Market Segment: Overall
This is a custom report for Coforge (Coforge) presenting the findings of the NelsonHall NEAT vendor evaluation for RPA & AI in Banking in the Overall market segment. It contains the NEAT graph of vendor performance, a summary vendor analysis of Coforge for RPA & AI in banking services, and the latest market analysis summary for RPA & AI in banking.
This NelsonHall Vendor Evaluation & Assessment Tool (NEAT) analyzes the performance of vendors offering RPA & AI services in the banking sector. The NEAT tool allows strategic sourcing managers to assess the capability of vendors across a range of criteria and business situations and identify the best performing vendors overall, and with specific capability around RPA, AI, and supporting new digital banking models.
Evaluating vendors on both their ‘ability to deliver immediate benefit’ and their ‘ability to meet client future requirements’, vendors are identified in one of four categories: Leaders, High Achievers, Innovators, and Major Players.
Vendors evaluated for this NEAT are: Atos, Capgemini, CGI, Firstsource, Genpact, HCL Technologies, Infosys, LTI, Mphasis, Coforge, NTT Data, Tech Mahindra, Wipro, and WNS Global Services.
Further explanation of the NEAT methodology is included at the end of the report.
NelsonHall has identified Coforge as a Leader in the Overall market segment, as shown in the NEAT graph. This market segment reflects Coforge’s overall ability to meet future client requirements as well as delivering immediate benefits to RPA & AI clients in the banking sector.
Leaders are vendors that exhibit both a high ability relative to their peers to deliver immediate benefit and a high capability relative to their peers to meet client future requirements.
Buy-side organizations can access the RPA & AI in Banking NEAT tool (Overall) here.
Overview
Coforge has been active in RPA since 2015, initially applying RPA to fund administration processes at a leading wealth management platform provider. Previously, the processes were processed manually. Coforge started a COE for the client and partnered with UIPath to identify processes and implement RPA for those processes. After the initial automation of fund administration processes, over eighteen months, Coforge extended the robotic automation into customer interaction processes, as well as reporting and general ledger processes.
Strengths
Challenges
Coforge will continue to largely target RPA and AI opportunities within capital markets and transaction-based processes within financial services. Many of the company's RPA implementations so far have been client-specific, and so Coforge is looking to template its existing RPA configurations and apply them more widely within the financial services industry.
Coforge leads with its frameworks and domain knowledge to optimize processes and then automate them. Clients are charged when bots become operational. Coforge receives the bulk of its RPA revenues from ongoing operations support so that clients are paying for service as they are receiving the benefits of that service.
The company is actively assisting clients to establish RPA COEs, which enables Coforge to become a long-term service provider to the client and help the client to scale RPA and AI within their organization. Coforge is expanding its technical capabilities by developing POCs using machine learning to make inferences based on past data in support of capital market processes and the IT service desk. Finally, Coforge is developing its automation platform using open-source code. The bots developed will use AI to enable OCR at lower price points than existing third-party RPA solutions.
Coforge is well-positioned to respond to capital markets firms, and banks demand RPA and AI engagements. It has a robust framework for process consulting and RPA implementation, a good installed base of RPA projects, a large portfolio of managed support services, and a strong pipeline for additional RPA and AI projects. Coforge has grown its RPA and AI practice in banking by ~20% per year over the last two years. It should be able to grow this practice in double digits per year for the next five years. Beyond that, to continue to grow its RPA and AI revenues in banking in the high single digits, it will need to develop aggressively:
Overview
The banking industry is adapting to new business conditions where they need to drive revenues from the faster introduction of new products which will have lower profit margins than in the past. Delivering these products profitably will require highly standardized, consolidated, automated operations across multiple products and markets. Operations need to be able to scale up/down with a very low cost of delivery.
Drivers in the market for banking RPA and AI services include:
RPA and AI services are established with tier one banks in mature markets. Lower tier banks are beginning to consider widespread adoption due to severe cost pressures.
The primary client profile is:
Clients are buying service bundles including:
NelsonHall estimates the size of the RPA and AI Services in the Banking market to be ~$635 m in 2018, and that it will grow at 14.9% per year in the period 2018 to 2023.
