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Feeling the pressure of faster payments:
With increased focus on faster payments, the time window for funds check based decisioning of payments is expected to get shorter just as for other categories of business validations on a payment. This is seen to increase the risk associated with rushed decisions on payments that meet with liquidity crunch. It is usually found that the time spent on resolving insufficient funds related exceptions is more than that spent on other categories of business exceptions.
Decision data:
Payments that pass the funds check process are instantly relegated to history. The ones that are delinquent from a funds availability standpoint go through a rigorous grind before the bank decides on what to do such payments. Multiple eyes get involved in the entire referral process with justification data also known as decision data, starting to collected at various levels of appraisal. Decision data carries the background information for the payment and feeds into the decision process. This data also includes notes, memos and remarks captured by the reviewers which represent the insight gathered from looking at various dimensions. It may also include the correspondence exchanged with the customer. As the referred payment moves across the decision hierarchy, data capture reduces and more time is spent analyzing and interpreting the justification data. This data is therefore extremely precious as it explains why the payment was rejected or progressed. This still does not always include deep insights related to how the customer has behaved in the past, depth of relationship, overdraft inertia and other critical dimensions that do not get recorded in the decision data for others to see.
Changing the Payments Middle Office
This data extraction, data analysis and linkage to the delinquent payment takes most of the time and has mostly been manual in nature handled in the payments middle office. Though credit risk monitoring has traditionally seen huge investments from an automation standpoint there are still avenues where lack of automation is significant. Moreover with paper based payments increasingly becoming electronic; the electronic payment traffic is on an upswing. Though the percentage of e-payments with NSF situation has large remained in a band, with an ever increasing of payments base, the volume of payments needing funds availability based Pay / No Pay decisions is enormous enough to make the minimalist system support, glaring. There is hardly any tool that automates data extraction and presentation of the information for review and decision on payments that in the first pass were found to be short covered. With the overall time window reducing for data gathering, distillation and decision derivation, payment related credit risk monitoring and control becomes time sensitive. Time window for decision making was never a factor to be considered when judging the quality of the decision. This is rapidly changing. Banks need to gear up to meet the challenge linked with faster decisions that are prudent.
A new tool taking birth?
For the kind of time imperatives around quicker decisions on insufficient funds linked payments and collections, that the banking industry has started to witness, a full bodied payment decisioning support is needed. Banks have started to scout the market for such applications. The business case for justifying such applications is essentially based on the time and effort saved through features such as:
- Pseudo decisioning on delinquent payments
- Historical data churn using a data centrifuge
- Ability to define business flow for payment decisioning
- Setup of payment purpose code linked account hierarchy and payment limits
- Fund source coalition
- Credit risk watch tower
Vendors in transaction banking space are beginning to seize the opportunity. On the fore front are those that already have essential ingredients such as process designer, rule engine, external system communication hub, referernce data store
These sure are interesting times to watch out in the area of Payment linked Credit Risk Monitoring and Control.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Jitender Balhara Manager at TCS
22 December
Arthur Azizov CEO at B2BINPAY
20 December
Sonali Patil Cloud Solution Architect at TCS
Retired Member
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