Super SEPA in Five Steps In this high volume, low margin business, stability and reliability is king. SEPA itself is not that complicated. Banks have now moved to SEPA payments processing and those that have, have done so by implementing new SEPA processing applications. Firms such as Logica and Dovetail have good offerings in this space. But making it work, 100% of the time is critical. As a high volume low margin business, straight through processing rates are vital. Whilst there less regulatory exposure to missing a deadline, small failures in processing can lead to impacts on multiple customers. And unhappy customers can walk, quickly. Standardising SEPA also means it's easier to swap from one provider to another - and as banks digitise payments further, the ability for your customer to "sin bin" you for a day will increase, as they take their business elsewhere. Reliability and margin are a winner of business here, not speed. And whilst you're busy trying to process today's payments, your sales people are out there selling more SEPA services - and guaranteeing SLAs you know nothing about. So how can you ensure you meet your client expectation whilst decreasing your failure rate? I've implemented a new SEPA engine - won't that tell me what's happening? Making this happen is not easy. The SEPA engine sits at the centre of a complex web of end to end systems, each with their own infrastructure, support teams and SLAs. These periphery systems provide and take data not just for SEPA but also other payment flows. 1
Failures in any of these systems cause knocks-ons, not just to downstream systems but to downstream processes. A bad file upstream can increase the manual work load downstream. It's critical for the ops guys to get clear line of sight to what's happening in the end to end IT landscape. And it's vital for IT to understand the business context they are in. e.g. not looking at system availability, but looking at whether the business process can work. So the answer is proactive monitoring of my SEPA application then? But most SEPA monitoring systems look at the engine only. And technology monitoring will only tell you the upstream applications are running. How do you ensure your customer files hit the engine on time? How do you know they have left the company? How do you balance the work to fix an upstream system with a large payment file stuck in it, with the time to process it manually before the deadline? Typically most firms have around a 98-99% straight through processing rate. But given the number of payments each day, the 1-2% failure rate still leads to some pretty large rejects, returns and manual processing. A firm we worked with would process upwards of 20Mn payments a day, meaning 40000 manually processed items each day. And with much of this being same day credit transfers, they needed to have enough people available to do the manual processing at the right time. That's expensive. Having a real time view of whats coming down the track compared to a historical average meant they were able to better plan their resource utilisation and optimise costs. It's critical to provide real time status of the total end to end picture. In our experience, clients who have succeeded have done five key things well, and it's not just the individual elements; it s putting all pieces together where the whole is much greater than the sum of the parts. 1. Understand the end to end value chain which delivers the client outcome. And how the combination of system functions and people tasks combine and interact to achieve this. Many firms have mapped processes but we keep seeing the same issues. Mapping what people are doing and keeping systems as a black box and mapping discrete process parts, not how they combine to deliver end value. The focus here is to start with the client outcome. What products have been sold to which clients with what SLAs. Then work backwards from this to identify the end to end value chain. 2
And keep the process level consistent and simple; map a step whether done by system or person. In reality we find over 95% of a value chain is based in systems, either processing data or sending / receiving from ops. Lastly work out the critical dependencies and timelines. You should be able to start stress testing this on paper, playing "what if" games, understanding if a process step breaks what the next process step is, and which system or person provides it. 2. Define focussed performance metrics so you can turn a process step into measurable early warning performance outcomes To measure the process - and ensure performance - each step needs to be evaluated with simple questions to define KPIs. What must happen to ensure success? What continues to succeed and what indicates a successful outcome? Most operational functions and IT functions already have a daily checklist of items which can be enormously helpful here. Typical things to look for are: file arrival times, both internally and externally (from EBA for example); sizes of work queues for particular payment times through the day (ensuring the queue of rejects for same day credit transfers is zero by 5pm); all payments for gold level customers must be proceeded by 4pm; the system needs more than 25% free to process. This last example is important to understand capacity headroom with actionable outcomes. An alert that system capacity is nearing breach can be linked to automatic capacity provisioning. Once performance metrics are defined, thresholds can be applied for early warnings which allow enough time to fix before the process is impacted. Once complete, you can test the end to end system on paper to ensure you can actually meet the SLAs your sales people are promising. By helping one of our clients understand the end to end flow, they were able to see they could not meet the commitments their sales people were making under high stress conditions. This lead to a change in behaviour where upstream teams would warn downstream ops teams when large files 3 arrived close to deadlines, ensuring the ops teams had enough capacity to process any issues 3. Make it real time, contextual and actionable Having metrics is useful, but understanding performance of these in real time keeps clients and keeps the regulator happy. Making it real relies on being able to drill through the metric to understand what, in the technology landscape can tell you your performance. This is complex, difficult stuff and takes time and collaboration across technology departments and business. But the outcome enables you to gap analyse your existing monitoring, so removing risk from your technology platform.
Seeing the detail in real time is great, but of equal importance is seeing the context. Creation of real time dashboards showing where an issue is in the context of the end to end process gives a myriad of benefits. Users can quickly see where in a chain an issue really resides - cutting down vital decision making time. Support and Operations teams start to understand their role in the process. And issues get resolved quicker. Of course monitoring is nothing without accountability. Successful firms don't treat this as a tech exercise. They create reporting on KPI performance by process, by product and by business area and drive accountability for this down to grass roots. What follows is the organisation insisting that amber and red alerting is implemented, links to workflow and incident tools created and teams take action immediately to fix before fail. 4. Keep the history - predict and improve Whilst real time is important, once day to day issues are nailed its the trends which will hurt. The ability the extrapolate trends and predict failure points moves you from a managed operation to a smart operation. This area splits into three key elements. Firstly, the ability to alert on trended volume by asking is today normal? Whilst your system landscape looks fine and no alerts are being raised, seeing that volume is 10% more than it normally is across any part of the process, compared to a (say) 30 or 90 day average allows further pro-active action. Secondly the ability to extrapolate based on trends. You may see that historically you meet all of your service level targets and KPIs, but you don t see that you are getting closer and closer to breaching them. How long have you got until you do breach? Lastly, having historic data combined with business flow is hugely powerful. You can start to compare how the end to end process reacted to different events, look at bottlenecks and build out change programmes based on facts to optimise the flow. And going a step further, rolling up performance through aggregation logic into client products lets you start to compare product delivery performance against cost, to make powerful business decisions against. 4
5. Wrap the work into a top down change programme Lastly, its how you do it which is important. Those who are successful in making this work both short term and in the long term have considered the delivery of end to end monitoring as a change programme. They have created senior steering committees with Operations, IT and client facing product delivery people at a senior level to create a mandate for change. This stops arguments amongst the various operations and various IT silos on priorities and moves the focus to end to end performance. Equally important is understanding the softer side. How are people s job s going to change with the new monitoring? Do they understand their role in the context of end to end? We find early paper based scenario testing of huge value here to start bringing the users on board. Many firms deliver SEPA payments successfully day in and day out, but maintaining business and winning more business is about ensuring you can deliver on your client expectations. That means understanding your end to end delivery chain and the performance you need to meet, combined with a proactive real time monitoring approach. Those firms which win in this space have done five things well to get to super SEPA. 5
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