Banks and collections teams have a data problem. The issue isn’t the data itself or even a lack of data. Indeed, banks with thousands of customers are swimming in data.
Instead, the challenge is data governance and management. Large banks are complex entities with more than one core banking system. And it’s not only difficult to find the right information in the right system but also to sketch a holistic portrait of individual customers.
Financial institutions have realised there is great value from the data that they have in different systems. Especially for their collections operations where intelligent data can enable smarter decisions and better customer service throughout the debt lifecycle.
EXUS Financial Suite (EFS) fundamentally alters your relationship with your organisational data, consolidating the information and extracting valuable commercial insight from it. EFS improves performance at every stage, not just in delinquency.
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Data analysis means that banks can more accurately gauge the risk of offering a loan to a customer. The information you need to do this is already out there, it’s just a matter of capturing it, consolidating it and putting it to good use.
The three kinds of data
When we say ‘data’, we’re actually referring to three linked but different concepts. These are the three core kinds of data set for a modern financial institution and its collections operation:
System data: This is existing information already residing in the bank’s systems that can be fed into collections software. This includes things like CRM data, for instance.
Customer data: Information captured from interaction with customers. It hinges on interactions with customers: phone calls, SMS messages or an online self-service portal. EFS takes this even further, capturing qualitative data like a specific customer’s financial situation or their willingness to collaborate.
Intelligent data: It’s here where EXUS Financial Suite sets itself apart: intelligent data is the insight that’s created through the analysing behaviours, patterns and inputs present within your systems and customer data. EFS incorporates bleeding edge innovations like AI and machine learning to further enhance these insights.
Capture and analyse
The big question for financial institutions is ‘Do we have the IT resources to get the data in the system?’ Data isn’t valuable in and of itself. If this were the case, merely collecting it and storing it would suffice. And Excel can fulfil this function with aplomb.
Just capturing data ignores its real potential and usefulness. A spreadsheet can dutifully house numbers, but all that information will lack texture and be devoid of any meaningful, operational usefulness.
For data to be useful it needs to be:
- Consolidated into a single system
- Readily accessible for the entire organisation
- Comprised of all three kinds (system, customer and intelligent data)
An effective collections system creates additional, intelligent data. For example, behavioural data based on the communication that the agent has with the customer.
So if a customer has given a promise to pay, then the system can automatically check whether this was kept or broken, which is a critical indicator for collections strategy and for collections workflows.
Data as customer service
EXUS Financial Suite effectively captures and stores data -- but this is only the beginning. Once the information has been pulled into the system, it’s possible to build behavioural profiles of customers stitched together from their data. This is a critical first step in personalising your customer service.
Personalisation has been all the rage in the banking industry for a few years now. Customers have become accustomed to the services they use being tailored to them specifically. To achieve this, however, requires intelligent data. Luckily, over half of consumers would share personal data in return for more personalised commercial experiences.
Banks are not only collecting and storing and using certain strands of operational information, like, ‘I’m going to pay,’ or, ‘I am not going to pay,’ but more qualitative information like personal circumstances. A debtor’s specific challenges can be incorporated into your collections strategy.
This leads to a more enlightened, customer friendly collections process. Debt collections doesn’t have the best reputation with customers, in large part because it traditionally relied on a one approach fits all model. This lack of functionality makes the customer’s journey less efficient, as they have to search for the action they want to complete.
Personalisation helps remedy this perception, making it possible to meet them half-way. Portfolio segmentation makes the right offer at the right time possible. By prioritising accounts based on risk, phase and likelihood of repayment, collections departments see better results and increased revenue.
Into the future
AI and machine learning elements are becoming every day in the banking sector. UBS uses Amazon’s Alexa for customer service, JPMorgan is using bots to execute trades and Morgan Stanley has an AI fraud detection team.
Collections will not be missed by this wave of innovation sweeping the industry. The ability of AI to sift through massive amounts of data and identify patterns that might elude human observers is one of its greatest strengths.
AI and machine learning harbour immense promise for debt collections. But it’s contingent on having the structures in place for these innovations to offer value. If data isn’t stored or accessed in a structured way, banks will be unable to get this additional value.
If you have the right data, structured in the right way, you can program your collections software to do many things on its own, like calculating the risk, creating customer segments segment or running the workflows. This makes you more efficient, cuts costs and, perhaps most importantly, makes your customers happy.
Data, data everywhere
Your bank is swimming in data. Indeed, sometimes it can feel like you’re drowning in it. As we see, that’s information that’s already in your system and data generated through your customer interactions.
EFS makes this information useful, giving your bank the ability to collect, interpret and extract value from the information you already have. Forget about big data, this is fast data: not just storage but analysis.
Add in the AI and machine learning innovations of EFS, and suddenly a far more personalised and focused collections process springs into life. One that is more targeted, more effective and more enlightened.
To find out how EXUS can revolutionise debt collections in your organisation, get in touch.