A playbook for banks on managing M&A integration

Banking

A playbook for banks on M&A integration

Efficient management of the complexities of disparate systems and data after an acquisition saves time and money.

Client

Banks that have merged or acquired new businesses.

Goal

Manage migration and integration complexity post M&A.

Tools and technologies

The Iris business acquisition playbook for banks.

BUSINESS CHALLENGE

In a low-interest rate regime, achieving scale is the only way for banks to stay profitable. The top 25 banks are growing at a rate faster than rest of the pack. The search for profitability from scale is predicated upon their ability to ensure that the operational costs do not grow linearly with business.
A significant part of this growth will come inorganically. Apart from M&As, brownfield expansion comes with banks selling off their books of business for reasons ranging from realigned strategic priorities to the more mundane need of raising cash. Any IT costs in absorbing the new book of work will negate the advantages of size.

SOLUTION

Iris has been working with banking clients to create a business acquisition playbook outlining steps to insource with a migration and integration strategy. We have enabled clients to deal with post-merger integrations and create a single source of truth for transactional data and positions. The Iris team delivered solutions specifically tailored for applications in the loan origination and servicing space.
We have helped our banking clients:

  • Consolidate multiple acquisition playbooks to create a single standardized framework for their lending business
  • Define insourcing steps for business and technology teams and create a migration strategy with quantifiable recommendations and a reusable checklist for insourcing activities.
  • Assess capability and readiness and help them choose from insourcing options:
  • Full migration of data and systems
  • Partial migration of systems and data migration and integration
  • Only data integration and connectivity for lending business.

OUTCOMES

We have helped clients achieve 50% savings in cycle time and cost for post-merger integration of business processes, application and data.

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Anti-money laundering: managing regulatory risks

Data & Analytics, Risk & Compliance

Anti-money laundering programs: managing data, regulatory risks

A global multinational bank successfully managed large data volumes in its anti-money laundering program and protected clients and franchisees from regulatory risks.

Client

A leading multinational bank

Goal

Identify and mitigate risks related to anti-money laundering (AML) regulations

Tools and technologies

Cloudera, Hadoop, Talend, Spark MLlib, MicroStrategy, Datameer, Sqoop

BUSINESS CHALLENGE

Our client, a multinational bank, had a comprehensive global program for anti-money laundering (AML) to protect its clients and franchisees from the risks of money laundering, terrorist financing and other financial crimes.

To be able to do so effectively, they needed to deal with mounting volumes of data, which their existing applications could not handle. Their systems also generated a high number of false positives that increased the need for manual intervention.

SOLUTION

We worked with the client’s global anti-money laundering program to develop a solution that provided them with consistent controls to identify AML risks and comply with relevant laws.

We incorporated a modern data lake architecture, a centralized data hub that allowed the processing of the increasing volumes of data from around the world. The solution we built was capable of handling data in petabytes.

OUTCOMES

We helped the multinational bank build a data lake that could hold 8 petabytes of data, much more than its existing data applications allowed. Next, Iris cross-trained the client’s global anti-money laundering team to ensure efficient use of the data lake in line with its global anti-money laundering program.

8 petabytes
Data capacity

14
Global regions covered

5,000
End users

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