partner to help them gain efficiencies from new banking technology for their treasuries. “Banks need to offer tailored solutions that satiate customers’ immediate needs, undertake faster payments, improve transparency, support industry standards (ISO 20022), manage liquidity in real time and facilitate efficient multibanking relationships to ensure better treasury management,” says Kamat.

Sankar  Krishnan, Capgemini
Krishnan, Capgemini: When you add the cash-management aspect to the same blockchain, it is an excellent choice for customers, with significantly lower risks for each party.

Banks have historically been able to meet basic-to-intermediate treasury needs, such as information reporting and domestic payments, quite well. However, when it comes to advanced treasury requirements at most large or multinational treasury departments, banks have not fared well in meeting client needs. “These more-complex treasury departments tend to rely on nonbanking treasury-technology providers to meet requirements such as global payment processing, foreign-exchange risk management, reconciliation and in-house banking,” says Andrew Bateman, head of corporate liquidity and bank treasury at FIS. “Many banks are reassessing their treasury-product road maps and digital-transformation strategies, to better position themselves to meet customer requirements, retain existing clients and grow their treasury businesses with new clients.”

Hybrid Models Bring Innovation

Andrew Bateman, FIS
Bateman, FIS: Many banks are reassessing their treasury products and digital strategies.

Bateman argues that banks should be looking to financial-technology specialists—fintechs—to help innovate in all areas of treasury. He points to use of application-programming interfaces (APIs) to help spread the cost of innovation and shorten the time to market for services. FIS’s treasury department, for example, recently successfully tested real-time payments using the FIS Trax “payment factory” and a Citi API. “While APIs specifically address the issue of how easily and efficiently a client can communicate with the bank, performing both inbound and outbound transaction processing, the opportunity to improve the client experience goes far beyond simply the API,” states Bateman. “As banks reassess product strategies and undertake digital-transformation initiatives, they are reconciling their own, more-significant technological limitations with fintech solutions that can help to address treasury-technology gaps without a significant one-time build effort, major investment or high internal-support requirements.”

Machine-Learned M&A

Various M&A challenges can be solved with automation and advanced analytics, according to Sankar Krishnan, executive vice president for capital markets and banking at Capgemini, who outlines the benefits of applying machine learning and artificial intelligence to customer data, market data, bank-specific ratings and other data in transaction banking.

• Assisting in categorizing and gathering documents

• Enabling increased investment-banking sales using “knowledge bots” and “chat bots”

• Automating inefficient and outdated processes through robotics and cognitive solutions

• Eliminating duplicate work to simplify information sharing across functions

• Reducing work for sellers and advisers

• Centralizing the entire deal process into a single workflow—for example, using specialized workflows such as PEGA

• Streamlining the due-diligence process

• Identifying anomalies in documents that deviate from a pattern or from market standards

Sankar Krishnan, executive vice president of capital markets and banking at Capgemini, predicts fintech will lead banks into a hybrid model whereby banks plug in what works for them through an API. That allows the bank to do what it needs to do via the back end, while the customer-facing front end happens via the API. He cites Moven Enterprise as a good example of getting this right, as both TD Bank in Canada and Westpac in New Zealand use Moven’s mobile money-management tool inside their own platforms to provide customers with better outcomes.

Oracle’s Kamat says open banking is an opportunity to embed financial transactions seamlessly in business transactions. “In my conversations with banks, they see tremendous value in the idea. Removing friction in the business flow of the customer has multiple direct benefits for everyone involved. Higher STP [straight-through processing] rates mean lower costs. Better financial flows mean better liquidity positions across the chain, and higher data transparency means less time spent in reconciliation of information.”

He says it’s important for banks to establish which customer business flows they want to target before deciding if open APIs should be deployed in direct integration with corporate systems or partnerships with fintechs. “The opportunity for innovation is in identifying those points in the business flow where you want to embed your bank and own the customer’s business.”

Payment Paths

Addressing predictability and tracking of a transaction in the payments lifecycle has, according to Kamat, ushered in innovation. The SWIFT global payments innovation (gpi) initiative is one example. It is expected to improve customer experience, but more importantly to give the bank a transparent view and end-to-end tracking of cross-border payments, as well as to provide a facility to stop payments. “With gpi, there is a sort of service-level agreement on execution of cross-border payments and complete visibility to the banks on what stage of the transaction the payment is currently in,” Kamat explains.

There are more than 15 instant-payment networks across the world, including the Single Euro Payments Area and the Immediate Payment Service, which cater to immediate payment initiation, transaction and settlement.

Horton, BAE: Criminals are now exploiting investmentbanking products, commercial banking, and especially trade finance products to disguise the global fl ow of illicit funds.
Horton, BAE: Criminals are now exploiting investment banking products, commercial banking, and especially trade finance products to disguise the global flow of illicit funds.

“The dynamics of the industry have been undergoing rapid change,” Kamat says. “The use cases for payments now also include a flexible way for payments to be made and received from both retail and corporate banking perspectives.” Banks need to adapt their payment infrastructures to provide more-transparent data management combined with speed and stricter compliance with regulations.

Blockchain enables faster and cheaper cross-border payments with the Ripple payment-processing engine, built on distributed-ledger technology, which is being used by over 100 financial institutions including Santander, UniCredit, UBS and Standard Chartered. SWIFT’s payments initiative was a response by the banking industry, looking to address this threat. The next big bet is on SWIFT’s adoption of blockchain through gpi. SWIFT has adopted Hyperledger for its blockchain pilot and experimented with running messages using the Hyperledger platform. The hope is that this initiative will result in fewer reconciliation needs between banks, apart from addressing the timeliness of payment delivery.

Trade Transparency

Krishnan says blockchain will help speed up transactions, make them more transparent and fight fraud by providing everybody with the same information at the same time. “When you add the cash-management aspect of this—such as clearing, settlement and payments—to the same blockchain, it is an excellent choice for customers, with significantly lower risks for each party.”

Rob Horton, head of financial-crime solutions for Europe, the Middle East and Africa at BAE Systems Applied Intelligence, says criminals are now exploiting investment-banking products, commercial banking and especially trade-finance products to disguise the global flow of illicit funds.

Chet Kamat, Oracle
Kamat, Oracle: The opportunity for innovation is in identifying where you want to embed your bank and own the customer’s business.

BAE Systems looks deeper into the context around a transaction with network-analytics technology—even overcoming the challenges of disparate and poor-quality data—automatically linking counterparties, identifying common directors and beneficial ownership, and detecting circular flows of funds. “By using these more-sophisticated technologies, we have seen that large banks are much better able to detect suspicious behaviors, with much greater accuracy, to reduce the operational costs of compliance,” he says.

Kamat concurs with this assessment of the importance of machine learning in fighting financial crime. He also points to its usefulness in large, dynamic datasets, such as those that track consumer behavior by identifying and correlating patterns with available data. “When behaviors change, it can detect delicate shifts in the underlying data and then revise algorithms accordingly. These exclusive capabilities make it relevant for a broad range of functionalities, especially around automated payment repair services.”

Owing to the amount of data that needs to be analyzed before an M&A deal is consummated, Krishnan sees great potential for advanced analytics and machine learning in solving many of the speed, cost and risk challenges involved. (See box.)

Many banks have created data lakes, and most are ensuring that their old documentation is valid in the electronic age. By enriching clients’ data using artificial intelligence, banks and their corporate customers alike should benefit.