The RPA and AI Services in the banking market start with Consulting, which accounts for ~20% ($130m) of client spend and is growing at 10.0% over the forecast period. Design & Deploy accounts for ~50% ($320m) of client spend and is growing at 15.0% over the forecast period.
Finally, Operations support accounts for ~30% ($185m) of client spend and is growing at ~18.9% over the forecast period.
The key challenges in the market for banking RPA and AI services include:
External challenges
Key success factors for clients include:
NelsonHall’s (vendor) Evaluation & Assessment Tool (NEAT) is a method by which strategic sourcing managers can evaluate outsourcing vendors and is part of NelsonHall's Speed-toSource initiative. The NEAT tool sits at the front-end of the vendor screening process and consists of a two-axis model: assessing vendors against their ‘ability to deliver immediate benefit’ to buy-side organizations and their ‘ability to meet client future requirements’. The latter axis is a pragmatic assessment of the vendor's ability to take clients on an innovation journey over the lifetime of their next contract.
The ‘ability to deliver immediate benefit’ assessment is based on the criteria shown in Exhibit 1, typically reflecting the current maturity of the vendor’s offerings, delivery capability, benefits achievement on behalf of clients, and customer presence.
The ‘ability to meet client future requirements’ assessment is based on the criteria shown in Exhibit 2, and provides a measure of the extent to which the supplier is well-positioned to support the customer journey over the life of a contract. This includes criteria such as the level of partnership established with clients, the mechanisms in place to drive innovation, the level of investment in the service, and the financial stability of the vendor.
The vendors covered in NelsonHall NEAT projects are typically the leaders in their fields. However, within this context, the categorization of vendors within NelsonHall NEAT projects is as follows:
The scoring of the vendors is based on a combination of analyst assessment, principally around measurements of the ability to deliver immediate benefit; and feedback from interviewing of vendor clients, principally in support of measurements of levels of partnership and ability to meet future client requirements.
Exhibit 1
Assessment Category | Assessment Criteria |
---|---|
Offerings | Breadth of application of RPA & AI to banking |
Application of RPA and AI to retail banking processes | |
Application of RPA & AI to capital markets processes | |
Application of RPA & AI to compliance | |
Application of RPA technology to banking | |
Application of AI/cognitive technology to banking | |
Ability to offer new process models with RPA & AI | |
Ability to benchmark processes and offer roadmap | |
RPA & AI implementation capability | |
Ongoing bot/AI management | |
Combined RPA/people-based exception handling capability | |
Delivery | Scale of RPA & AI delivery capability |
UIPath delivery capability | |
IPSoft delivery capability | |
Automation Anywhere delivery capability | |
Blue Prism delivery capability | |
Cognitive delivery capability | |
Delivery capability – U.S. | |
Delivery capability - U.K. | |
Delivery capability - Continental Europe | |
Delivery capability – Rest of EMEA | |
Delivery capability - APAC | |
Delivery capability - LATAM | |
Use of pre-existing RPA templates | |
RPA & AI change management capability | |
Maturity of RPA & AI delivery model | |
RPA & AI governance capability | |
Design thinking capability | |
Presence | Overall banking RPA presence |
Overall banking AI presence | |
Retail banking RPA presence | |
Retail banking AI presence | |
Capital Markets RPA presence | |
Capital Markets AI presence | |
U.S. presence | |
U.K. presence | |
Continental Europe presence | |
Rest of EMEA presence | |
APAC presence | |
LATAM presence | |
Benefits Achieved | Overall banking RPA presence |
Level of process cost savings achieved | |
Process error reduction | |
Process cycle time reduction | |
Improved CSAT |
Exhibit 2
Assessment Category | Assessment Criteria |
---|---|
Service Innovation | Perceived suitability to meet future client RPA & AI needs |
Perceived suitability to develop new banking business models & processes | |
Ability to apply automation to banking processes | |
Ability to introduce new digital business models | |
Service culture | |
Innovation & creativity | |
Level of Investments | In RPA |
In cognitive/AI | |
In RPA & AI in support of retail banking | |
In RPA & AI in support of capital markets | |
In own tools & platforms in support of RPA & AI in banking | |
In new RPA & AI-based systems of engagement for banking sector | |
Market Momentum | RPA market momentum |
AI market momentum |
For more information on other NelsonHall NEAT evaluations, please contact the NelsonHall relationship manager listed below.