1) The document discusses the development and implementation of a debt collection automation system for a large retail bank over two phases. 2) The first phase automated the pre-collection stage processes and integrated various systems like dialing and banking software. This decreased the pre-collection workload by three times. 3) The second phase automated additional soft-collection stage processes like customer information access, communication history, and contract details. This helped the bank manage problematic debts 32% faster on average.

1. Collection
& recovery
a Debt Collection Management
System

2. Debt Collection Automation
in Just three Months
Learn how debt collection automation helped our banking client decrease the
workload by three times and speed up management of problematic debts.
Project Essence
Collection is a past-due debt management collection system. It covers all
banking front-office workflows related to debt collection.
Decision-making strategy development — completed
Pre-collection stage operations — automated
Soft-collection stage operations — automated
Hard-collection stage operations — in progress
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3. Challenge
The customer, the owner of the Collection system, is a sizable retail-oriented
bank with a focus on lending to SMEs. Therefore, debt collection management
is one of the bank’s essential business operations.
Facing major productivity bottlenecks in this area, the bank came to the
realization that debt collection automation was what they required most for
their business development.
As the bank had already used FICO-based solutions with satisfying results,
they chose FICO as the basic technology for the automated debt collection
system to be developed and implemented by an external vendor.
Our company was well familiar with FICO, and as we had already been in touch
providing on-demand consultations to the bank's managers, we were chosen
as a reliable and qualified contractor.
Our long-term cooperation was subject to our team’s successful completion of
the first project stage, which included delivering the following:
A core server-side module that would make it possible to add new
features in the future
A database management system
A web application with basic features
A mobile application with basic features
All the required internal and external integrations
Pre-collection stage process automation
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4. Solution
Thanks to the choice of the OutSystems-based FICO Application Studio and
Oracle technologies, we carried out the development of all the first-stage
components swiftly.
However, integrations were the trickiest part, since they differed considerably
and the system required a string of them. Despite this challenge, our senior
developers handled integrations expertly and finished this stage on time.
These are the software and services we successfully integrated:
Avaya Predictive Dialing System (PDS). A hardware-software solution
for both inbound and outbound calls. The Avaya solution had already
been in use at the bank when we started the project.
Automated Banking System (ABS). This integration of the bank’s
existing software was essential for seamless data exchange.
Yandex.Money. This external financial service is widely used by most
banking institutions, including our customer.
There was only one crucial issue during the first project stage. When the
development was in full swing, the customer’s executives decided to change
the way the dialing system was to be implemented.
For a long time, the bank had been using the software architecturally based on
an enterprise service bus. Its high complexity caused overspending on the
implementation and testing of every single change in the requirements.
To mitigate that, the idea was to switch to microservices. However, the
decision came rather late in the project, especially as the customer expected
the deliverables as soon as possible.
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Dealing with a Mid-project Change to the
Architecture

5. Recognizing this major time constraint, our team suggested reusing the old
code partially to save time while achieving the same outcome. As a result, we
successfully repackaged the legacy backend into a microservice container.
Pre-collection Stage Process Automation
At this stage, we thoroughly reviewed the business rules that made part of the
pre-collection stage processes and put all of them into the FICO Blaze Advisor
Business Rules Management System. Then we implemented the required UI
elements for enabling the execution of processes within the system. Finally, we
run the tests to ensure that everything worked properly.
This was the end of the first iteration, and as we met all of the customer’s
requirements, they decided to continue the project with us as their contractor.
Debt Management Collection System: Phase Two
The second iteration included the debt collection automation of the
soft-collection stage processes.
The list of automated operations looks as follows:

6. - Customer Information File (CIF) preview. In the automatic query processing
mode, the next CIF headline is displayed automatically once the processing is
initialized. Users can easily search and sort CIFs using filters.
- Customer contact details editing. The bank’s staff member can update all the
contact details if necessary, simply editing the appropriate field and then
clicking the ‘Save’ button.
- Data input based on communication results. The results of every
communication session must be reflected in the CIF. There is the special ‘Call
Result’ reference form available for it. Users can access it by clicking the
button of the same name.

7. - Communication history preview. All the communications with a certain
customer are stored in the ‘Request History’ folder. This information can be
sorted by the history of requests, changes, edits, and batch uploads.
- Contract data preview. In the ‘Supervisor Only’ mode, there is the possibility
to preview the details of customers’ contracts. The user with the Supervisor
rights can also add necessary actions for specific contracts only.
- Loan amortization schedule preview. Staff members can preview the
up-to-date loan amortization schedule for every customer in the system. It
contains planned and factual dates of payments, primary debt and percentage
changes, and factual payments for easy comparison.
- Debt estimate. The system allows users to estimate outstanding debt for up
to the next 15 days.
- Adding and activation of new services. It’s possible to add new services for
the existing customer via the ‘Add a Service’ button. Some of the new services
require the loan amortization schedule to be re-estimated. The decision of
whether to start a new service or not is based on the selection in the ‘Result’
droplist.
- Arranging and editing of branch-based meetings. The meetings in the office
can be arranged for the purpose of refinancing. All the arranged meetings can
be found in the ‘Meetings’ folder. Only those meetings that are currently in the
‘Planned’ status can be edited.
- The history of adding and activating services. It is possible to view the
history of added and activated services per contract. The report contains the
service name, status, date of activation, and username.
- Sampling for data analysis. The ‘Supervisor Only’ mode allows users to form
a fetch based on selected parameters. The list of parameters can be adjusted
manually or imported into an XLSX file.
- Batch updating. The batch updating can be executed by importing the XLSX
file or based on the sampling with the parameters adjusted manually.

8. Impact
The first iteration resulted in a threefold decrease in the pre-collection
workload.
After the first six months of operation, the Collection system made it
possible to manage problematic debts 32% faster on average.
As our cooperation expanded from one iteration to the next, the bank
became one of our biggest customers. Now, we continue to collaborate on
other projects.